View Full Version : Easy to use Offensive Power Rankings (OPR) program for mid-regional scouting
5:42 EST (v2): Updated with more DLLs in the binary zip which will hopefully allow it to work.
6:27 EST (v3): Updated with sorting and a reduction in verbosity.
I've spent a bit of time recently cleaning up my offensive power rating code and adding a few new features that I felt would be useful this year. The application is attached, as is the source code.
Features:
1) Automatically downloads current results from usfirst.org, parses them, and outputs the results, with only 3 parameters from the user (which regional, which year, and which statistic you want)
2) Three statistics: Offensive Power Rating, Defensive Power Rating, and Estimated +/-. The +/- is simply the OPR minus the DPR. It may or may not actually be useful (or correct!).
3) Easy to use, by my standards. Just double click, enter the parameters it asks for, and it'll download match results itself. Can also be run from a script with command-line parameters for people that want their statistics automated.
4) The parsing code is written so it can be used before a regional is complete. Obviously this reduces the accuracy of the outputted stats, and it doesn't even work before each team has played 2-3 matches. But this can be useful for the friday-evening scouting meeting to pick out diamonds in the rough.
Disclaimers:
1) There are people that don't believe OPR will be useful this year. I disagree with them, but keep that in mind.
2) OPR does not indicate just a robot's performance, but a whole team's performance. If a team has a weak robot but a stellar human player, they might still have a high OPR.
3) Having a high OPR in this game means very little without also having a low DPR. If you score 80 points in a match but always give away 100, you are not useful to your alliance.
4) I don't know how accurate the +/- stuff is, it is a result of me playing around. Hopefully some teams out at regionals right now can compare with their scouting data and give feedback.
Interpretations:
A high OPR might indicate:
-A robot that is very effective at getting balls into enemy trailers
-A HP that is very effective at getting balls into enemy trailers
-A robot that does the grunt-work at supplying empty cells so that its alliance can always score a couple super-cells
-Any robot that just 'greases the wheels' of its alliance, resulting in higher scores
A low OPR (yes, it can even be negative) might indicate:
-An otherwise good robot that takes a lot of penalties
-A robot that simply doesn't score much
-A robot impedes its alliance-partner's progress at scoring
A high DPR might indicate:
-No-shows or broken robots that spend whole matches with a stopped trailer, thus getting filled up
-Robots that tend to get into positions where they get scored on
-Robots that tend to get their alliance partners into positions where they get scored on
-Robots with no auto mode
-Generally, high DPR means low mobility. It is a robot that gets scored on a lot.
A low DPR might indicate:
-A mobile robot that can effectively keep its trailer out of trouble
-A lucky robot
Really, I should have called DPR something else, because a high DPR actually means you're very bad at defending your trailer.
Without further adieau, the attachments:
Rick Wagner
27-02-2009, 17:14
Sounds interesting. Before I download, what did you compile it with and for what platform (Windows XT I assume)?
Sounds interesting. Before I download, what did you compile it with and for what platform (Windows XT I assume)?
Visual Studio 2005, developed on Windows XP, though I'm pretty sure it'll work on Vista as well. It makes heavy use of Windows API functions for the internet stuff, I think you'll need the windows SDK to compile it.
EricVanWyk
27-02-2009, 17:27
I got this error :
This application has failed to start because the application configuration is incorrect. Reinstalling the application may fix this problem.
Rick Wagner
27-02-2009, 17:29
Visual Studio 2005, developed on Windows XP, though I'm pretty sure it'll work on Vista as well. It makes heavy use of Windows API functions for the internet stuff, I think you'll need the windows SDK to compile it.
Thanks. I have the SDK.
I got this error :
This application has failed to start because the application configuration is incorrect. Reinstalling the application may fix this problem.
Hmmm...
Try grabbing the Visual Studio 2005 redistributable:
http://www.microsoft.com/downloads/details.aspx?FamilyId=32BC1BEE-A3F9-4C13-9C99-220B62A191EE&displaylang=en
I'm going to update the .zip with the DLLs I think are necessary, but I don't have high hopes.
Samuel H.
27-02-2009, 17:40
I got this error :
This application has failed to start because the application configuration is incorrect. Reinstalling the application may fix this problem.
It appears there is a problem with the manifest for the program. When I viewed the dependencies using Dependency Walker, it provided these errors:
Error: The Side-by-Side configuration information for "c:\documents and settings\1880337\my documents\downloads\OPRNET.EXE" contains errors. This application has failed to start because the application configuration is incorrect. Reinstalling the application may fix this problem (14001).
Error: At least one required implicit or forwarded dependency was not found.
Warning: At least one delay-load dependency module was not found.
Warning: At least one module has an unresolved import due to a missing export function in a delay-load dependent module.
MSVCP80D.DLL and MSVCR80D.DLL seem to be the dlls mentioned by the warnings.
When I googled them, I found several mentions of people getting that error and solving it by selecting the "Embed Manifest" option when compiling. I don't know whether this correct or relevant.
Thanks
- Sam
Edit: Tried installing the redistributable, made no difference.
It appears there is a problem with the manifest for the program. When I viewed the dependencies using Dependency Walker, it provided these errors:
MSVCP80D.DLL and MSVCR80D.DLL seem to be the ones in question.
When I googled them, I found several mentions of people getting that error and solving it by selecting the "Embed Manifest" option when compiling. I don't know whether this correct or relevant.
Thanks
- Sam
I think there are two problems:
1) The .exe I zipped is the debug version, and so looks for debug DLLs that most people won't have
2) Some (most?) people won't have the VS2005 redistributable anyway.
Next time you do this sort of stuff, PM me so I can develop a mac version alongside yours!
I may try to port this one
Next time you do this sort of stuff, PM me so I can develop a mac version alongside yours!
I may try to port this one
Most of the math stuff should be easily portable, its just the downloading that is heavily dependent on windows.
Edit: here's the math library I used.
engunneer
27-02-2009, 18:19
Runs on my vista system
Thanks,
Just posted a v3 revision that sorts the output, reduces how much pre-statistic stuff it spews, and fixes a bug where the command-line version would pause for input.
engunneer
27-02-2009, 18:50
please add a "verbose" option that I can turn off :)
thanks.
EricVanWyk
27-02-2009, 21:05
Results from Jersey below (go 1923!!) :
OPR 1923 31.6079
OPR 708 29.8004
OPR 25 26.0054
OPR 816 25.0949
OPR 1006 24.1073
OPR 2753 23.9246
OPR 136 23.6915
OPR 1218 22.9299
OPR 223 20.6492
OPR 869 19.7636
DPR 136 32.7112
DPR 11 29.109
DPR 1616 26.7029
DPR 869 26.0814
DPR 223 25.7706
DPR 1048 24.3491
DPR 486 21.5663
DPR 219 20.9251
DPR 1617 20.6711
DPR 2344 20.3672
PlusMinus 1218 24.2442
PlusMinus 1923 22.7624
PlusMinus 102 21.6363
PlusMinus 2753 20.7922
PlusMinus 25 19.8969
PlusMinus 75 16.9573
PlusMinus 708 14.669
PlusMinus 423 14.5928
PlusMinus 816 11.5961
PlusMinus 1366 9.48648
I only listed the top 10, you'll have to download this cool chunk of code yourself to see the rest.
engunneer
27-02-2009, 21:07
Also, can you reverse the sort on DPR? (since lower is better, they should be at the top of the list)
great work, thanks.
This is pretty cool. I'm debating whether or not to use this or the matrix system I spent the last couple weeks setting up. I guess depending on the delay, doing it by hand is probably faster though, even if it is a pain. Anyway, seems to work fine on my vista system, and I didn't have to compile it with the SDK or anything. One question, though. Is it supposed to close after you enter a command after it gives you the requested stats?
engunneer
27-02-2009, 23:54
yes
you're supposed to run it from a terminal, so the window doesn't close.
if you run it from a command line, then you can give it the parameters all at once as well.
This is pretty cool. I'm debating whether or not to use this or the matrix system I spent the last couple weeks setting up. I guess depending on the delay, doing it by hand is probably faster though, even if it is a pain. Anyway, seems to work fine on my vista system, and I didn't have to compile it with the SDK or anything. One question, though. Is it supposed to close after you enter a command after it gives you the requested stats?
I wanted it to pause at the end if the user double-clicked on it. I couldn't remember the "press any key to continue" API call, so I did it in the poor man's way:
if(!fRunWithoutCommandLineParameters)
{
int a;
cin>>a;
}
DMetalKong
28-02-2009, 19:04
My friend and I were talking, and if you use the match points from the opposing alliance in the calculation, you can find the approximate number of points scored ON a robot during matches. Could be useful this year.
My friend and I were talking, and if you use the match points from the opposing alliance in the calculation, you can find the approximate number of points scored ON a robot during matches. Could be useful this year.
That's the DPR calculation. It can be phrased as "DPR is the average number of points that a team's presence adds to its opponent's score." aka, DPR is the average number of points scored in a robots trailer. It should be lower for highly mobile robots, and very high for no-shows or robots whose strategies or drivetrain tend to get them scored on.
Samuel H.
01-03-2009, 06:11
Hello,
Using v3 worked for me earlier, but I now have a new problem. Running OPRNet.exe kc 2009 opr downloads the match data, but fails when parsing with the error:
Parsing!
No matches found. This regional may not have run yet, or may have HTML output that the parser does not recognize.
Failure to parse XML. Code: -2147467259
I've attached temp.tmp
Thank you,
- Sam
Hello,
Using v3 worked for me earlier, but I now have a new problem. Running downloads the match data, but fails when parsing with the error:
I've attached temp.tmp
Thank you,
- Sam
Hmmm... the temp.tmp (which is simply the match results HTML page) simply doesn't have any match data. If you look at the KC results page (http://www2.usfirst.org/2009comp/events/KC/matchresults.html), you can see that the qualifying matches are no longer up. This looks like a FIRST problem.
Thanks for the bug report though!
billbo911
01-03-2009, 11:16
I'm currently "evaluating" this app for it's effectiveness with some very positive findings. The one thing that I would really like to do is to "export" the output into an Excel spreadsheet for ease of viewing offline. If I am not mistaken, the results are only sent to the screen. Is there a way to have them go to a ".csv" file, or some other format that can easily be opened in Excel?
I'm currently "evaluating" this app for it's effectiveness with some very positive findings. The one thing that I would really like to do is to "export" the output into an Excel spreadsheet for ease of viewing offline. If I am not mistaken, the results are only sent to the screen. Is there a way to have them go to a ".csv" file, or some other format that can easily be opened in Excel?
In a command line:
oprnet (regional code) (year) (stat) > blah.csv
This uses the DOS redirect operator to send it to a text file. The stats are are tab-seperated so that you should be able to copy/paste it into excel and have all the cells line up properly.
billbo911
01-03-2009, 12:14
In a command line:
oprnet (regional code) (year) (stat) > blah.csv
This uses the DOS redirect operator to send it to a text file. The stats are are tab-seperated so that you should be able to copy/paste it into excel and have all the cells line up properly.
Yep, that'll do it!! (Good ol' DOS, it still has some life left in it ;) )
By the way. I am currently running this on a Vista x64, quad core system with 8GB of ram. It absolutely rips! No mods were needed what so ever to get this running. THX!!
Yep, that'll do it!! (Good ol' DOS, it still has some life left in it ;) )
By the way. I am currently running this on a Vista x64, quad core system with 8GB of ram. It absolutely rips! No mods were needed what so ever to get this running. THX!!
Well, it's only solving a TeamCount x TeamCount matrix. Crazier stuff I've done in the past was post-season analysis involving every single team (1300x1300 matrix, or so), and that ends up taking a long time.
Also, v4 is done.
Changes:
-DPR is now called SAA for 'scores against average' to make its name more line up with its values
-You can now choose to sort by team. Command-line looks like this:
oprnet il 2009 opr t. If you don't want to sort by team, just put an 'r' there, or leave the parameter off entirely.
-Command-line users can now append a 'q' to completely suppress all non-error messages. For example, this:
oprnet il 2009 opr r q
will only print out the OPR values (or errors if there were any)
-Sorting for SAA/DPR is now reversed, so that the 'best' values come first.
Vikesrock
01-03-2009, 18:37
This just keeps getting better and better.
It looks like the SAA/DPR still sorts with the highest number on top (which ismost points scored against, right?)
Michael Corsetto
01-03-2009, 19:26
I'm running on a mac, is there any way that someone could run the app with the numbers from this week's regionals, export to Excel, and post the results on CD? I loved the OPR last year and it was very useful IMO. Thanks Bongle for making it even better this year!
Vikesrock
01-03-2009, 19:31
I'm running on a mac, is there any way that someone could run the app with the numbers from this week's regionals, export to Excel, and post the results on CD? I loved the OPR last year and it was very useful IMO. Thanks Bongle for making it even better this year!
Match results seem to have disappeared for a number of events. I'll try and remember to check over the next few days and do this when the results reappear.
engunneer
01-03-2009, 20:13
Here are OPR for the events that do have match results posted; a zip file of Team, OPR, SAA, and +/- (tab delimited for easy excel import).
each event is a separate text file.
I wrote a script that will generate these txt files on the fly in autohotkey. I can post (more or less uncommented) code if anyone wants.
This was made using v4 of OPRNet (yay for the new 'quiet' feature.)
Interpretations:
A high DPR might indicate:
-No-shows or broken robots that spend whole matches with a stopped trailer, thus getting filled up
-Robots that tend to get into positions where they get scored on
-Robots that tend to get their alliance partners into positions where they get scored on
-Robots with no auto mode
-Generally, high DPR means low mobility. It is a robot that gets scored on a lot.
...
High DPR can also mean that a robot purposely scored on his own alliance trailers to increase RS (ranking score) or to prevent a G14 violation.
I can tell you that we did this in 4 of our 7 Q-matches. And it got us the highest RS of all the 2 loss teams and allowed us to be seeded 4th. Without this strategy we would not have gotten to pick 1625 and and probably not have won the regional.
In one case we stopped scoring for ourselves with 30 seconds to go and scored about 40 points for the other alliance. So that also lowered our OPR a little bit. I think many the good veteran teams did this to some extent.
High DPR can also mean that a robot purposely scored on his own alliance trailers to increase RS (ranking score) or to prevent a G14 violation.
I can tell you that we did this in 4 of our 7 Q-matches. And it got us the highest RS of all the 2 loss teams and allowed us to be seeded 4th. Without this strategy we would not have gotten to pick 1625 and and probably not have won the regional.
In one case we stopped scoring for ourselves with 30 seconds to go and scored about 40 points for the other alliance. So that also lowered our OPR a little bit. I think many the good veteran teams did this to some extent.
Good points. I can't edit the first post anymore or else I'd add that.
I guess this is up to v5 now. The only difference of any substance is the new prediction feature. Basically, this uses the OPRs computed so far to predict the remaining matches at a regional, and prints out the simulated rankings afterwards. If all the matches have been played, it does a self-analysis to see how accurate it would have been. Based on this, I can say that it is about 65-70% accurate when predicting after 40-50 matches, though this seems to depend heavily on the regional. It is much better at predicting GTR 2008 (80%) than it is predicting DC 2009 (55-60). Still, it is generally a good bit better than a coinflip.
Command-line is:
oprnet <regional> <year> predict <sort style> <quiet flag>
So...
oprnet il 2009 predict t q
or
oprnet dc 2009 predict t
or
oprnet oh 2009 predict
or
oprnet on 2008 predict (this has pretty cool results)
The main problem with predicting match results is that robots evolve quite a bit over the course of a regional. Some break, some get fixed, some get improved tactics or mechanical parts. Without actual 'on-the-ground' knowledge of what is going on with individual robots, any purely mathematical model is going to fail. Getting 65-70% of guesses right isn't bad. But still, the 'predict' feature is an entertainment-only kind of feature.
billbo911
03-03-2009, 10:23
In a command line:
oprnet (regional code) (year) (stat) > blah.csv
This uses the DOS redirect operator to send it to a text file. The stats are are tab-seperated so that you should be able to copy/paste it into excel and have all the cells line up properly.
I just tested this method with v.5. I needed to save it as a .txt file for Excel to open it correctly. No big deal.
I also noted that Excel sorted it backward. In other words, the highest ranked team was listed last.Again, this is no big deal and can easily be dealt with.
I'll test more to see if I can get Excel to import it in reverse sort order.
I just tested this method with v.5. I needed to save it as a .txt file for Excel to open it correctly. No big deal.
I also noted that Excel sorted it backward. In other words, the highest ranked team was listed last.Again, this is no big deal and can easily be dealt with.
I'll test more to see if I can get Excel to import it in reverse sort order.
Oh sorry, I forgot to fix that. I knew there was something requested...
Any OPR listing for BAE regional?
Any OPR listing for BAE regional?
Nope, because the qualification matches have mysteriously disappeared.
Fireworks 234
03-03-2009, 10:57
Nope, because the qualification matches have mysteriously disappeared.
And Buckeye hasn't been updated yet, it's only got a few of the elimination matches in there and they don't even have the cities the teams are from for the awards yet.
Clinton Bolinger
03-03-2009, 11:40
Any chase you can have it run a full report, something like:
il 2009 opr saa pm t > blah.csv
That way you can bring all the data in to Excel at once instead of running it multiple times.
-Oris-
Any chase you can have it run a full report, something like:
il 2009 opr saa pm t > blah.csv
That way you can bring all the data in to Excel at once instead of running it multiple times.
-Oris-
I'll add an "all" option tonight.
engunneer
03-03-2009, 12:02
attached is a Autohotkey script I wrote (compiled and main source) that grabs every event in the eventlist.txt file, and makes a .txt file of the results. The result file is already arranged as they will be in the "all" option.
Thanks for the continued updates.
Any way you can grab data from TBA when First's rankings aren't available? I guess you would need a lookup table from (year,event) -> TBA eventID.
Killraine
03-03-2009, 12:34
Am I correct in assuming that each of the following should be sorted (best -> worst) like this:
OPR: High (best) -> Low (worst)
SAA (DPR): Low (best) -> High (worst)
+/-: High (best) -> Low (worst)
If I am right, it seems that V5 sorts them wrong, sorting all categories as low -> high
billbo911
03-03-2009, 12:37
I'll add an "all" option tonight.
While you are adding options...........
Being that this app is dependent on FIRST updating their postings accurately and in a timely manner...
In the odd situation where there would not be access to that data (ie. no wifi available at the venue) or when FIRST has not updated it completely, is thee a way we could create our own file containing all the match scores and teams in each match from regional we are interested in and then have OPRnet point to that data source?
While you are adding options...........
Being that this app is dependent on FIRST updating their postings accurately and in a timely manner...
In the odd situation where there would not be access to that data (ie. no wifi available at the venue) or when FIRST has not updated it completely, is thee a way we could create our own file containing all the match scores and teams in each match from regional we are interested in and then have OPRnet point to that data source?
Check my OPR thread from last year. That's how it used to work, and I decided it was an annoying way to do things, which is why this year's version has internet connectivity. Keep in mind you need about 30 matches before it starts being able to run OPR, so that'd be a lot of hand-entering.
I'll see about adding a TBA parser (it'd be pretty nice because TBA uses the same formatting for each year, unlike FIRST), but it looks like it'll be pretty annoying owing to the fact that TBA doesn't use the FRC acronyms for events so I'd need a big mapping from (year,event)->(tbaID).
If I am right, it seems that V5 sorts them wrong, sorting all categories as low -> high
Yep, that's on the to-do list.
Tom Schindler
03-03-2009, 13:05
Nope, because the qualification matches have mysteriously disappeared.
Anyone know what's going on with the official results from BAE? The only match results listed on FIRST's page are the elimination rounds, even those are not fully up-to-date.
Killraine
03-03-2009, 13:17
Also, since the scores are getting sorted anyway, could you add an actual number rank (ie highest opr would be 1, next would be 2, etc.)?
v6:
-Sorts OPR, SAA, and PMs in a more logical manner
-New 'all' statistic type that prints out OPR, SAA, and PM in a table. Different output for the console window versus command-line running so that you guys running it for excel will get your tabs, while the console-window people will still be able to read it.
Clinton Bolinger
05-03-2009, 11:21
Looks good...
When you try the following the Pos is just in numerical order:
OPRNet.exe il 2009 all t q > all.txt
Any chance you can have it show their Rank instead?
-Oris-
Looks good...
When you try the following the Pos is just in numerical order:
OPRNet.exe il 2009 all t q > all.txt
Any chance you can have it show their Rank instead?
-Oris-
Rather than 't' (for sort-by-team), use 'r' (for sort-by-rank). That'll sort the table by OPR first, though if you want to sort it, I'd recommend copying the contents of all.txt into excel and sorting there.
Killraine
05-03-2009, 12:40
When I sort +/- by rank, the highest ranked team is rank "0" rather than "1"
Edit: Also, it would be nice to be able to sort by team, but still see what rank the teams are when sorted by rating. Ie. Sort by rating first to get a rank value for each team, then resort by team number. I know its not really necessary if you just take the data and put it in excel, but it would be nice for the program as a stand alone.
Bongle -- do you mind if I port this over to Java? I want to try to get a real-time OPR Scoring program working by the time Atlanta rolls around.
Bongle -- do you mind if I port this over to Java? I want to try to get a real-time OPR Scoring program working by the time Atlanta rolls around.
Go ahead. If you're running it from a server, I think it'd be easiest to just run oprnet once each match is done and parse the results. Porting the math stuff might be hard.
SteveGPage
06-03-2009, 09:56
I have a general question that I would love for you all to consider. I am a firm believer in the OPR/DPR concept, and included it in our team's scouting application. But what I found was that in this game, ALLIANCE data in a match is not that helpful. If a really good team has an alliance with two essentially non-functional robots in 2 or 3 of your matches - the numbers look terrible for that team. A case in point, 234 (Cyberblue) at the DC regional - if you look at the OPR numbers for them, they are in the middle of the pack. Our scouting team did NOT look at the alliance data this year. I had scouts answer the following questions:
1) How many MR did they place in a trailer (including their own in the event they were trying to avoid the penalty)
2) How many MR were in their trailer (by either the opposing alliance, or the HP)
3) How many EC did they deliver to be exchanged with a SC
I then calculated the OPR and DPR on those stats. In my example above, regarding 234 - they jumped from middle of the pack, to essentially the same level as 45, which is where they should have been ranked.
Any one else looking at TEAM OPR and DPR, and if so, how are you doing it, and what were your results like.
By the way, when I looked at the predictive nature of the values we calculated, we were right in our predictions more than 85% of the time. Only something like "forgetting to turn on the radio" or some such issue would throw off the results.
Best regards,
Steve
I have a general question that I would love for you all to consider. I am a firm believer in the OPR/DPR concept, and included it in our team's scouting application. But what I found was that in this game, ALLIANCE data in a match is not that helpful.
Any team that scouts entirely off of the output of this program (or any OPR program) is doing something wrong. Personally, I use it to get a quick idea of which robots to watch if I'm watching a webcast and haven't been following an entire regional. I completely second your recommendation of in-person scouting. Just like the FRC rankings system often fails an otherwise good team, the OPR ranking algorithm can screw up too.
If a really good team has an alliance with two essentially non-functional robots in 2 or 3 of your matches - the numbers look terrible for that team.
That's not necessarily true. If your two non-functional alliance partners are consistently non-functional, then your OPR should be unaffected. The main thing that throws off OPR is inconsistency. If an very good team has a battery fall out during a match, then it affects their alliance partners' OPR scores quite badly, because it 'looks' to the algorithm like their presence resulted in a massive reduction in their alliance's score.
Killraine
06-03-2009, 11:27
If only we could have some kind of "fluke" marker that we could place on team's whenever they behave inconsitently. I don't know your algorithm, but maybe it could treat a fluke robot performance as a no-name default robot that performs at the low level it does.
Surprisingly, I got alot of the backbone of the porting done last night. Luckily Jama makes a Java library as well. I may have a first pass at it completed by the end of the weekend. All I have to do is figure out this silly URL issue...
Surprisingly, I got alot of the backbone of the porting done last night. Luckily Jama makes a Java library as well. I may have a first pass at it completed by the end of the weekend. All I have to do is figure out this silly URL issue...
Oh, how I understand you! ;)
I'm working on a MATLAB version since last night and the math is all working IF you input the data (copy from FIRST to Excel then to MATLAB, really easy but cumbersome). Coding to parse the results from FIRST's website is going to take the full weekend, I believe.
Oh, how I understand you! ;)
I'm working on a MATLAB version since last night and the math is all working IF you input the data (copy from FIRST to Excel then to MATLAB, really easy but cumbersome). Coding to parse the results from FIRST's website is going to take the full weekend, I believe.
That depends on how flexible you want your parsing to be. I spent 2 hours trying to write an uber-XML parser with MSXML, then I gave up and spent about half an hour hacking together the one that I use now. All of FIRST's score pages from mid-2008 onwards are generated from the same application, and have identical formatting. I just read one line at a time and looked for the text that always preceded a team score. It works well enough for me, though it'll need an update if they ever change their match results page style.
Better idea, if you're not already committed to scraping from FIRST: scrape from TBA - they use the same style for all events, all years. Your program would be able to run OPRs all the way back to 2006.
Edit: Speaking of parsing, I notice that the prediction code doesn't work with a regional underway. I'll have to look at that tonight (I wasn't able to properly test it since all regionals were done when I initially wrote that feature).
That depends on how flexible you want your parsing to be. I spent 2 hours trying to write an uber-XML parser with MSXML, then I gave up and spent about half an hour hacking together the one that I use now. All of FIRST's score pages from mid-2008 onwards are generated from the same application, and have identical formatting. I just read one line at a time and looked for the text that always preceded a team score. It works well enough for me, though it'll need an update if they ever change their match results page style.
Better idea, if you're not already committed to scraping from FIRST: scrape from TBA - they use the same style for all events, all years. Your program would be able to run OPRs all the way back to 2006.
Edit: Speaking of parsing, I notice that the prediction code doesn't work with a regional underway. I'll have to look at that tonight (I wasn't able to properly test it since all regionals were done when I initially wrote that feature).
You, sir, are wise. ;)
As a professor used to say, there are always at least two ways to solve a problem. More often than not, the easy ways are not correct and the correct ways are not easy. We chose easy, so eventually it will come and bite us.
I used TBA data so you can get stats for events from 2006 to 2009. It's nearly impossible to obtain a 2007 event matrix that's not ill-conditioned - I believe it's due to FIRST's awful alliance sorting algorithms from that year, but have not looked into in detail. In short, OPR for 2007 will not work. If someone is feeling reminiscent this days, please take a look.
Here's the code, just run OPR from MATLAB's command window and ask for what you want. The script returns three arrays containing ranked OPR, DPR (or whatever you might call it) and +/- stats for that particular event.
I have tested it with several events, but bugs may arise. Please test and let me know.
You, sir, are wise. ;)
As a professor used to say, there are always at least two ways to solve a problem. More often than not, the easy ways are not correct and the correct ways are not easy. We chose easy, so eventually it will come and bite us.
I used TBA data so you can get stats for events from 2006 to 2009. It's nearly impossible to obtain a 2007 event matrix that's not ill-conditioned - I believe it's due to FIRST's awful alliance sorting algorithms from that year, but have not looked into in detail. In short, OPR for 2007 will not work. If someone is feeling reminiscent this days, please take a look.
Here's the code, just run OPR from MATLAB's command window and ask for what you want. The script returns three arrays containing ranked OPR, DPR (or whatever you might call it) and +/- stats for that particular event.
I have tested it with several events, but bugs may arise. Please test and let me know.
It is probably a combination of the terrible alliance picking, and that 2007 had non-linear scoring. A robot that always scored 3 ringers in 2007 might contribute 6 points in one match (by scoring 2 points, 3 times), or it might contribute 192 points in another, by extending a row of 5 into a row of 8.
In 2006, 2008, and 2009, a robot that did <game action> 5 times in each match generally generated the same number of points.
It doesn't seem to matter how I redo the matrices, nor whether I use LU or QR decomposition, I keep getting these numbers and they don't match up with the OPRNet.exe data:
My Output
Washington DC Regional
01. Team 2199 W:5 L:2 OPR:25.39 DPR:15.13 PMR:10.26
02. Team 2377 W:6 L:1 OPR:22.73 DPR:7.89 PMR:14.83
03. Team 0045 W:7 L:0 OPR:21.54 DPR:5.66 PMR:15.88
04. Team 0234 W:6 L:1 OPR:19.74 DPR:13.76 PMR:5.98
05. Team 0365 W:4 L:3 OPR:19.58 DPR:11.78 PMR:7.80
OPRNet.exe Output
Solve complete.
Pos Team OPR SAA PM
1 2199 44.74 26.5 18.24
2 365 35.45 13.81 21.63
3 45 34.37 -0.7267 35.09
4 2377 32.05 7.856 24.19
5 234 31.55 23.53 8.021
On another interesting note, if you take the sum of the entire 'PMR' column for all teams within a regional on either, you get 0.
WARNING: Attachment has some gui bugs. It also creates temp files for every regional/year, so I'd recommend putting it in a folder on its own. It also requires Java 1.6 since it does some neat enumeration and comparator stuff. To run it, just double-click it.
It doesn't seem to matter how I redo the matrices, nor whether I use LU or QR decomposition, I keep getting these numbers and they don't match up with the OPRNet.exe data:
Can you post your M matrix for the DC regional for us to compare?
M:
14 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 1 1 0 0 1 0 1 0 0 0 0 1 0 1 0 0 0 0 0
0 14 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 0 0 1 1 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0
0 0 14 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 1 1 1 0 1 0 0
0 0 0 14 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 1
0 0 0 0 14 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0
0 0 0 1 0 14 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 1
0 0 0 1 0 1 14 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1
1 0 0 0 1 0 0 14 0 1 0 1 0 0 1 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 1 0 0 1 0 0 0
0 1 0 0 1 0 0 0 14 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 1 0 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
0 0 1 0 0 0 0 1 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 1 0 0 1 1 0 1
0 0 0 0 0 0 0 0 0 0 14 0 1 0 1 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 1 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0
0 0 1 0 0 0 1 1 0 0 0 14 0 0 1 1 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 1 0 14 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 1 1 0 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0
1 1 0 1 0 0 0 0 0 0 0 0 1 14 0 0 0 1 1 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0
0 0 0 0 0 0 0 1 0 0 1 1 0 0 14 1 1 0 1 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
1 0 0 0 0 0 0 0 1 0 0 1 0 0 1 14 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0
1 1 0 0 0 0 1 1 0 0 0 0 0 0 1 0 14 0 0 0 0 1 0 1 0 1 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 14 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0 1 0 0 0 1
0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 14 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 1 0 1 0 0 0 0 1 0 0 0 0
0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 14 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0 1 1 0 0 0 0
0 0 0 0 1 1 1 0 0 0 1 0 1 1 1 0 0 1 0 0 14 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0
0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 14 0 0 0 0 0 1 0 0 1 1 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0
0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 1 0 1 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 1 0 0 0 0 14 1 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0
0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 14 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1
0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 14 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 1 1 0
0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1 0 14 0 0 1 0 0 0 1 1 1 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1
0 0 0 0 1 0 0 0 1 0 0 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 14 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0
0 0 1 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 14 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 0 0 0 1 1 0 0 0 0 0
0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 1 0 0 14 0 0 0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 1 1
0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1 0 0 0 0 14 0 1 1 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0
0 1 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0
0 0 0 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 14 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 0 0 1 0 0 0
0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 1 0 0 14 0 0 0 0 0 0 0 0 0 1 1 1 0 0 1 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0
0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 1 0 0 0 14 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 0 0 0
0 1 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 14 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0
0 0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 14 0 0 0 0 0 0 0 1 1 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0
1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 1 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 1 1 0 0 0 0 0 1
0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 14 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 1 0 0 1 1 0 0 0 0
1 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 1 0 0 1 1 1 0 0 0 0 0 0 0 14 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0
0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 1 1 0 1 0 0 0 1 0 1 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 14 0 1 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0
0 0 1 0 0 0 1 0 1 0 1 0 1 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 16 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1
1 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 14 1 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0
0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 1 1 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 1 14 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 1
1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 1 0 0 0 0 0 0 1 1 1 0 0 1 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 1 0 14 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 1 1 0 0 14 1 0 1 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0
1 1 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 14 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0
0 0 0 1 1 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 1 14 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0
0 0 1 0 0 0 0 0 0 1 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 14 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0
1 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 0 1 0 0 0 0 0 14 0 0 0 0 0 0 1 0 0 0 0 1 0 0
0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 1 0 0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 14 0 0 0 0 0 0 0 1 0 0 0 0 0
1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 0 1 0 0 0 0 1 0 0 1 1 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 14 0 1 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 1 0 1 1 0 1 1 0 0 1 0
0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 1 1 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 1 14 0 0 0 0 0 0 0 0 1 1
0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 1 1 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 1 0 0 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 1 0 1 0 1 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 14 0 1 0 1 0 0 0 0
1 0 0 0 0 0 1 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 14 0 0 0 0 1 1 0
0 0 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 14 1 1 0 0 0 1
1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 1 14 0 0 0 0 0
0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 14 0 1 0 0
0 0 0 1 0 1 0 1 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0
0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1 1 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 14 0 0
0 1 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 1 1 0 0 0 0 1 1 0 0 1 0 0 0 0 0 14 0
0 0 0 1 0 1 1 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 14
Corresponding SFor:
310
358
388
328
409
365
541
336
345
326
410
368
348
242
335
300
481
384
312
308
361
369
322
395
321
302
387
317
317
279
327
365
406
396
228
342
360
260
365
359
319
370
589
346
438
336
312
228
312
297
454
300
273
322
414
270
331
409
356
292
412
445
324
402
328
Corresponding team/row map
1915
272
2068
1370
7
401
2199
1900
2729
1111
1731
2819
1522
1885
1872
1123
45
1629
1748
53
768
1279
2964
176
2962
2963
181
2961
538
2912
611
2913
2914
614
1849
1699
339
615
623
346
620
3046
2377
1719
1712
1727
1418
2121
449
2537
234
587
709
2421
118
357
116
597
836
2900
1446
365
2911
122
1793
M:
14 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 1 1 0 0 1 0 1 0 0 0 0 1 0 1 0 0 0 0 0
0 14 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 0 0 1 1 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0
0 0 14 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 1 1 1 0 1 0 0
0 0 0 14 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 1
0 0 0 0 14 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0
0 0 0 1 0 14 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 1
0 0 0 1 0 1 14 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1
1 0 0 0 1 0 0 14 0 1 0 1 0 0 1 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 1 0 0 1 0 0 0
0 1 0 0 1 0 0 0 14 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 1 0 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
0 0 1 0 0 0 0 1 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 1 0 0 1 1 0 1
0 0 0 0 0 0 0 0 0 0 14 0 1 0 1 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 1 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0
0 0 1 0 0 0 1 1 0 0 0 14 0 0 1 1 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 1 0 14 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 1 1 0 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0
1 1 0 1 0 0 0 0 0 0 0 0 1 14 0 0 0 1 1 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0
0 0 0 0 0 0 0 1 0 0 1 1 0 0 14 1 1 0 1 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
1 0 0 0 0 0 0 0 1 0 0 1 0 0 1 14 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0
1 1 0 0 0 0 1 1 0 0 0 0 0 0 1 0 14 0 0 0 0 1 0 1 0 1 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 14 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0 1 0 0 0 1
0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 14 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 1 0 1 0 0 0 0 1 0 0 0 0
0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 14 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0 1 1 0 0 0 0
0 0 0 0 1 1 1 0 0 0 1 0 1 1 1 0 0 1 0 0 14 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0
0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 14 0 0 0 0 0 1 0 0 1 1 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0
0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 1 0 1 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 1 0 0 0 0 14 1 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0
0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 14 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1
0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 14 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 1 1 0
0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1 0 14 0 0 1 0 0 0 1 1 1 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1
0 0 0 0 1 0 0 0 1 0 0 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 14 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0
0 0 1 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 14 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 0 0 0 1 1 0 0 0 0 0
0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 1 0 0 14 0 0 0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 1 1
0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1 0 0 0 0 14 0 1 1 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0
0 1 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0
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OK, the only difference is in the main diagonal of the M matrix. S results are correct. You're counting each team twice in the "how much matches played with itself". Dividing the main diagonal by 2 will do the trick, though fixing the logic might be wiser (and just as easy).
I also find it easier to work with the team list sorted from low to high. For instance, with your numbers, I had to sort, transpose, and sort again to match mine.
Let us know when it's fixed! :D
I also find it easier to work with the team list sorted from low to high. For instance, with your numbers, I had to sort, transpose, and sort again to match mine.
The user can sort by 3 statistics, and in the future possibly more. There are additional gui aspects I'm working on, which is why if you run the gui you see a tabbed panel at the top. I figure sorting doesn't matter during calculation due to the fact that it will all be sorted a billion ways after it's calculated anyways ;)
Thanks for the find, it's fixed!
Here's the top 25 from Week 1 & 2:
01. Team 0071 W:7 L:0 OPR:63.55 DPR:13.69 PMR:49.86
02. Team 0968 W:9 L:0 OPR:52.85 DPR:12.82 PMR:40.03
03. Team 1625 W:6 L:2 OPR:48.82 DPR:13.99 PMR:34.83
04. Team 0694 W:5 L:1 OPR:48.05 DPR:17.20 PMR:30.85
05. Team 2199 W:5 L:2 OPR:44.74 DPR:26.50 PMR:18.24
06. Team 1622 W:8 L:2 OPR:44.21 DPR:10.39 PMR:33.82
07. Team 0188 W:6 L:2 OPR:43.56 DPR:23.64 PMR:19.92
08. Team 1114 W:7 L:1 OPR:43.18 DPR:11.25 PMR:31.93
09. Team 2753 W:7 L:0 OPR:43.03 DPR:8.07 PMR:34.96
10. Team 1155 W:6 L:1 OPR:41.84 DPR:7.39 PMR:34.45
11. Team 1923 W:4 L:3 OPR:41.15 DPR:16.71 PMR:24.44
12. Team 0111 W:6 L:2 OPR:41.13 DPR:15.06 PMR:26.07
13. Team 0245 W:10 L:2 OPR:40.52 DPR:3.37 PMR:37.15
14. Team 1806 W:7 L:0 OPR:39.87 DPR:9.12 PMR:30.75
15. Team 0040 W:7 L:2 OPR:39.74 DPR:11.28 PMR:28.46
16. Team 1507 W:6 L:0 OPR:39.63 DPR:17.30 PMR:22.33
17. Team 1823 W:6 L:1 OPR:38.78 DPR:5.14 PMR:33.64
18. Team 1218 W:6 L:1 OPR:38.57 DPR:8.18 PMR:30.40
19. Team 0121 W:7 L:1 OPR:38.44 DPR:2.03 PMR:36.41
20. Team 0025 W:5 L:2 OPR:37.95 DPR:7.24 PMR:30.70
21. Team 0395 W:4 L:2 OPR:37.21 DPR:16.10 PMR:21.11
22. Team 0085 W:9 L:3 OPR:37.08 DPR:6.80 PMR:30.28
23. Team 0835 W:5 L:2 OPR:36.79 DPR:5.48 PMR:31.31
24. Team 0175 W:6 L:2 OPR:36.37 DPR:22.71 PMR:13.67
25. Team 0056 W:6 L:1 OPR:36.36 DPR:14.28 PMR:22.08
Double click the uncompressed jar for it to run. You need Java jre 1.6 (http://java.sun.com/javase/downloads/index.jsp) (first download link) for it to run.
There's still a couple of bugs, but I'm working on it.
=== updates ===
Now attempts to parse data from multiple sources until it gets valid data, in this order: 1.) local html file, 2.) usfirst.org, 3.) tba.net Buckeye data isn't up on USFIRST or TBA, sorry
You now have the options to show only the regionals up to a given week
You can now rank all teams against each other for the full season (will be fully tested in week 3 when several teams do their second regional)
More to come; most of the methods and classes are setup for easy code reuse.
Hmm...not many of the top 25 listed are shooters?
Hmm...not many of the top 25 listed are shooters?
Being that these numbers are all based on qualification rounds only, I think even more noticable is that there aren't many of the top 25 who have won a regional. Sure, there are some noticable names, but out of the top 5 only 1625 even made it to the finals of a regional.
This just goes to show you that top OPR isn't everything when it comes to winning the big matches (though it definitely helps).
And when running some extra stats, I just noticed that 2753 has completed 2 regionals but only has OPR data for 1 regional... hmm... that's the first thing to fix! The second thing is to refactor the gui and omi into two separate threadpools so it doesn't lock up when you push the 'print' button.
Vikesrock
10-03-2009, 13:14
Being that these numbers are all based on qualification rounds only, I think even more noticable is that there aren't many of the top 25 who have won a regional. Sure, there are some noticable names, but out of the top 5 only 1625 even made it to the finals of a regional.
This just goes to show you that top OPR isn't everything when it comes to winning the big matches (though it definitely helps).
Is the PMR column +/- or CCWM? The program calls it CCWM to sort by it, but the numbers appear to simply be OPR-DPR.
Regardless of what it is sorting by this category results in 3 of the top 5 being regional winners and 5 of the top 7.
Here are the top 25 by PMR:
01. Team 0071 W:7 L:0 OPR:63.55 DPR:13.69 PMR:49.86
02. Team 0968 W:9 L:0 OPR:52.85 DPR:12.82 PMR:40.03
03. Team 0245 W:10 L:2 OPR:40.52 DPR:3.37 PMR:37.15
04. Team 0121 W:7 L:1 OPR:38.44 DPR:2.03 PMR:36.41
05. Team 0045 W:7 L:0 OPR:34.37 DPR:-0.73 PMR:35.09
06. Team 2753 W:7 L:0 OPR:43.03 DPR:8.07 PMR:34.96
07. Team 1625 W:6 L:2 OPR:48.82 DPR:13.99 PMR:34.83
08. Team 1155 W:6 L:1 OPR:41.84 DPR:7.39 PMR:34.45
09. Team 1939 W:6 L:1 OPR:36.11 DPR:1.92 PMR:34.19
10. Team 1622 W:8 L:2 OPR:44.21 DPR:10.39 PMR:33.82
11. Team 1823 W:6 L:1 OPR:38.78 DPR:5.14 PMR:33.64
12. Team 1114 W:7 L:1 OPR:43.18 DPR:11.25 PMR:31.93
13. Team 0835 W:5 L:2 OPR:36.79 DPR:5.48 PMR:31.31
14. Team 0694 W:5 L:1 OPR:48.05 DPR:17.20 PMR:30.85
15. Team 1806 W:7 L:0 OPR:39.87 DPR:9.12 PMR:30.75
16. Team 0025 W:5 L:2 OPR:37.95 DPR:7.24 PMR:30.70
17. Team 0155 W:6 L:1 OPR:34.30 DPR:3.86 PMR:30.44
18. Team 1218 W:6 L:1 OPR:38.57 DPR:8.18 PMR:30.40
19. Team 0085 W:9 L:3 OPR:37.08 DPR:6.80 PMR:30.28
20. Team 0040 W:7 L:2 OPR:39.74 DPR:11.28 PMR:28.46
21. Team 1126 W:5 L:3 OPR:29.37 DPR:1.21 PMR:28.16
22. Team 0217 W:7 L:2 OPR:31.74 DPR:3.85 PMR:27.89
23. Team 2811 W:4 L:3 OPR:33.03 DPR:5.58 PMR:27.46
24. Team 0102 W:4 L:2 OPR:32.59 DPR:5.26 PMR:27.33
25. Team 0020 W:7 L:1 OPR:34.83 DPR:7.52 PMR:27.31
Jared Russell
10-03-2009, 13:22
The lack of correlation between OPR, DPR, and winning a regional is at first surprising. But if you step back and look at how several regionals have been won so far this year, teamwork and strategy seem to be the common theme.
I believe that in Lunacy, the strength of an alliance is not defined strictly by the sum of its parts.
The lack of correlation between OPR, DPR, and winning a regional is at first surprising. But if you step back and look at how several regionals have been won so far this year, teamwork and strategy seem to be the common theme.
I believe that in Lunacy, the strength of an alliance is not defined strictly by the sum of its parts.
The most interesting correlation I've found is that the robots that get to go into eliminations correspond very strongly with the PM rating. At FLR, all but one of the top 20 robots ranked by PMR were either captains or were selected to go into eliminations. The correlation is less strong with OPR.
Is the PMR column +/- or CCWM? The program calls it CCWM to sort by it, but the numbers appear to simply be OPR-DPR.
Regardless of what it is sorting by this category results in 3 of the top 5 being regional winners and 5 of the top 7.
I found that it doesn't matter if you solve the matrix based upon win margin or if you just subtract DPR from OPR, the number is still the same. The CCWM is based upon the white paper that I saw Ed Law put out at the end of last year, which is what I originially tried to implement in the matrices. When I saw that the numbers were the same, I simplified all of the code and didn't rename the stuff -- oversight on my part.
CCWM = Caclulated Contribution to Winning Margin
aka PlusMinus Rating, i.e. different calculations to arrive at the same solution.
I think you want a high OPR for a first round pick, then a high CCWM for the second round... that is, if you want a high-octane, excitingly offensive alliance (which is my preference).
I found that it doesn't matter if you solve the matrix based upon win margin or if you just subtract DPR from OPR, the number is still the same. The CCWM is based upon the white paper that I saw Ed Law put out at the end of last year, which is what I originially tried to implement in the matrices. When I saw that the numbers were the same, I simplified all of the code and didn't rename the stuff -- oversight on my part.
CCWM = Caclulated Contribution to Winning Margin
aka PlusMinus Rating, i.e. different calculations to arrive at the same solution.
I think you want a high OPR for a first round pick, then a high CCWM for the second round... that is, if you want a high-octane, excitingly offensive alliance (which is my preference).
I just had an idea, which might resolve to CCWM/PMR, but I don't think it will.
It ends up with a 2N x 2N matrix (for a regional with N teams)
sum[team's scores] = weighted sum of OPRs of alliance members minus weighted sum of DPRs of opponents.
At first I thought that it would be unsolvable (each equation has 6 unknowns, and you'd end up with 2N unknowns and only N equations), until today I had the fairly-obvious brainwave that each match would give you two equations (one OPRred - DPRblue = scorered for red, one OPRblue - DPRred = scoreblue for blue). This approach seems like it would be more predictive of robot performance than simply doing OPR and DPR separately*. I'm going to try to implement it tonight, but if someone wants to try it themselves and report back, that'd be great.
*The problem with the current approach to OPR and DPR, especially in a game like lunacy, is that they assume that a alliance's score comes ENTIRELY from its teams' offensive powers, or ENTIRELY from its opponent's lack of mobility. This proposed new equation seems like it would balance the two, and hopefully give more accurate results.
I found that it doesn't matter if you solve the matrix based upon win margin or if you just subtract DPR from OPR, the number is still the same. The CCWM is based upon the white paper that I saw Ed Law put out at the end of last year, which is what I originially tried to implement in the matrices. When I saw that the numbers were the same, I simplified all of the code and didn't rename the stuff -- oversight on my part.
CCWM = Caclulated Contribution to Winning Margin
aka PlusMinus Rating, i.e. different calculations to arrive at the same solution.
I think you want a high OPR for a first round pick, then a high CCWM for the second round... that is, if you want a high-octane, excitingly offensive alliance (which is my preference).
Hi Jesse,
If we look at the system of equations to calculate OPR, it is
A * OPR = B(opr)
and the system of equations to calculate DPR is
A * DPR = B(dpr)
The way I solve for CCWM is
A * CCWM = B(wm) = B(opr)-B(dpr)
A is the same matrix for all 3 systems of equations. I put the winning margin into vector B which is the same as vector B for OPR minus vector B for DPR. Hence the results of CCWM and +/- (PMR) should be identical. Thanks for confirming it Jesse. I never tried it myself.
Regards,
Ed Law
The most interesting correlation I've found is that the robots that get to go into eliminations correspond very strongly with the PM rating. At FLR, all but one of the top 20 robots ranked by PMR were either captains or were selected to go into eliminations. The correlation is less strong with OPR.
Hi Bongle,
I referenced your work in my white paper. I didn't realize you are mentoring Team 2702 now. I still associated you with Team 1281 in my presentation. I will update it. I really like your insight/explanation how to interpret these rating numbers.
I want to discuss with you about correlation between OPR and CCWM/PMR. I think we both agreed that it changes from year to year depending on the game. One way, as you suggest in your post, is to see whether the teams that were alliance captain or got picked and went to the elimination round have higher OPR rankings or higher CCWM/PMR rankings. This will tell us whether teams value pure offensive power or contribution to winning margin when they select teams. Perhaps we should exclude the alliance captains when we do this comparison.
Another way to look at correlation is how "predictive" the two different ratings are to outcome of elimination round matches. I did a study of the prediction of match results using OPR and CCWM. Through the first two weeks including those events that have complete data published, in the elimination round, the prediction using CCWM is 59.5% and using OPR is slightly better at 63.6%. One reason the correlation is not that good is because there were a lot of close matches that could have gone either way.
We should be careful not to draw conclusions from just one regional. Each of the two ratings correlate better for some regionals but not for others.
Regards,
Ed Law
At first I thought that it would be unsolvable (each equation has 6 unknowns, and you'd end up with 2N unknowns and only N equations), until today I had the fairly-obvious brainwave that each match would give you two equations (one OPRred - DPRblue = scorered for red, one OPRblue - DPRred = scoreblue for blue). This approach seems like it would be more predictive of robot performance than simply doing OPR and DPR separately*. I'm going to try to implement it tonight, but if someone wants to try it themselves and report back, that'd be great
You would want to have (blueScore = blueOPR + redDPR) and vice versa. Remember, you having a low DPR is better for you, hence you want your opponents to have a high DPR. If you subtract the opponent's DPR then you're lowering your own score just because the opponents are easier to score on ... which doesn't make sense when the opponent's DPR is positive (which is pretty bad).
Some simulation data to come tonight; I have an idea for a quick and dirty Match Prediction method.
<edit> Quick match prediction using the formula above for the DC Quarterfinals:
blueScore = blueOPR - redDPR:
Teams: (RED) 234, 45, & 620 vs. (BLUE) 1111, 122, 768
Predicted Scores: Red = 43, Blue = 6
Actual Scores: Red = 126, Blue = 100
blueScore = blueOPR + redDPR:
Teams: (RED) 234, 45, & 620 vs. (BLUE) 1111, 122, 768
Predicted Scores: RED=101 BLUE=80
Actual Scores: Red = 126, Blue = 100
Note that the prediction for their second match was identical even when the new match data was added, so predicting the outcome of the second QF match when the scores are that close is nearly impossible. Predictions also don't take into account adjustments for strategy, which is probably why it's best to leave the actual statistics for Qualification Matches only.
You would want to have (blueScore = blueOPR + redDPR) and vice versa. Remember, you having a low DPR is better for you, hence you want your opponents to have a high DPR. If you subtract the opponent's DPR then you're lowering your own score just because the opponents are easier to score on ... which doesn't make sense when the opponent's DPR is positive (which is pretty bad).
Some simulation data to come tonight; I have an idea for a quick and dirty Match Prediction method.
<edit> Quick match prediction using the formula above for the DC Quarterfinals:
blueScore = blueOPR - redDPR:
Teams: (RED) 234, 45, & 620 vs. (BLUE) 1111, 122, 768
Predicted Scores: Red = 43, Blue = 6
Actual Scores: Red = 126, Blue = 100
blueScore = blueOPR + redDPR:
Teams: (RED) 234, 45, & 620 vs. (BLUE) 1111, 122, 768
Predicted Scores: RED=101 BLUE=80
Actual Scores: Red = 126, Blue = 100
Note that the prediction for their second match was identical even when the new match data was added, so predicting the outcome of the second QF match when the scores are that close is nearly impossible. Predictions also don't take into account adjustments for strategy, which is probably why it's best to leave the actual statistics for Qualification Matches only.
Hi Jesse,
I think the general consensus in the CD community agrees that OPR should be calculated with qualifying matches only. The extra matches by some teams who made it to elimination round will bias the results if they are used.
Ed
Hey y'all...
Can anyone run the program for the NYC regional and post the results?
I reformatted and haven't gotten a chance to install VMWare Fusion on my mac again.
Thanks a bunch!
Dandon
Vikesrock
10-03-2009, 22:50
Here's the NYC results sorted by +/-
New York City
New York City data retrieved from local HTML file
01. Team 1155 W:6 L:1 OPR:40.13 DPR:7.71 PMR:32.43
02. Team 0694 W:5 L:1 OPR:48.45 DPR:16.43 PMR:32.02
03. Team 2753 W:5 L:2 OPR:40.41 DPR:10.78 PMR:29.63
04. Team 2344 W:6 L:1 OPR:37.71 DPR:11.32 PMR:26.39
05. Team 0354 W:5 L:2 OPR:30.65 DPR:5.93 PMR:24.72
06. Team 0371 W:5 L:2 OPR:24.19 DPR:0.05 PMR:24.14
07. Team 0271 W:6 L:1 OPR:33.62 DPR:10.62 PMR:23.00
08. Team 0056 W:6 L:1 OPR:34.82 DPR:13.50 PMR:21.32
09. Team 1396 W:5 L:2 OPR:16.90 DPR:-1.69 PMR:18.59
10. Team 3059 W:4 L:3 OPR:16.46 DPR:-0.88 PMR:17.34
11. Team 0395 W:4 L:2 OPR:34.57 DPR:17.66 PMR:16.90
12. Team 1302 W:5 L:2 OPR:19.31 DPR:3.41 PMR:15.90
13. Team 0335 W:5 L:2 OPR:19.48 DPR:3.61 PMR:15.87
14. Team 0555 W:4 L:3 OPR:31.73 DPR:16.13 PMR:15.60
15. Team 0743 W:3 L:4 OPR:28.15 DPR:13.62 PMR:14.53
16. Team 2265 W:3 L:4 OPR:13.59 DPR:0.03 PMR:13.56
17. Team 2933 W:4 L:3 OPR:27.06 DPR:14.36 PMR:12.70
18. Team 1807 W:6 L:1 OPR:23.10 DPR:10.70 PMR:12.40
19. Team 0358 W:2 L:5 OPR:9.30 DPR:-3.01 PMR:12.31
20. Team 0237 W:5 L:2 OPR:27.48 DPR:16.54 PMR:10.93
21. Team 0270 W:4 L:3 OPR:16.16 DPR:6.91 PMR:9.25
22. Team 0806 W:5 L:2 OPR:16.18 DPR:7.07 PMR:9.12
23. Team 0041 W:3 L:4 OPR:29.08 DPR:20.49 PMR:8.58
24. Team 1660 W:6 L:1 OPR:25.19 DPR:16.74 PMR:8.45
25. Team 3017 W:4 L:3 OPR:9.20 DPR:1.35 PMR:7.85
26. Team 1796 W:4 L:3 OPR:24.28 DPR:17.44 PMR:6.84
27. Team 1257 W:3 L:4 OPR:18.69 DPR:12.12 PMR:6.57
28. Team 1211 W:5 L:2 OPR:14.03 DPR:7.46 PMR:6.57
29. Team 2681 W:5 L:2 OPR:14.22 DPR:8.45 PMR:5.77
30. Team 0375 W:7 L:0 OPR:28.39 DPR:22.82 PMR:5.57
31. Team 1881 W:3 L:4 OPR:14.22 DPR:10.59 PMR:3.62
32. Team 0527 W:4 L:3 OPR:16.86 DPR:13.26 PMR:3.60
33. Team 1237 W:2 L:4 OPR:12.71 DPR:9.29 PMR:3.42
34. Team 1156 W:3 L:4 OPR:12.07 DPR:9.84 PMR:2.23
35. Team 2285 W:3 L:3 OPR:23.47 DPR:21.81 PMR:1.66
36. Team 2601 W:3 L:4 OPR:18.98 DPR:17.41 PMR:1.57
37. Team 2070 W:3 L:4 OPR:7.30 DPR:6.57 PMR:0.73
38. Team 0640 W:2 L:5 OPR:8.66 DPR:11.47 PMR:-2.81
39. Team 1230 W:5 L:2 OPR:11.28 DPR:15.17 PMR:-3.89
40. Team 0369 W:5 L:2 OPR:9.11 DPR:13.57 PMR:-4.45
41. Team 2579 W:3 L:4 OPR:5.34 DPR:12.70 PMR:-7.36
42. Team 1862 W:2 L:4 OPR:-0.63 DPR:6.93 PMR:-7.56
43. Team 0333 W:2 L:5 OPR:7.73 DPR:16.31 PMR:-8.58
44. Team 1563 W:1 L:6 OPR:22.48 DPR:31.97 PMR:-9.50
45. Team 2577 W:3 L:4 OPR:20.45 DPR:30.12 PMR:-9.67
46. Team 3111 W:2 L:4 OPR:12.75 DPR:22.44 PMR:-9.69
47. Team 1989 W:3 L:4 OPR:2.76 DPR:13.64 PMR:-10.88
48. Team 1600 W:3 L:4 OPR:11.61 DPR:23.95 PMR:-12.34
49. Team 1520 W:1 L:6 OPR:2.07 DPR:14.43 PMR:-12.37
50. Team 2205 W:2 L:5 OPR:11.63 DPR:24.03 PMR:-12.40
51. Team 0329 W:4 L:3 OPR:-3.86 DPR:9.24 PMR:-13.10
52. Team 2573 W:2 L:5 OPR:6.82 DPR:19.95 PMR:-13.13
53. Team 1880 W:0 L:7 OPR:3.65 DPR:19.53 PMR:-15.88
54. Team 0263 W:2 L:5 OPR:20.96 DPR:37.03 PMR:-16.07
55. Team 3053 W:2 L:5 OPR:9.44 DPR:26.20 PMR:-16.76
56. Team 1340 W:1 L:6 OPR:10.14 DPR:28.07 PMR:-17.93
57. Team 2554 W:3 L:4 OPR:4.92 DPR:24.93 PMR:-20.00
58. Team 0759 W:4 L:3 OPR:2.52 DPR:22.78 PMR:-20.26
59. Team 0380 W:2 L:5 OPR:0.99 DPR:21.58 PMR:-20.59
60. Team 0421 W:5 L:2 OPR:1.94 DPR:25.20 PMR:-23.26
61. Team 3004 W:1 L:6 OPR:6.56 DPR:30.20 PMR:-23.65
62. Team 1635 W:2 L:5 OPR:8.29 DPR:35.37 PMR:-27.08
63. Team 2895 W:3 L:4 OPR:2.33 DPR:31.59 PMR:-29.26
64. Team 3112 W:1 L:6 OPR:0.70 DPR:33.29 PMR:-32.59
65. Team 0334 W:1 L:6 OPR:-6.96 DPR:32.80 PMR:-39.76
66. Team 1698 W:0 L:7 OPR:-1.64 DPR:39.21 PMR:-40.86
I just had an idea, which might resolve to CCWM/PMR, but I don't think it will.
It ends up with a 2N x 2N matrix (for a regional with N teams)
sum[team's scores] = weighted sum of OPRs of alliance members minus weighted sum of DPRs of opponents.
At first I thought that it would be unsolvable (each equation has 6 unknowns, and you'd end up with 2N unknowns and only N equations), until today I had the fairly-obvious brainwave that each match would give you two equations (one OPRred - DPRblue = scorered for red, one OPRblue - DPRred = scoreblue for blue). This approach seems like it would be more predictive of robot performance than simply doing OPR and DPR separately*. I'm going to try to implement it tonight, but if someone wants to try it themselves and report back, that'd be great.
*The problem with the current approach to OPR and DPR, especially in a game like lunacy, is that they assume that a alliance's score comes ENTIRELY from its teams' offensive powers, or ENTIRELY from its opponent's lack of mobility. This proposed new equation seems like it would balance the two, and hopefully give more accurate results.
I gave it a shot. I'm not sure I implemented it correctly, but matrix A (Ax = b) always comes up with a large conditioning number - nearly singular, which means that small changes in b, or the matches results, would result in huge shifts in OPR/DPR for teams.
Anyway, here are my results for the NY Regional:
OPR:
1 1155 32.277
2 694 31.639
3 56 29.308
4 395 24.951
5 3059 23.105
6 2344 22.331
7 1600 22.075
8 743 21.927
9 2753 21.897
10 1257 18.944
11 1302 16.873
12 2554 16.547
13 335 13.228
14 237 11.405
15 1796 10.521
16 1660 10.011
17 1156 9.9718
18 3004 9.263
19 1881 9.2177
20 2681 8.3132
21 1862 7.8608
22 2265 6.898
23 375 6.6255
24 270 6.5267
25 1807 6.2078
26 1230 5.148
27 1396 4.5395
28 527 2.2106
29 371 1.8905
30 555 1.7473
31 41 0.72257
32 354 0.4532
33 271 -0.89414
34 2601 -1.8199
35 421 -2.437
36 369 -2.7544
37 2933 -4.2083
38 1340 -4.8236
39 1880 -5.2459
40 358 -5.4201
41 263 -6.2038
42 1563 -6.389
43 2285 -7.0976
44 3111 -8.2768
45 2577 -8.5896
46 806 -10.413
47 333 -10.934
48 3053 -11.506
49 640 -11.515
50 1520 -12.58
51 759 -12.655
52 2895 -13.538
53 1237 -13.924
54 1989 -14.043
55 2070 -14.541
56 3017 -14.922
57 2573 -15.48
58 1698 -16.094
59 2205 -16.962
60 2579 -17.403
61 1635 -17.776
62 1211 -18.224
63 380 -19.378
64 329 -20.404
65 3112 -22.538
66 334 -32.883
DPR:
(and note that now this is how many points on average your presence on an alliance takes points away from the opponent - a negative number indicates you're likely to increase your opponent's score)
1 1862 19.379
2 640 12.14
3 1155 10.869
4 1257 8.4759
5 1396 8.1218
6 1807 4.3868
7 56 1.2983
8 1600 0.60363
9 2070 0.29453
10 395 -0.96611
11 2601 -1.051
12 1237 -1.2811
13 270 -1.4666
14 371 -1.8914
15 1520 -1.9435
16 3059 -4.2095
17 1156 -4.3151
18 1302 -4.5479
19 2265 -5.5535
20 2554 -6.1296
21 358 -7.8337
22 380 -9.532
23 3004 -9.8214
24 237 -10.27
25 2344 -10.662
26 329 -13.279
27 2753 -13.602
28 1340 -14.952
29 2933 -15.027
30 1230 -15.604
31 1880 -15.936
32 3017 -16.672
33 333 -17.101
34 527 -17.291
35 2681 -17.463
36 1660 -17.746
37 1989 -18.37
38 421 -20.028
39 335 -20.761
40 1796 -21.286
41 1881 -21.618
42 743 -21.675
43 806 -22.481
44 2577 -23.904
45 759 -25.582
46 271 -25.939
47 3111 -26.223
48 1211 -26.5
49 694 -26.53
50 369 -26.648
51 263 -26.796
52 2895 -27.583
53 3053 -28.046
54 354 -28.105
55 41 -29.584
56 1563 -30.406
57 3112 -31.288
58 2573 -32.228
59 1698 -32.62
60 375 -32.85
61 334 -33.248
62 1635 -33.382
63 2205 -33.423
64 555 -36.653
65 2579 -37.541
66 2285 -45.508
+/-:
(just occurred me to calculate that, haven't given it much thought but I don't think it indicates anything)
1 694 58.169
2 743 43.602
3 375 39.475
4 2285 38.411
5 555 38.401
6 2753 35.499
7 335 33.989
8 2344 32.993
9 1796 31.807
10 1881 30.836
11 41 30.307
12 354 28.558
13 56 28.009
14 1660 27.757
15 3059 27.315
16 395 25.917
17 2681 25.776
18 271 25.045
19 1563 24.017
20 369 23.894
21 2554 22.677
22 237 21.675
23 1600 21.471
24 1302 21.421
25 1155 21.408
26 1230 20.752
27 263 20.592
28 2579 20.139
29 527 19.501
30 3004 19.084
31 3111 17.946
32 421 17.591
33 2573 16.748
34 3053 16.54
35 1698 16.526
36 2205 16.46
37 1635 15.606
38 2577 15.314
39 1156 14.287
40 2895 14.045
41 759 12.927
42 2265 12.451
43 806 12.069
44 2933 10.819
45 1880 10.69
46 1257 10.468
47 1340 10.128
48 3112 8.7504
49 1211 8.2755
50 270 7.9933
51 333 6.1671
52 1989 4.3263
53 371 3.7819
54 358 2.4136
55 1807 1.821
56 3017 1.7499
57 334 0.36525
58 2601 -0.76893
59 1396 -3.5823
60 329 -7.1252
61 380 -9.846
62 1520 -10.636
63 1862 -11.518
64 1237 -12.643
65 2070 -14.836
66 640 -23.656
I don't have prediction software implemented yet, so I can't give any estimates, so... Any ideas? Considering the matrix is ill-conditioned, I'm not sure those numbers can be trusted. It could be that my MATLAB implementation is wrong, so here's the code if anyone wants to check it out.
SteveGPage
11-03-2009, 15:15
I gave it a shot. I'm not sure I implemented it correctly, but matrix A (Ax = b) always comes up with a large conditioning number - nearly singular, which means that small changes in b, or the matches results, would result in huge shifts in OPR/DPR for teams.
(snip)
I don't have prediction software implemented yet, so I can't give any estimates, so... Any ideas? Considering the matrix is ill-conditioned, I'm not sure those numbers can be trusted. It could be that my MATLAB implementation is wrong, so here's the code if anyone wants to check it out.
I think that you are on to something, and I do think that the +/- calculation can and would be important. I've been struggling with the following equation, trying to figure out how to implement it and do the calculation, so let me know what you all think. It is similar to Boggle's concept above, and may be essentially the same result, but can't figure out how to parse the data to actually make it happen, especially since it creates a 2N x 2N matrix...
Two equations:
1. (Xioblue + Xjoblue + Xkoblue) - (Xldred + Xmdred + Xndred) = Scoreblue
2. (Xlored + Xmored + Xnored) - (Xidblue + Xjdblue + Xkdblue) = Scorered
Where ...
............X
..............io (Team i - OPR)
................blue (Alliance)
and likewise, id would represent Team i - DPR.
You would have to solve for both the OPR and DPR for each team.
For the DC regional, which had 65 teams, it would be a 130x130 matrix * {x} = Bio or Bid, which would allow you to then solve for the separate OPR and DPR values. I don't have a good way to parse this, much less see if the results actually mean anything, but the concept came from a friend of mine - Kenneth Massey, who developed one of the BCS algorithms (www.masseyratings.com) so I think it has merit.
For the DC regional, I did the following simple calculation to try and get a similar estimated value for how tough the match was:
AVG[((TotalMatchPoints/TotalAlliancePoints)*TeamOffensivePoints) + (TeamOffensivePoints – TeamDefensivePoints)]
MATCH_ID ALLIANCE_ID TEAM_ID OFF_POINTS DEF_POINTS
.....1................1................1.......... ...20...............10
.....1................1................2.......... ...10...............10
.....1................1................3.......... ...15................5
.....1................2................4.......... ....0................10
.....1................2................5.......... ...10...............20
.....1................2................6.......... ...20...............20
Example:
Total Match Points = SUM(OFF_POINTS), GROUP BY MATCH_ID
Total Alliance Points = SUM(OFF_POINTS), GROUP BY MATCH_ID, ALLIANCE_ID
Team 1
((75/45)*20 + (20 – 10)) = 43.33
Team 2
16.66
Team 3
35
Team 4
((75/30)*0 + (0 – 10)) = -10
Team 5
15
Team 6
50
Alliance 1 43.33 + 16.66 + 35 = 95
Alliance 2 (-10) + 15 + 50 = 55
Alliance 1/Alliance 2 = 1.72 – Alliance 1 72% stronger
I think that you are on to something, and I do think that the +/- calculation can and would be important. I've been struggling with the following equation, trying to figure out how to implement it and do the calculation, so let me know what you all think. It is similar to Boggle's concept above, and may be essentially the same result, but can't figure out how to parse the data to actually make it happen, especially since it creates a 2N x 2N matrix...
Two equations:
1. (Xioblue + Xjoblue + Xkoblue) - (Xldred + Xmdred + Xndred) = Scoreblue
2. (Xlored + Xmored + Xnored) - (Xidblue + Xjdblue + Xkdblue) = Scorered
Where ...
............X
..............io (Team i - OPR)
................blue (Alliance)
and likewise, id would represent Team i - DPR.
You would have to solve for both the OPR and DPR for each team.
OK, so either your idea is identical to Bongle's, or I misunderstood him, because what you explained above is exactly what I implemented. Bongle's been away from the topic for a while, hopefully he'll see this and let us know if that's what he meant.
OK, so either your idea is identical to Bongle's, or I misunderstood him, because what you explained above is exactly what I implemented. Bongle's been away from the topic for a while, hopefully he'll see this and let us know if that's what he meant.
Steve's idea appears to be the same as mine, or at least his two equations are. I tried to implement it on tuesday, but it had bugs and I haven't had to time to get back to it. It is unfortunate that the matrix comes out as somewhat ill-conditioned, but I guess that isn't that terribly surprising since the amount of data we're processing is fairly small.
I'll try again to implement this new matrix tonight, and I'll plug it into my prediction code to see if it is any better than the more basic OPR/DPR stats.
We need to come up with a name for this more-complex stat: how about OPR+ and DPR+?
SteveGPage
12-03-2009, 10:18
Steve's idea appears to be the same as mine, or at least his two equations are. I tried to implement it on tuesday, but it had bugs and I haven't had to time to get back to it. It is unfortunate that the matrix comes out as somewhat ill-conditioned, but I guess that isn't that terribly surprising since the amount of data we're processing is fairly small.
I'll try again to implement this new matrix tonight, and I'll plug it into my prediction code to see if it is any better than the more basic OPR/DPR stats.
We need to come up with a name for this more-complex stat: how about OPR+ and DPR+?
I figured as much, and am glad you have had more success in implementing it than I have! I tried to get my son, a senior in college - Comp Sci/Math Major to help me ... but "NO" he didn't have time to help me with my "homework'! :) I like the idea of OPR+ and DPR+ to indicate the additional complexity of the stat. I'd love to see what you are able to do, as well as how predictive the resulting values are. Thanks for all your hard work and your efforts! If there is anything I can do to assist or push this along, just let me know!
Steve
Jared Russell
12-03-2009, 10:31
This is starting to get seriously cool guys...the Sabremetrician in me is very happy.
How about a VORR stat (Value over replacement robot)?
DISS (Defense independent scoring statistics)?
Pythagorean W-L expectations?
Win shares?
The possibilities are endless...
SteveGPage
12-03-2009, 10:34
Steve's idea appears to be the same as mine, or at least his two equations are. I tried to implement it on tuesday, but it had bugs and I haven't had to time to get back to it. It is unfortunate that the matrix comes out as somewhat ill-conditioned, but I guess that isn't that terribly surprising since the amount of data we're processing is fairly small.
I'll try again to implement this new matrix tonight, and I'll plug it into my prediction code to see if it is any better than the more basic OPR/DPR stats.
We need to come up with a name for this more-complex stat: how about OPR+ and DPR+?
One other thing, then I'll go back to my day job ... When I was talking to Kenneth Massey (the BCS guy) he also suggested something, that would modify these equations just a bit - but would require team by team scouting. The red or blue score would NOT be the final score as published, but would first, obviously, not include penalties - so we are really measuring "capabilities" not just performance; and secondly, if you were to have added MR to your own alliance - so as to avoid <G22>, the points that you scored on a alliance partner would be removed from the opposing alliance's score. How much of an effect would this cause in the long run, I don't think much - but if we are basing the OPR+ and DPR+ on a limited number of matches, then it could very likely be significant.
Steve
One other thing, then I'll go back to my day job ... When I was talking to Kenneth Massey (the BCS guy) he also suggested something,
A good idea (it would certainly increase accuracy), but my goal (for my program, at least), is to try and provide the most accurate scouting-independent ranking possible using only match data.
As for implementation of OPR+/DPR+, how I arranged my matrix was:
Odd Rows (for row i): "Team i/2's total score is equal to the weighted sum of the team i/2's alliance OPRs minus the weighted sum of team i/2's opponents' DPRs"
Constant: team i/2's total score
Coefficients: Alternating
Odd columns (col j): # of times team i/2 played with team j/2 (positive)
Even columns (col j): # of times team i/2 played against team j/2 (negative)
Even Rows (for row i): "Team i's opponents' score is equal to the weighted sum of the opponents' alliance OPRs minus the weighted sum of team i's alliance's DPRs"
Constant: team i/2's opponents' total score
Coefficients: Alternating
Odd columns (col j): # of times team i/2 played against team j/2 (positive)
Even columns (col j): # of times team i/2 played with team j/2 (negative)
For verification, I'm pretty sure that the sum of the absolute values of each row should equal the number of matches that team played times 6.
SteveGPage
12-03-2009, 16:45
A good idea (it would certainly increase accuracy), but my goal (for my program, at least), is to try and provide the most accurate scouting-independent ranking possible using only match data.
As for implementation of OPR+/DPR+, how I arranged my matrix was:
...
I think that is a great goal to have that level of information! Certainly, we will continue to do scouting, and would never expect a particular algorithm to tell us who or who not to select. This is a tool to use in that over all process. My scouts will continue to do pit scouting, as well as individual match scouting, and I think we will be looking at the OPR+/DPR+ type of values to help us find those teams down in the noise of the competition, that may have a very low ranking, but have the qualities we are looking for in an alliance.
I would love to see how you finally implement this, since it is questionable that I will be able to put in my database between now and next weekend, especially since I am using a datawarehouse and a Business Intelligence tool to create the reports. The data interface is still lagging!
The methodology you described is exactly what I was looking doing as well, and I believe it has merit! Good luck with getting it debugged! Good luck at your competitions!
If anyone else is working on these concepts, and will be at the Chesapeake Regional next week, I would love to chat with you there!
Steve
SteveGPage
13-03-2009, 08:59
...
I'll try again to implement this new matrix tonight, and I'll plug it into my prediction code to see if it is any better than the more basic OPR/DPR stats.
...
Just heard my Comp Sci/Math Major son is coming home for the weekend. He was excited to hear what we were working on and wants to help me get something up and running this weekend. If you would like, we could work on any issues you may be having and perhaps get something up to the CD community prior to next week's competitions.
Steve
Killraine
13-03-2009, 12:09
Just heard my Comp Sci/Math Major son is coming home for the weekend. He was excited to hear what we were working on and wants to help me get something up and running this weekend. If you would like, we could work on any issues you may be having and perhaps get something up to the CD community prior to next week's competitions.
Steve
So in time for Chesapeake?
SteveGPage
13-03-2009, 12:16
So in time for Chesapeake?
Yes, that is my plan! If I can't get a release on CD by then, I plan on having a working copy on my machine. Just come and find me in the stands on Friday and I'll be happy to either share the app, or at least be able to share the results with you. I try and sit in the upper section of the stands - to the right of the field (near the air exchange vents - which has an outlet to plug into!)
Steve
Joe Ross
14-03-2009, 09:30
With v6, I was not able to get predictions for the Los Angeles regional (CA). Am I doing something wrong, or did is something on FIRST's side screwy?
With v6, I was not able to get predictions for the Los Angeles regional (CA). Am I doing something wrong, or did is something on FIRST's side screwy?
Sorry, v6 has a bug with predictions. I'll upload a fixed version soon.
Edit: v7 now up. The only external improvement (I think) is that predictions are fixed and now work mid-way through a regional.
Edit2: Fixed a parsing issue with single-digit teams.
The Lucas
14-03-2009, 11:49
Sorry, v6 has a bug with predictions. I'll upload a fixed version soon.
Edit: v7 now up. The only external improvement (I think) is that predictions are fixed and now work mid-way through a regional.
Edit2: Fixed a parsing issue with single-digit teams.
Can you release the source as well?
I m looking into giving it a run offline option (-o) in case there is no internet publically available at the Philly regional. I am thinking about saving all the html results files in a local directory structure (instead of the temp file). That way on Sat I can update the html file by hand and keep re running the calc. I am not sure if I will have time to get this working or not
Thanks,
Brian
Can you release the source as well?
I m looking into giving it a run offline option (-o) in case there is no internet publically available at the Philly regional. I am think about saving all the html results files in a local directory structure (instead of the temp file). That way on Sat I can update the html file by hand and keep re running the calc. I am not sure if I will have time to get this working or not
Thanks,
Brin
See attached.
SteveGPage
15-03-2009, 11:14
Yes, that is my plan! If I can't get a release on CD by then, I plan on having a working copy on my machine. Just come and find me in the stands on Friday and I'll be happy to either share the app, or at least be able to share the results with you. I try and sit in the upper section of the stands - to the right of the field (near the air exchange vents - which has an outlet to plug into!)
Steve
We were able to finally get OPR+ and DPR+ values calculated from the equation that Bongle and I had both posted. Attached is the perl script that my son and I were able to get together this weekend.
Usage: cmd line: perl scouteval.pl {qualmatch}.txt ---- which will create a file called results.txt, and where {qualmatch} is the file created from the usfirst match results page, copied into a text file. Then use whatever software you use to solve the matrix for the team OPR+ and DPR+ values.
The OPR+ and DPR+ values (sorted by OPR+), as calculated for the DC regional, is as follows:
Team Number OPR+ DPR+
118 78 38
2199 72 6
116 68 44
1731 66 32
1712 66 26
176 64 8
2068 62 32
1629 60 28
836 60 18
2961 58 26
2964 56 50
181 56 34
597 54 40
122 54 22
1418 54 10
45 52 54
1872 52 30
449 52 20
401 50 36
365 48 0
3046 46 34
1446 46 12
1915 44 36
272 42 34
339 42 26
587 42 26
611 42 12
2913 40 28
709 40 26
2914 40 16
53 40 16
1900 36 32
1748 36 8
620 34 16
1123 32 26
357 32 24
2819 30 40
1522 30 12
234 30 6
2911 30 0
346 28 8
538 26 18
2377 26 10
615 24 22
1719 22 46
768 22 26
1793 22 22
2962 20 12
7 20 12
2421 20 -4
1849 18 6
623 18 -10
614 18 -14
1111 16 6
2963 14 2
1727 12 28
2912 12 4
2900 10 2
1370 10 0
2121 8 -2
1885 8 -6
1279 6 26
2729 6 -4
2537 2 34
1699 -16 16
A couple of things I noticed, if you run the OPR+/DPR+ numbers with incomplete data, the numbers will look wrong, but relative sorting will be pretty close - but expect numbers like +800 to - 800. When all of the matches finish, the numbers should settle out to values like above. Also, we noticed that we could predict the outcome of the elimination matches about 65-70% of the time.
We are working to automate the process.
Let me know what you think!
Steve
martin417
16-03-2009, 11:03
I get this error when I run Oprnet on some regionals. (BAE for one) I know Peachtree and SanDiego work, but haven't found others that do yet.
Downloaded 34342 bytes
File download complete
Parsing!
No matches found. This regional may not have run yet, or may have HTML output that the parser does not recognize.
Failure to parse XML. Code: -2147467259
I get this error when I run Oprnet on some regionals. (BAE for one) I know Peachtree and SanDiego work, but haven't found others that do yet.
Look at the FIRST-provided results (http://www2.usfirst.org/2009comp/events/NH/matchresults.html) for BAE. They don't exist for the qualification matches, and so OPRNet cannot run. Some people in this thread have written parsers that work with TBA results, which are posted. Check the whole thread and see if there is an app posted that can read TBA results.
Look at the FIRST-provided results (http://www2.usfirst.org/2009comp/events/NH/matchresults.html) for BAE. They don't exist for the qualification matches, and so OPRNet cannot run. Some people in this thread have written parsers that work with TBA results, which are posted. Check the whole thread and see if there is an app posted that can read TBA results.
Part of the reason I extended my program to pull from multiple sources was to eventually put all of the data into a standardized, formatted .csv file that any program or Excel sheet could read. That way, we could pass around a master file with our programs for those who do not have the internet immediately available (or are blocked by a firewall for whatever reasons).
The format for a line will be something like
REG_CODE,MATCH_NUM,RED_1,RED_2,RED_3,BLUE_1,BLUE_2 ,BLUE_3,R_SCORE,B_SCORE
Where REG_CODE is the usfirst.org regional code. There will be 1 line for every match at every regional (roughly 48*76 = 3648 lines). Once the matches are verified I'm also going to put in a new 'feature' that writes the parsed lines directly into the Java source code for the next time the code is compiled (which is often for me since I use a similar program to do my Fantasy FIRST picks). The order it will check for valid data is source code --> local parsed file --> local html file --> usfirst.org --> tba.net ... and it will go until it finds valid data. Buckeye data still isn't up though, so I wonder what we'll have to do to get those scores :confused:
Then, eventually I'll put a scouting layer on top of that so you can input data into it at a regional. Then, I'll make a simple version of this input, so someone can input it via PDA, iPhone, or whatever other touchpad technology comes available. This part won't happen publicly till the offseason though.
I've been away from it for a few days since I was at the FL regional, but now it's back to work to have it done in time for Atlanta.
-- edit -- Ooh and a w00t to Greg Marra and crew for simplifying the tba.net urls for each regional and year!
martin417
16-03-2009, 17:58
I ran through all the regionals that worked (three didn't) and put each one on a spreadsheet. I also combined tham all into one sheet (master). hope this is useful to teams.
Lil' Lavery
16-03-2009, 18:09
We were able to finally get OPR+ and DPR+ values calculated from the equation that Bongle and I had both posted. Attached is the perl script that my son and I were able to get together this weekend.
Usage: cmd line: perl scouteval.pl {qualmatch}.txt ---- which will create a file called results.txt, and where {qualmatch} is the file created from the usfirst match results page, copied into a text file. Then use whatever software you use to solve the matrix for the team OPR+ and DPR+ values.
The OPR+ and DPR+ values (sorted by OPR+), as calculated for the DC regional, is as follows:
Team Number OPR+ DPR+
118 78 38
2199 72 6
116 68 44
1731 66 32
1712 66 26
176 64 8
2068 62 32
1629 60 28
836 60 18
2961 58 26
2964 56 50
181 56 34
597 54 40
122 54 22
1418 54 10
45 52 54
1872 52 30
449 52 20
401 50 36
365 48 0
3046 46 34
1446 46 12
1915 44 36
272 42 34
339 42 26
587 42 26
611 42 12
2913 40 28
709 40 26
2914 40 16
53 40 16
1900 36 32
1748 36 8
620 34 16
1123 32 26
357 32 24
2819 30 40
1522 30 12
234 30 6
2911 30 0
346 28 8
538 26 18
2377 26 10
615 24 22
1719 22 46
768 22 26
1793 22 22
2962 20 12
7 20 12
2421 20 -4
1849 18 6
623 18 -10
614 18 -14
1111 16 6
2963 14 2
1727 12 28
2912 12 4
2900 10 2
1370 10 0
2121 8 -2
1885 8 -6
1279 6 26
2729 6 -4
2537 2 34
1699 -16 16
A couple of things I noticed, if you run the OPR+/DPR+ numbers with incomplete data, the numbers will look wrong, but relative sorting will be pretty close - but expect numbers like +800 to - 800. When all of the matches finish, the numbers should settle out to values like above. Also, we noticed that we could predict the outcome of the elimination matches about 65-70% of the time.
We are working to automate the process.
Let me know what you think!
Steve
I love sabremetrics, OPR/DPR, +/-, and stats in general. I was excited for these OPR+ and DPR+ numbers. But unfortunately, just from looking at them, I can tell we might have taken it a step too far and they might have become less accurate.
The fact that my former team, 116 is ranked 3rd at the event should be the first indicator (as well as the ranks of 45, 365, and 234 being so low), despite struggling to score the entire regional. I don't have the raw OPR numbers handy (on my Mac), so I can't give detailed comparisons between the rankings, but judging by these, I think it may have become less accurate to what the team's real performance was.
SteveGPage
16-03-2009, 21:42
I love sabremetrics, OPR/DPR, +/-, and stats in general. I was excited for these OPR+ and DPR+ numbers. But unfortunately, just from looking at them, I can tell we might have taken it a step too far and they might have become less accurate.
The fact that my former team, 116 is ranked 3rd at the event should be the first indicator (as well as the ranks of 45, 365, and 234 being so low), despite struggling to score the entire regional. I don't have the raw OPR numbers handy (on my Mac), so I can't give detailed comparisons between the rankings, but judging by these, I think it may have become less accurate to what the team's real performance was.
I have similar concerns. Last night I ran every regional that we had numbers for. I had hoped to create a combined "top 25" list from every regional, until I saw which teams rose to the top, and which teams did not. I did a double check on TBA to see how these teams had actually performed, and was surprised that teams in some regionals - such as WI, NYC, and Oregon - were showing up on the top despite the fact that many had only moderate records, and did not appear to be high scorers. Some regionals, the numbers corresponded with what I expected, but other regionals, the numbers did not. The one factor that I'm still not sure about, and perhaps you can help me with this Sean - the team scores are not only the robot - so the purpose of this equation was designed to look at not only how effective the robot is, but also how well the HP does, too.
During DC, I had my scouts do extensive scouting on each match, looking at how many MRs each scored, and how many MRs were scored on them (developing a match by match +/-). What I failed to do, was to have them track the HP and how many SCs the team delivered to the HP, both of which had profound impact on the game. If I just looked at the performance of each robot, 45, 365, and 234 were on the top of my list. But I knew from observations that 2199's HP was deadly, and 118 had the ability to get at least 2 SCs exchanged. So I wonder if there isn't some aspect of the OPR+ calculation relying on those other factors, and not just how effective the robot is.
I'm going to run these numbers (looking at all three factors - robot, HP and SCs) while we are in the midst of the competition at Chesapeake this weekend to see if I see any trends. Perhaps this equation isn't going to give us the info we are looking for, but I still want to run some additional numbers to see how they do.
Best regards,
Steve
AlexD744
16-03-2009, 22:08
It was perfect because we were #1 after Friday. And therefore it must have been the best tool ever. Just Kidding, however, it really did help in our meeting. It confirmed that KRUNCH was as amazing as we thought.
SteveGPage
16-03-2009, 22:45
It was perfect because we were #1 after Friday. And therefore it must have been the best tool ever. Just Kidding, however, it really did help in our meeting. It confirmed that KRUNCH was as amazing as we thought.
The numbers you are referring to, are the OPR/DPR numbers. The numbers that we are talking about are the OPR+/DPR+ numbers - which, yes, I know don't look a lot different! :)
I pulled the data from FL, and ran the calculation for the finals, using the OPR+ and DPR+ numbers. Here are the results ...
First, averaging the score across all three finals matches, the avg Red score was 74 and the avg Blue score was 84.
I plugged the calculated values into the OPR+ and DPR+ formulas, and here is the outcome Red 68, Blue 90. An 8% difference for Red and a 7% difference for Blue between the predicted values and actual values. Penalties, which are not considered in the calculations, could easily account for that kind of discrepancy.
In doing so, one thing became obvious, the OPR+ number can not be taken into consideration by itself, but must be linked with the DPR+ number - but not simply by adding them together - but in the separate calculations of Red vs Blue Score. I'm going to do some additional modelling of the data to see how we can get a combined ranking value.
I am going to run additional calculations at other regionals and see how they correspond.
Steve
andrew418
17-03-2009, 16:10
Hi, I've been trying to access the ratings for the Dallas regional, and the program has not been able to parse the html data. Does anyone know why?
Hi, I've been trying to access the ratings for the Dallas regional, and the program has not been able to parse the html data. Does anyone know why?
Annoyingly, it looks like the HTML output by the Texas regional is quite different than that spat out by every other regional so far. It has the same style as the HTML printed out by the first 1-2 weeks of regionals last year. It might be time to adjust OPRNet to read off of TBA instead of USFirst.
billbo911
17-03-2009, 16:45
Annoyingly, it looks like the HTML output by the Texas regional is quite different than that spat out by every other regional so far. It has the same style as the HTML printed out by the first 1-2 weeks of regionals last year. It might be time to adjust OPRNet to read off of TBA instead of USFirst.
Well, as long as you get the TBA feed version perfected by next Wednesday, you have my permission to do it. :p
Seriously now, if a TBA version is more reliable, then go for it. With the latest copy of your code AND a TBA version, I feel very confident we will be able to gather some fairly valid information. It will be interesting to compare the results.
Nawaid Ladak
17-03-2009, 18:41
i was wondering, i used to use OPR's back in 2006 and 2007 when they first became available
I was curious as to how the opponents you play factor into the situation. i'd much rather see a formula like a RPI or a SoS used alongside the OPR, DPR, and PM systems already established
ie
RPI
=
teams winning percentage x .25 +
opponents winning percentage x .5 +
opponents opponents winning percentage x .25
SoS
=
(Opponents win percentage) - (Your Alliance Partners win percentage)
i think looking at these stats alongside the OPR, DPR and PM systems can truly show which teams are better than what is shown on the standings, and which teams just got bad luck and got paired with their worst nightmare's
(Im using this to scout because i don't have any video from the Oregon Regional to view.)
Well, as long as you get the TBA feed version perfected by next Wednesday, you have my permission to do it. :p
Seriously now, if a TBA version is more reliable, then go for it. With the latest copy of your code AND a TBA version, I feel very confident we will be able to gather some fairly valid information. It will be interesting to compare the results.
V8: Now uses TBA as a fallback for 2009 regionals, and as the only source for pre-2009 regionals. Note that because of this, this version should be able to do any regional that TBA has in its database, which is a big improvement over earlier versions.
...It may have a lot of bugs in it. I think I got rid of most of them, but there are probably a few left.
RPI
=
teams winning percentage x .25 +
opponents winning percentage x .5 +
opponents opponents winning percentage x .25
I will try to implement this, I don't think it should be too hard so long as I get the recursion right.
I will try to implement this, I don't think it should be too hard so long as I get the recursion right.
V9: Now computes RPI. I looked at SoS, couldn't find any quick explanations for it, so I didn't bother.
Gaurav27
17-03-2009, 21:37
Bongle, you're awesome!
It works like a charm! :eek:
By the way, is there any way we can output the temporary file created through command prompt to an EXCEL worksheet?
Just for quick ranking purposes...?
opponents opponents winning percentage x .25
Also, what do you mean by the above statement? I couldn't catch that.
engunneer
17-03-2009, 21:47
(Im using this to scout because i don't have any video from the Oregon Regional to view.)
You can view videos of the Oregon regional at http://www.bpsepaa.com/video . login is guest with password guest (or you can register)
Nawaid Ladak
17-03-2009, 23:06
Also, what do you mean by the above statement? I couldn't catch that.
the win percentage of whoever your opponents played during the regional
You can view videos of the Oregon regional at http://www.bpsepaa.com/video . login is guest with password guest (or you can register)
yeah, i saw that five minutes after i posted that.
Oh, SoS-Strength of Schedule, pretty much, what was your opponents record. but i guess that's already factored into the RPI as is
i love it when we can use a formula for College Basketball and FIRST at the same time
Bongle, you're awesome!
It works like a charm! :eek:
By the way, is there any way we can output the temporary file created through command prompt to an EXCEL worksheet?
Just for quick ranking purposes...?
From the command line:
"oprnet (regional) (year) (statistic) (team/rank ranking) q > output.out"
Ex: "oprnet il 2009 all r q > output.txt" will print all stats for Midwest 2009 to output.txt in a tab-separated table.
That will spit out all the data to a file called output.out (it can be called anything). It'll all be tab-separated (make sure you put that q there, or it won't put the tabs), so you can copy/paste it into excel. Look through the thread for examples of the usage.
Also, what do you mean by the above statement? I couldn't catch that.
WP: wins / games played
OWP: Average of a team's opponent's WP's
OOWP: Average of a team's opponent's OWP's
This recursive implementation is very slow, but it was very easy to implement.
I'm unable to get any results from years other than 2009, using v9.
File download complete
Failure to parse qualification match 0
Failure to parse from TBA and USFirst, giving up. Code: -2147467259
This is a nice tool and most of the information is pretty accurate according to my own.
I'm unable to get any results from years other than 2009, using v9.
File download complete
Failure to parse qualification match 0
Failure to parse from TBA and USFirst, giving up. Code: -2147467259
Strange. I'll try to look into it tonight. I'm getting the same result.
There is no Match Zero....
There is no Match Zero....
That's not the problem. That is just an error in how I report which match it failed on (it should have a +1 on it). My best guess is that TBA changed how its HTML is created, and now my parser doesn't work anymore.
Edit: And my suspicion is correct: they've greatly changed the HTML. However, it'll be easier to parse now, so it shouldn't take too long to make a new parser.
Edit: And my suspicion is correct: they've greatly changed the HTML. However, it'll be easier to parse now, so it shouldn't take too long to make a new parser.
Yea, my TBA parser broke a couple of weeks ago because of this...didn't even think about it since the match 0 thing threw me off. I had to add a bit of protection from those match 0's...
In my latest version I have a flag set which writes a formatted line out to a java file. If I run the main program from Eclipse, it will download all of the data and auto-program itself into the next time the program launches. Fun stuff ... or scary iRobot stuff, however you look at it :ahh:
I will say that doing the permanent data increases the program size by a few hundred K, but if you're using Java a few hundred K shouldn't matter :p
V10
-Fixes parsing issue
-Fixes bugs in RPI implementation
Nawaid Ladak
30-03-2009, 20:41
when i select all regionals, under that tab
it will terminate the program for some reason... is this because both MN and GLR (sry, i mean MSC) haven't been completed?
when i select all regionals, under that tab
it will terminate the program for some reason... is this because both MN and GLR (sry, i mean MSC) haven't been completed?
That's because I added the text for that feature, but didn't finish adding the feature. I suppose I'll do it now. v11 coming soon (if it turns out to be easy).
Still can't get old regionals.
This is the tail of `oprnet.exe ny 2008 all`
Downloaded 148551 bytes
File download complete
Failure to parse qualification match 0
Solving matrix...
Could not perform OPR calculations. There may not have been enough matches play
ed. Try again later.
Failure to compute statistics. Code: -2147467259
Also, instead of putting in the search all, maybe it would just be better to run it on your own and post the results, so we don't harass first's bandwidth too much (or have to wait for it to process)
Alright folks, the feature that my PM box has been filling up for:
V11
-Can now do every single regional at once
-Fixed a bug where it would lock up trying to parse some regionals
Example syntax:
oprnet all 2009 all r q > allRegionals.txt
Will print all statistics for all regionals to allRegionals.txt. On my computer, it took about 1 minute to finish. If it takes longer than 5, something is wrong-ish. You'll still be able to open the file, but it might not have every team in it.
Now that everything can be spat into a single file and analyzed in excel, I've realized:
1) RPI is still broken (look at the 'gt' regional's RPIs)
2) SAA is fairly useless so far as predicting a team's finishing position
3) OPR is fairly good at predicting a team's finishing position
4) I need to do some more parsing to get more statistics. How does OPR correlate to win %? What is the distribution of OPRs among elimination alliances?
You make a good point about harrassing bandwidth. Here is a nice tab-separated data block:
Rank Outof Reg Team OPR SAA PM RPI
1 59 on 188 54.8454 20.1327 34.7127 0.606606
2 59 on 2056 48.8918 8.98663 39.9052 0.619678
3 59 on 1114 34.516 11.1734 23.3426 0.531504
4 59 on 2386 33.961 2.10167 31.8593 0.621064
5 59 on 610 33.2707 17.1356 16.1352 0.570747
6 59 on 1503 33.0993 12.0785 21.0208 0.541568
7 59 on 1126 32.6056 17.8517 14.754 0.521051
8 59 on 1141 31.1227 3.41049 27.7122 0.522872
9 59 on 772 28.7774 31.3252 -2.54786 0.493484
10 59 on 2625 28.3546 22.3965 5.95817 0.517007
11 59 on 2200 27.7983 2.30793 25.4904 0.515181
12 59 on 1241 25.869 12.2174 13.6517 0.512651
13 59 on 854 25.4401 21.5575 3.8826 0.57824
14 59 on 2361 25.0423 10.3198 14.7225 0.478506
15 59 on 1310 23.5855 10.9669 12.6186 0.544426
16 59 on 886 23.5667 13.7587 9.80799 0.511241
17 59 on 1305 22.5284 27.9254 -5.39696 0.517104
18 59 on 1244 21.4576 36.9551 -15.4975 0.491933
19 59 on 1219 21.2337 8.90821 12.3255 0.577973
20 59 on 3117 21.0902 17.1868 3.90336 0.477793
21 59 on 1006 20.9014 20.0291 0.872234 0.540557
22 59 on 781 20.1785 29.9166 -9.73807 0.465813
23 59 on 2852 19.8415 16.0344 3.80707 0.506237
24 59 on 2809 19.4044 25.2875 -5.88309 0.546606
25 59 on 2505 19.0277 12.0269 7.00082 0.547673
26 59 on 2166 18.9514 26.5083 -7.55683 0.48297
27 59 on 2198 18.9183 14.3635 4.55479 0.457442
28 59 on 1535 18.0582 8.27375 9.78445 0.557943
29 59 on 1334 17.9872 5.18729 12.8 0.546712
30 59 on 2076 16.8631 17.7665 -0.903471 0.497861
31 59 on 2935 16.7217 37.1408 -20.4191 0.483738
32 59 on 1605 16.4245 22.4556 -6.03112 0.526173
33 59 on 1846 15.7142 27.5082 -11.7939 0.443499
34 59 on 1075 15.0236 14.0354 0.988181 0.491583
35 59 on 2013 14.5088 15.0915 -0.582691 0.535436
36 59 on 2994 14.2357 2.34451 11.8911 0.413479
37 59 on 677 14.1976 2.81744 11.3801 0.485846
38 59 on 1518 13.8889 25.2581 -11.3692 0.511929
39 59 on 1559 13.7832 22.356 -8.57278 0.480471
40 59 on 1547 13.696 13.6963 -0.000324249 0.529993
41 59 on 2626 13.5433 28.2256 -14.6823 0.443538
42 59 on 1404 13.5305 21.6218 -8.09133 0.520131
43 59 on 1312 12.2419 15.9158 -3.67384 0.465242
44 59 on 919 11.6764 36.4368 -24.7604 0.475998
45 59 on 1835 10.7791 6.87518 3.90387 0.503955
46 59 on 1514 10.7266 32.29 -21.5634 0.421039
47 59 on 1558 10.6766 31.0299 -20.3533 0.41148
48 59 on 2634 8.86438 22.7321 -13.8678 0.44543
49 59 on 1325 8.59273 13.6599 -5.0672 0.502041
50 59 on 2185 8.50867 29.1764 -20.6678 0.492032
51 59 on 771 7.85468 7.58999 0.264695 0.524004
52 59 on 1482 7.19423 11.0677 -3.87344 0.504039
53 59 on 907 6.93794 13.1205 -6.18259 0.435557
54 59 on 843 5.35 31.3512 -26.0012 0.432592
55 59 on 865 5.15013 14.3252 -9.17505 0.448685
56 59 on 1053 3.10232 38.5109 -35.4085 0.408296
57 59 on 2670 1.63005 33.2534 -31.6234 0.420281
58 59 on 1246 1.47727 38.4821 -37.0049 0.39202
59 59 on 1815 1.03729 -7.78935 8.82664 0.440189
1 44 az 1726 51.507 5.52655 45.9805 0.629979
2 44 az 69 45.903 7.08524 38.8177 0.59304
3 44 az 2840 36.2716 13.8319 22.4397 0.557527
4 44 az 1828 34.0316 19.0508 14.9808 0.521489
5 44 az 1633 30.8113 8.78649 22.0248 0.506179
6 44 az 60 29.2345 12.8123 16.4222 0.514477
7 44 az 3014 28.7811 11.0879 17.6932 0.527802
8 44 az 2570 28.7099 18.3277 10.3822 0.564564
9 44 az 2844 22.8101 18.0122 4.79786 0.490447
10 44 az 1492 22.4383 29.4573 -7.01895 0.513632
11 44 az 842 22.3816 19.4508 2.93075 0.530111
12 44 az 3048 22.0912 18.677 3.41423 0.457237
13 44 az 1013 21.1482 21.858 -0.709834 0.490043
14 44 az 991 20.034 8.14128 11.8927 0.448315
15 44 az 39 19.017 10.2414 8.77559 0.571386
16 44 az 1165 19.0092 13.8099 5.19927 0.533687
17 44 az 3019 18.4419 15.2608 3.18107 0.48368
18 44 az 2375 17.6358 14.1543 3.4815 0.508218
19 44 az 2196 16.76 44.9923 -28.2324 0.441389
20 44 az 2837 16.3634 13.6865 2.67689 0.502039
21 44 az 2102 16.2802 1.91595 14.3642 0.557264
22 44 az 2414 15.4971 13.5909 1.90618 0.454904
23 44 az 498 15.0806 15.7795 -0.69893 0.486068
24 44 az 996 13.7852 13.7223 0.0629649 0.50455
25 44 az 2128 13.5854 15.9223 -2.33683 0.458603
26 44 az 2134 13.424 13.5552 -0.131222 0.475701
27 44 az 812 12.094 3.2338 8.86023 0.527306
28 44 az 1852 10.8461 30.2139 -19.3678 0.394847
29 44 az 2839 10.6184 3.5947 7.02367 0.557668
30 44 az 698 10.4561 6.63889 3.81722 0.524073
31 44 az 1290 9.95298 17.9291 -7.97615 0.456184
32 44 az 1212 9.70459 17.6509 -7.94631 0.492566
33 44 az 2662 9.39008 25.059 -15.6689 0.443495
34 44 az 2647 9.22693 17.1734 -7.94646 0.432203
35 44 az 2478 8.87174 19.4835 -10.6117 0.507018
36 44 az 1798 5.44938 17.8092 -12.3598 0.428547
37 44 az 2486 5.24913 15.2961 -10.047 0.405252
38 44 az 1324 4.703 29.327 -24.624 0.435853
39 44 az 2413 4.68567 16.8566 -12.1709 0.506369
40 44 az 1164 3.92853 12.2307 -8.30218 0.458119
41 44 az 2657 0.226015 10.3164 -10.0904 0.447286
42 44 az 2406 -5.06044 28.8235 -33.8839 0.384302
43 44 az 2449 -6.14376 30.0496 -36.1933 0.433134
44 44 az 2403 -8.34279 6.46576 -14.8086 0.521029
1 31 la 624 37.5215 7.57843 29.9431 0.604245
2 31 la 2992 36.2094 13.1379 23.0716 0.562424
3 31 la 456 32.1632 10.3153 21.8479 0.519982
4 31 la 364 31.8626 7.21552 24.6471 0.56093
5 31 la 2242 27.359 13.4355 13.9235 0.549976
6 31 la 348 25.7869 8.69074 17.0962 0.526802
7 31 la 1421 25.2036 17.2866 7.91705 0.521378
8 31 la 1477 24.0657 9.14321 14.9225 0.602806
9 31 la 499 23.2864 14.4571 8.82929 0.533008
10 31 la 1927 21.0778 20.3387 0.739096 0.47744
11 31 la 2815 20.9063 19.4731 1.43324 0.551356
12 31 la 3039 20.1723 18.7189 1.45332 0.4897
13 31 la 49 20.0034 5.74428 14.2591 0.536315
14 31 la 2540 19.6792 18.5588 1.12041 0.51948
15 31 la 2183 17.0757 23.8029 -6.72725 0.477688
16 31 la 2975 16.9819 22.0015 -5.01955 0.539639
17 31 la 2091 16.726 8.80537 7.92067 0.494787
18 31 la 1920 16.6725 16.8372 -0.164669 0.501475
19 31 la 2206 16.4536 15.9519 0.501736 0.518175
20 31 la 462 16.3796 14.4039 1.97572 0.486386
21 31 la 538 15.7757 19.3412 -3.56554 0.520708
22 31 la 2920 13.531 24.3581 -10.8271 0.434725
23 31 la 2078 12.0344 21.6879 -9.65344 0.489204
24 31 la 2556 11.0735 15.7073 -4.63386 0.431245
25 31 la 2983 7.98988 24.7153 -16.7255 0.384616
26 31 la 1912 6.80565 26.8757 -20.0701 0.403701
27 31 la 2873 6.19531 24.2784 -18.0831 0.470999
28 31 la 2221 5.74443 29.7362 -23.9917 0.474477
29 31 la 2173 5.33167 26.136 -20.8044 0.448598
30 31 la 2080 4.52307 26.9292 -22.4061 0.460145
31 31 la 1550 1.37417 30.483 -29.1088 0.404223
1 35 in 111 37.5717 22.0022 15.5695 0.552808
2 35 in 45 36.8054 10.0286 26.7768 0.541687
3 35 in 2081 36.32 18.2849 18.0351 0.532106
4 35 in 234 36.021 24.124 11.897 0.542232
5 35 in 292 30.3989 17.1473 13.2516 0.532375
6 35 in 868 30.0659 19.4379 10.6281 0.550754
7 35 in 1720 27.0959 12.2279 14.868 0.567294
8 35 in 2040 26.8393 16.5074 10.332 0.525657
9 35 in 135 25.8244 30.9065 -5.08207 0.5101
10 35 in 1741 24.0896 18.1145 5.97512 0.54593
11 35 in 1760 24.0413 8.84041 15.2009 0.548332
12 35 in 393 23.2011 11.1786 12.0225 0.481147
13 35 in 1747 23.0703 24.7694 -1.69912 0.49194
14 35 in 1327 21.1504 14.3529 6.7975 0.464685
15 35 in 829 21.1318 17.9717 3.16014 0.481572
16 35 in 2856 20.7318 17.9817 2.7501 0.44791
17 35 in 447 20.1074 12.0284 8.07899 0.524031
18 35 in 1000 20.0275 12.302 7.72554 0.54554
19 35 in 1018 19.8793 19.4218 0.457542 0.507752
20 35 in 554 19.1676 20.6737 -1.50609 0.460903
21 35 in 2197 19.0308 21.4792 -2.44839 0.434653
22 35 in 1024 17.9828 33.4499 -15.4671 0.42948
23 35 in 2749 14.6798 28.6512 -13.9714 0.434754
24 35 in 2368 13.6132 26.4408 -12.8276 0.416941
25 35 in 1555 12.5982 9.96872 2.62948 0.453313
26 35 in 2360 12.5275 23.6415 -11.1141 0.493114
27 35 in 461 12.4053 27.4617 -15.0564 0.426025
28 35 in 2867 12.2315 15.0955 -2.86397 0.457781
29 35 in 2171 11.6209 23.4083 -11.7873 0.465667
30 35 in 2783 10.5882 30.9009 -20.3127 0.379917
31 35 in 1501 10.4582 12.196 -1.73785 0.45755
32 35 in 451 9.33853 22.741 -13.4024 0.445716
33 35 in 1646 8.40234 20.9129 -12.5105 0.483242
34 35 in 1529 5.33043 21.5463 -16.2159 0.406377
35 35 in 2909 1.38978 31.5001 -30.1103 0.414814
1 53 ma 155 33.5987 4.62853 28.9701 0.571982
2 53 ma 2009 31.7988 10.1325 21.6663 0.493061
3 53 ma 125 31.7029 12.1213 19.5816 0.538738
4 53 ma 61 30.68 4.54397 26.136 0.592345
5 53 ma 1100 28.9207 10.2872 18.6335 0.608882
6 53 ma 190 28.3785 10.7997 17.5788 0.569714
7 53 ma 69 27.3015 12.2696 15.0319 0.543852
8 53 ma 1153 26.9746 5.09026 21.8843 0.539925
9 53 ma 178 26.3006 9.33681 16.9638 0.589812
10 53 ma 1757 26.1883 0.113529 26.0748 0.546202
11 53 ma 126 24.5894 10.9621 13.6273 0.544783
12 53 ma 2888 24.4331 14.6363 9.79674 0.477459
13 53 ma 1761 24.3744 18.2952 6.0792 0.456348
14 53 ma 1735 23.2025 11.7197 11.4829 0.54218
15 53 ma 1350 22.1187 14.292 7.82674 0.505372
16 53 ma 2877 21.7195 13.3083 8.41116 0.568322
17 53 ma 2104 20.9756 14.2522 6.72342 0.485774
18 53 ma 701 20.5658 2.67166 17.8941 0.580038
19 53 ma 97 20.4236 25.8289 -5.40529 0.423402
20 53 ma 1474 18.9 15.4578 3.44219 0.492468
21 53 ma 2713 17.6279 13.8169 3.81095 0.513335
22 53 ma 88 17.5851 32.2593 -14.6742 0.483855
23 53 ma 2386 17.189 0.658249 16.5307 0.527425
24 53 ma 2423 16.1274 21.5849 -5.45743 0.49302
25 53 ma 157 15.4743 28.897 -13.4227 0.532892
26 53 ma 2349 14.8445 -0.3816 15.2261 0.513039
27 53 ma 2447 14.413 28.098 -13.685 0.384163
28 53 ma 1779 11.5632 36.0711 -24.5079 0.422565
29 53 ma 1768 11.4428 23.0672 -11.6244 0.434834
30 53 ma 213 11.3702 14.6789 -3.30867 0.517722
31 53 ma 2589 11.3455 16.6873 -5.34184 0.513874
32 53 ma 2648 11.1797 8.53841 2.64126 0.491821
33 53 ma 2043 11.0902 23.3465 -12.2563 0.454458
34 53 ma 2103 10.945 11.3027 -0.357683 0.520557
35 53 ma 1916 10.8557 -4.48038 15.3361 0.540653
36 53 ma 1965 10.741 23.3392 -12.5982 0.50579
37 53 ma 348 10.2713 35.753 -25.4817 0.491023
38 53 ma 2871 8.83003 13.6525 -4.82248 0.434888
39 53 ma 2079 8.60672 27.0054 -18.3987 0.458387
40 53 ma 1099 8.07857 14.5298 -6.45121 0.475352
41 53 ma 230 7.96109 14.2207 -6.25961 0.396702
42 53 ma 839 6.734 13.9081 -7.17412 0.388133
43 53 ma 2262 6.64915 18.3149 -11.6658 0.499082
44 53 ma 529 6.23561 32.3697 -26.1341 0.414586
45 53 ma 246 5.11496 18.9505 -13.8356 0.462612
46 53 ma 2876 4.83318 -2.80568 7.63886 0.435023
47 53 ma 549 3.64858 16.0899 -12.4413 0.493332
48 53 ma 2127 2.71515 26.7053 -23.9901 0.40499
49 53 ma 2084 1.06864 15.79 -14.7214 0.459182
50 53 ma 2593 0.876608 15.9154 -15.0388 0.381059
51 53 ma 2124 0.0550931 10.5158 -10.4607 0.455214
52 53 ma 1973 -0.623678 33.3164 -33.94 0.476472
53 53 ma 1027 -3.66528 5.60219 -9.26748 0.411538
1 59 oh 1038 31.831 12.5406 19.2903 0.592624
2 59 oh 1747 30.4297 15.8473 14.5824 0.593656
3 59 oh 291 28.6585 15.305 13.3535 0.541007
4 59 oh 695 28.1463 12.3604 15.7859 0.538719
5 59 oh 1018 27.7495 14.0602 13.6893 0.586798
6 59 oh 868 27.4834 8.54806 18.9353 0.496501
7 59 oh 292 25.3329 21.4342 3.8987 0.532922
8 59 oh 3010 24.7657 7.93989 16.8258 0.544604
9 59 oh 963 22.8459 26.1788 -3.33286 0.545408
10 59 oh 2387 22.6675 11.3124 11.3551 0.534412
11 59 oh 48 22.3503 8.19148 14.1588 0.572769
12 59 oh 829 22.1909 4.45296 17.738 0.519623
13 59 oh 2197 21.6291 14.3872 7.2419 0.53714
14 59 oh 1319 21.3767 17.5604 3.81634 0.551483
15 59 oh 1250 20.9356 22.2275 -1.2919 0.509323
16 59 oh 1248 20.8734 14.0385 6.83486 0.416705
17 59 oh 1317 20.595 14.1922 6.4028 0.494412
18 59 oh 2917 20.1978 10.8899 9.30791 0.515128
19 59 oh 1001 19.0453 9.04296 10.0024 0.472593
20 59 oh 1014 18.9504 8.52196 10.4284 0.553096
21 59 oh 108 18.8939 22.1052 -3.21129 0.492882
22 59 oh 1787 18.3003 28.7125 -10.4122 0.444162
23 59 oh 1502 17.7242 6.00737 11.7168 0.591894
24 59 oh 279 17.548 16.6166 0.9314 0.520326
25 59 oh 1308 17.2366 11.1114 6.1252 0.45716
26 59 oh 2901 16.7762 7.98698 8.7892 0.50303
27 59 oh 1008 16.1752 26.2176 -10.0423 0.465118
28 59 oh 1646 15.5937 11.0258 4.56792 0.53186
29 59 oh 451 15.3489 27.2984 -11.9496 0.448246
30 59 oh 2603 14.8573 14.3233 0.534061 0.527682
31 59 oh 1270 14.4192 15.7114 -1.29225 0.490223
32 59 oh 306 14.3287 18.8962 -4.56746 0.506206
33 59 oh 1990 14.3164 16.1524 -1.83603 0.545983
34 59 oh 379 13.2594 17.7726 -4.51323 0.412675
35 59 oh 461 13.0212 12.3417 0.679443 0.575968
36 59 oh 2941 12.6039 22.9779 -10.374 0.43805
37 59 oh 2031 12.1031 25.0171 -12.914 0.424601
38 59 oh 1143 12.0917 13.0162 -0.924491 0.45803
39 59 oh 964 11.6682 23.9158 -12.2476 0.446072
40 59 oh 677 11.3785 15.7122 -4.33373 0.45041
41 59 oh 2172 11.2238 8.91995 2.30383 0.451822
42 59 oh 276 11.0424 17.1592 -6.11686 0.466936
43 59 oh 1590 11.0003 21.2679 -10.2677 0.368327
44 59 oh 2665 10.8872 15.7601 -4.87297 0.489892
45 59 oh 3121 10.8408 20.7715 -9.93072 0.442538
46 59 oh 2835 10.7061 15.5328 -4.82667 0.506371
47 59 oh 2399 10.4885 22.5004 -12.0118 0.426895
48 59 oh 888 9.60093 24.5194 -14.9184 0.440298
49 59 oh 2010 9.48409 17.8114 -8.3273 0.442909
50 59 oh 120 9.43429 19.8288 -10.3946 0.374873
51 59 oh 1274 8.8007 18.4098 -9.60905 0.465875
52 59 oh 872 7.26605 6.91529 0.350757 0.463556
53 59 oh 63 5.80469 10.9779 -5.17323 0.448945
54 59 oh 1766 5.77301 14.1315 -8.35849 0.424352
55 59 oh 2632 5.17401 16.6661 -11.4921 0.481212
56 59 oh 1643 3.44173 9.91547 -6.47374 0.411082
57 59 oh 1386 2.29641 7.96365 -5.66724 0.487048
58 59 oh 2051 1.11025 19.9789 -18.8686 0.362767
59 59 oh 2252 -4.2769 2.7524 -7.02929 0.426927
1 55 md 1195 40.5344 17.5991 22.9353 0.522664
2 55 md 40 39.5288 17.0022 22.5266 0.58239
3 55 md 768 37.8062 21.0651 16.7411 0.521748
4 55 md 2199 36.9275 21.8992 15.0283 0.59235
5 55 md 2377 32.7323 18.6848 14.0474 0.532119
6 55 md 190 31.942 20.2199 11.7221 0.515659
7 55 md 1626 27.8995 18.7721 9.12737 0.488519
8 55 md 1893 27.5506 24.5949 2.95567 0.533111
9 55 md 166 25.9071 19.8892 6.01793 0.537781
10 55 md 449 25.7171 22.7501 2.96702 0.542676
11 55 md 836 24.6524 17.4179 7.2344 0.559831
12 55 md 1111 24.489 34.5252 -10.0362 0.423932
13 55 md 2016 23.9104 11.5193 12.3911 0.484006
14 55 md 2528 23.7838 8.18908 15.5948 0.4664
15 55 md 287 23.556 10.9917 12.5643 0.501141
16 55 md 2079 23.5015 21.3628 2.13869 0.475779
17 55 md 2534 23.1029 15.5518 7.55105 0.517597
18 55 md 379 22.1079 19.4918 2.61604 0.434714
19 55 md 1884 22.0564 20.3512 1.70513 0.439097
20 55 md 1727 21.9155 8.57633 13.3392 0.557916
21 55 md 7 21.4468 12.8638 8.58302 0.504373
22 55 md 75 21.4198 21.4896 -0.0698227 0.465439
23 55 md 888 20.9616 20.1582 0.803336 0.478208
24 55 md 2641 20.8986 5.07237 15.8263 0.477134
25 55 md 1511 20.6953 -4.74795 25.4433 0.527994
26 55 md 2866 20.5795 7.66423 12.9153 0.547128
27 55 md 229 20.2869 38.5575 -18.2706 0.482045
28 55 md 527 17.8187 14.1633 3.65539 0.528827
29 55 md 134 15.9621 29.017 -13.0549 0.420886
30 55 md 1748 15.7391 18.4112 -2.6721 0.411566
31 55 md 1980 15.5186 20.8753 -5.35669 0.500348
32 55 md 752 15.3178 15.9045 -0.586787 0.488304
33 55 md 1230 14.7886 14.0233 0.765333 0.433412
34 55 md 1418 14.6641 19.898 -5.2339 0.485897
35 55 md 2849 13.7858 14.0451 -0.259233 0.412771
36 55 md 1656 13.4795 13.9751 -0.495606 0.417787
37 55 md 2053 12.9486 21.5805 -8.63185 0.44367
38 55 md 339 12.9004 21.2817 -8.38126 0.492578
39 55 md 1446 12.7988 31.4077 -18.6089 0.414369
40 55 md 1886 12.6584 30.7338 -18.0753 0.390834
41 55 md 1168 12.5112 17.1567 -4.64545 0.511744
42 55 md 303 11.9224 17.8598 -5.9374 0.427665
43 55 md 53 11.3629 13.5214 -2.15849 0.443466
44 55 md 2483 11.2799 12.7549 -1.47501 0.502413
45 55 md 614 10.9224 27.3825 -16.4601 0.408347
46 55 md 467 10.8559 16.4226 -5.5667 0.510887
47 55 md 1389 10.4761 24.7675 -14.2913 0.418081
48 55 md 1719 9.93943 29.72 -19.7805 0.460204
49 55 md 686 9.86892 34.0916 -24.2227 0.405297
50 55 md 2546 9.59762 13.1334 -3.53582 0.452742
51 55 md 2537 8.80192 11.9763 -3.17438 0.463524
52 55 md 1933 6.50178 26.5839 -20.0821 0.437616
53 55 md 1640 5.95189 1.26466 4.68723 0.454988
54 55 md 2234 4.7429 32.0952 -27.3523 0.381571
55 55 md 203 -1.87537 9.61134 -11.4867 0.395111
1 48 co 399 48.5697 6.64104 41.9286 0.646447
2 48 co 207 36.793 13.7087 23.0842 0.630291
3 48 co 1158 35.6508 7.37693 28.2739 0.564153
4 48 co 233 32.5611 30.5336 2.02756 0.523621
5 48 co 1619 32.2731 23.8473 8.42576 0.527589
6 48 co 1939 31.605 6.01861 25.5864 0.497543
7 48 co 1332 31.0229 -5.36029 36.3832 0.596088
8 48 co 1361 30.2827 9.83498 20.4477 0.525132
9 48 co 2164 30.0582 9.7305 20.3277 0.500378
10 48 co 1583 28.7593 2.69893 26.0604 0.577475
11 48 co 2275 27.5694 27.1265 0.442976 0.47175
12 48 co 1777 26.6184 16.9061 9.71231 0.579932
13 48 co 4 24.7221 16.4018 8.3203 0.455593
14 48 co 2711 23.7588 9.0407 14.7181 0.556217
15 48 co 159 23.1223 -0.167259 23.2896 0.523904
16 48 co 1584 22.4504 6.02058 16.4299 0.578798
17 48 co 1348 22.2132 13.5613 8.65195 0.498583
18 48 co 2226 21.7053 0.587822 21.1175 0.561508
19 48 co 662 19.3519 25.0719 -5.71995 0.422902
20 48 co 1552 18.8337 6.70589 12.1278 0.534864
21 48 co 2240 17.1023 24.0462 -6.94389 0.463719
22 48 co 2410 16.5329 8.18888 8.34404 0.510488
23 48 co 1157 15.7032 10.9701 4.73316 0.482804
24 48 co 2400 15.3915 23.3395 -7.94806 0.468915
25 48 co 2083 15.3713 18.9227 -3.55138 0.451436
26 48 co 1377 14.5712 21.9673 -7.39608 0.464569
27 48 co 1515 14.0042 17.0747 -3.0705 0.475907
28 48 co 1303 13.5207 24.6735 -11.1528 0.516629
29 48 co 1789 11.9918 24.9295 -12.9377 0.441138
30 48 co 2259 11.884 26.7421 -14.8581 0.503874
31 48 co 1245 11.4403 20.0351 -8.59477 0.452475
32 48 co 1410 11.3206 14.5081 -3.1875 0.459184
33 48 co 1987 11.2693 31.8868 -20.6176 0.553571
34 48 co 2859 10.8275 15.8989 -5.07141 0.504535
35 48 co 2249 10.5478 26.6323 -16.0845 0.39692
36 48 co 1339 10.4888 25.7821 -15.2933 0.469482
37 48 co 2972 10.2097 28.6317 -18.422 0.504157
38 48 co 1408 9.86006 11.1354 -1.27537 0.504535
39 48 co 2996 8.03342 19.6784 -11.645 0.4726
40 48 co 1357 7.60385 35.2037 -27.5998 0.415438
41 48 co 1691 4.88787 9.11084 -4.22297 0.523054
42 48 co 2250 4.86353 16.3596 -11.4961 0.458806
43 48 co 2036 1.95582 23.2913 -21.3355 0.501417
44 48 co 1977 1.91559 15.716 -13.8004 0.521731
45 48 co 443 0.366821 17.8404 -17.4735 0.39503
46 48 co 2261 -0.338212 24.3817 -24.7199 0.413454
47 48 co 1799 -1.06422 34.8427 -35.9069 0.459373
48 48 co 2945 -3.46897 26.639 -30.1079 0.441988
1 60 ct 694 51.2924 10.4047 40.8878 0.560702
2 60 ct 2877 47.5881 13.4042 34.1839 0.527964
3 60 ct 121 47.1896 8.28233 38.9073 0.632378
4 60 ct 175 42.6279 5.2054 37.4225 0.590092
5 60 ct 1073 39.332 22.8374 16.4946 0.575211
6 60 ct 1100 38.9061 14.9876 23.9185 0.589658
7 60 ct 716 38.8168 9.50193 29.3149 0.558656
8 60 ct 178 32.8256 32.4191 0.406471 0.482763
9 60 ct 20 31.2986 23.1204 8.17826 0.527096
10 60 ct 558 29.9801 30.4537 -0.473572 0.437004
11 60 ct 241 29.0602 10.9889 18.0712 0.467014
12 60 ct 126 28.6561 28.3521 0.30398 0.55475
13 60 ct 61 27.5044 12.6972 14.8072 0.539063
14 60 ct 236 26.6578 17.7875 8.87024 0.502914
15 60 ct 2170 25.7603 20.5589 5.20137 0.440786
16 60 ct 1155 24.9979 14.1846 10.8133 0.562996
17 60 ct 549 23.6164 22.701 0.915378 0.472594
18 60 ct 1902 23.2304 14.99 8.24038 0.476252
19 60 ct 2228 23.2236 30.1375 -6.91387 0.491381
20 60 ct 743 23.1707 15.9236 7.24704 0.496528
21 60 ct 663 21.7628 28.7756 -7.01281 0.46627
22 60 ct 177 21.5735 17.5663 4.00721 0.553075
23 60 ct 157 21.4491 22.4261 -0.976977 0.465154
24 60 ct 335 20.7506 13.4314 7.31917 0.476625
25 60 ct 230 19.4294 15.5446 3.88475 0.542659
26 60 ct 195 18.2261 17.3432 0.882911 0.457155
27 60 ct 2168 18.0087 20.6374 -2.62869 0.486917
28 60 ct 639 17.5481 32.9554 -15.4074 0.463418
29 60 ct 95 17.0802 9.45823 7.62194 0.539249
30 60 ct 1991 17.0282 38.4415 -21.4134 0.399678
31 60 ct 1124 16.8495 15.662 1.18748 0.490079
32 60 ct 228 16.236 10.9664 5.26959 0.485243
33 60 ct 48 16.1207 10.3973 5.72332 0.534288
34 60 ct 2265 15.8963 17.1075 -1.21121 0.460503
35 60 ct 2067 15.7381 21.3193 -5.58122 0.467014
36 60 ct 839 15.4986 15.8042 -0.305618 0.520895
37 60 ct 1592 15.3528 10.0644 5.28836 0.547991
38 60 ct 2523 15.1838 14.0592 1.12462 0.494916
39 60 ct 176 14.2823 11.5631 2.71924 0.514757
40 60 ct 2836 13.7689 25.3669 -11.598 0.37903
41 60 ct 1699 13.6658 18.6355 -4.96965 0.485367
42 60 ct 433 13.1859 8.90113 4.28474 0.506138
43 60 ct 2785 12.2892 23.8766 -11.5874 0.451575
44 60 ct 1740 11.4124 11.9298 -0.517407 0.46999
45 60 ct 2862 11.3563 21.5935 -10.2371 0.466704
46 60 ct 1665 11.3473 35.3622 -24.0149 0.425285
47 60 ct 1687 10.3445 28.4295 -18.085 0.444754
48 60 ct 237 10.2487 29.9295 -19.6808 0.488157
49 60 ct 500 10.1269 14.3991 -4.27221 0.466146
50 60 ct 181 10.0184 24.7793 -14.7609 0.46317
51 60 ct 1493 9.76372 12.0148 -2.25107 0.50279
52 60 ct 999 9.71353 14.2262 -4.5127 0.46162
53 60 ct 173 9.07977 26.4187 -17.3389 0.485181
54 60 ct 571 8.86189 27.7536 -18.8917 0.482949
55 60 ct 1071 7.40949 21.2152 -13.8057 0.481275
56 60 ct 1403 6.82397 12.3513 -5.52738 0.53435
57 60 ct 2064 6.4152 17.2868 -10.8716 0.519655
58 60 ct 1784 2.29408 21.4601 -19.166 0.451885
59 60 ct 3104 0.697236 44.4872 -43.79 0.37314
60 60 ct 2497 -4.57284 31.1217 -35.6946 0.434152
1 49 roc 188 43.6441 23.9811 19.6629 0.556008
2 49 roc 1507 39.6698 17.459 22.2108 0.583165
3 49 roc 191 32.1049 16.7748 15.3301 0.550935
4 49 roc 1728 30.444 24.6914 5.75262 0.513854
5 49 roc 174 29.8086 22.1572 7.65142 0.479398
6 49 roc 1126 29.2305 0.680291 28.5502 0.516046
7 49 roc 610 25.419 15.37 10.0489 0.530404
8 49 roc 1241 24.231 18.2742 5.95686 0.538713
9 49 roc 1765 24.085 13.3722 10.7127 0.55744
10 49 roc 316 23.7138 19.491 4.22288 0.425208
11 49 roc 173 23.5314 17.398 6.1334 0.500042
12 49 roc 1503 23.3905 16.8805 6.51003 0.549603
13 49 roc 2791 23.3472 26.4044 -3.05722 0.434996
14 49 roc 3015 23.1889 19.8779 3.31097 0.535681
15 49 roc 772 22.8282 11.2191 11.6091 0.422275
16 49 roc 340 22.585 7.71742 14.8676 0.522387
17 49 roc 522 20.086 22.3947 -2.30864 0.45245
18 49 roc 424 19.6697 13.9056 5.76413 0.54115
19 49 roc 229 18.9818 6.24179 12.74 0.528377
20 49 roc 1626 18.0239 13.3948 4.62911 0.444386
21 49 roc 1559 17.9314 26.6005 -8.66918 0.481431
22 49 roc 578 17.565 27.8282 -10.2633 0.423785
23 49 roc 250 17.5076 10.9685 6.53901 0.491954
24 49 roc 378 17.4045 9.72317 7.68134 0.491298
25 49 roc 1591 16.8492 22.4074 -5.55817 0.509651
26 49 roc 2053 16.316 15.443 0.873005 0.489046
27 49 roc 73 16.3082 26.4381 -10.1299 0.447494
28 49 roc 2999 15.6643 16.1952 -0.530854 0.438614
29 49 roc 3003 15.6071 12.9312 2.67581 0.486585
30 49 roc 1551 13.4998 31.9547 -18.4549 0.427059
31 49 roc 809 13.3146 17.467 -4.15233 0.524118
32 49 roc 2228 13.0657 27.7546 -14.689 0.436595
33 49 roc 211 12.9647 8.12908 4.83561 0.485926
34 49 roc 2609 12.9357 16.907 -3.97134 0.473153
35 49 roc 145 12.1214 20.8777 -8.75627 0.449603
36 49 roc 1713 12.0569 17.753 -5.69603 0.468275
37 49 roc 2340 11.9289 11.6565 0.272361 0.466436
38 49 roc 1246 11.61 13.6437 -2.03368 0.444012
39 49 roc 639 11.4626 15.3785 -3.9159 0.484291
40 49 roc 2624 9.61793 14.7288 -5.1109 0.43546
41 49 roc 3057 8.84014 26.7409 -17.9008 0.371907
42 49 roc 3044 8.81849 23.9206 -15.1021 0.444201
43 49 roc 1511 7.81815 15.6155 -7.79733 0.482831
44 49 roc 1585 7.43676 5.97567 1.46109 0.478609
45 49 roc 1450 5.55733 16.457 -10.8997 0.387933
46 49 roc 1547 5.20381 19.6234 -14.4196 0.378976
47 49 roc 1518 4.85576 23.9297 -19.0739 0.396296
48 49 roc 771 2.13402 12.3276 -10.1936 0.431245
49 49 roc 1405 -1.05891 15.6969 -16.7558 0.464566
1 52 fl 103 47.4899 7.30672 40.1832 0.608943
2 52 fl 79 40.772 7.62948 33.1425 0.535855
3 52 fl 1144 36.5386 11.5203 25.0183 0.617088
4 52 fl 179 34.9017 15.4683 19.4334 0.536976
5 52 fl 744 33.1933 7.78636 25.4069 0.561434
6 52 fl 25 31.2281 16.6655 14.5626 0.591986
7 52 fl 501 30.9167 10.9549 19.9619 0.557246
8 52 fl 425 30.1376 24.4434 5.6942 0.471475
9 52 fl 1649 28.477 11.9296 16.5474 0.502419
10 52 fl 238 28.4533 33.2568 -4.80349 0.511005
11 52 fl 180 24.565 19.4233 5.14171 0.519504
12 52 fl 233 23.9555 13.9618 9.99372 0.495383
13 52 fl 1341 23.7259 27.0367 -3.31084 0.497048
14 52 fl 2885 22.5805 17.5837 4.99684 0.509884
15 52 fl 665 20.9785 11.1063 9.8722 0.529676
16 52 fl 1251 20.9023 19.0514 1.85092 0.485872
17 52 fl 2564 20.659 10.762 9.89701 0.543522
18 52 fl 2383 20.5687 10.6124 9.95628 0.462363
19 52 fl 1875 18.9726 14.7652 4.20737 0.507391
20 52 fl 2152 17.8761 12.3389 5.53725 0.490863
21 52 fl 1902 17.6011 16.1631 1.43798 0.518543
22 52 fl 1557 17.4178 15.326 2.09182 0.561036
23 52 fl 168 17.2552 26.0676 -8.81238 0.521048
24 52 fl 1390 17.2139 23.4525 -6.23858 0.401277
25 52 fl 108 16.6563 17.1918 -0.535462 0.478842
26 52 fl 59 16.5454 16.7468 -0.201399 0.457305
27 52 fl 1922 15.9529 10.0889 5.86405 0.436502
28 52 fl 21 15.2488 27.3961 -12.1473 0.429098
29 52 fl 1345 14.9804 15.6471 -0.666672 0.493056
30 52 fl 2757 14.6294 21.5518 -6.92245 0.44371
31 52 fl 2422 14.5917 25.0336 -10.4418 0.484635
32 52 fl 801 13.9466 24.1233 -10.1767 0.412998
33 52 fl 2569 13.9325 13.3676 0.564941 0.475009
34 52 fl 945 13.7542 9.60633 4.14785 0.510441
35 52 fl 1612 13.4913 25.5877 -12.0964 0.434952
36 52 fl 2884 13.2294 22.1369 -8.90754 0.489963
37 52 fl 1616 12.8885 33.2356 -20.3471 0.490637
38 52 fl 1592 12.2581 17.7057 -5.4476 0.442509
39 52 fl 386 12.034 22.0532 -10.0192 0.42535
40 52 fl 1523 11.8825 3.49955 8.38297 0.464451
41 52 fl 408 11.6851 16.3215 -4.63642 0.486405
42 52 fl 2425 11.4989 7.14224 4.35663 0.496013
43 52 fl 2023 10.9802 20.616 -9.63582 0.466411
44 52 fl 2797 8.71842 25.125 -16.4066 0.410145
45 52 fl 1889 8.31611 15.4065 -7.09036 0.495064
46 52 fl 1876 7.87935 12.9242 -5.04483 0.503552
47 52 fl 1543 7.80508 18.3302 -10.5252 0.465762
48 52 fl 1885 5.61526 18.2053 -12.5901 0.427408
49 52 fl 1284 5.52718 23.5852 -18.058 0.378993
50 52 fl 1029 3.21397 37.7889 -34.5749 0.402661
51 52 fl 2916 -0.869478 23.8252 -24.6947 0.448786
52 52 fl 86 -2.21696 21.7012 -23.9182 0.453765
1 61 kc 1806 39.8654 9.11895 30.7465 0.630687
2 61 kc 835 36.7924 5.48403 31.3084 0.544165
3 61 kc 1939 36.1115 1.92199 34.1895 0.588538
4 61 kc 1997 34.5591 18.9688 15.5903 0.557843
5 61 kc 269 31.0519 7.28287 23.769 0.480802
6 61 kc 1981 30.1999 12.5737 17.6262 0.535421
7 61 kc 1108 29.9421 14.6886 15.2535 0.547466
8 61 kc 935 27.9584 8.26374 19.6947 0.544162
9 61 kc 1448 27.3312 1.27183 26.0594 0.496233
10 61 kc 2164 27.0132 15.8635 11.1497 0.549288
11 61 kc 1208 25.3528 25.2381 0.114769 0.498593
12 61 kc 1785 23.9053 2.91377 20.9915 0.438102
13 61 kc 1777 23.8492 21.6504 2.19884 0.502826
14 61 kc 1827 23.7172 22.9921 0.725066 0.337762
15 61 kc 1986 23.3047 9.83342 13.4713 0.5086
16 61 kc 2410 22.6202 9.07789 13.5423 0.542752
17 61 kc 525 22.4068 23.3533 -0.946522 0.502104
18 61 kc 1775 22.3962 12.2265 10.1697 0.493545
19 61 kc 937 20.0865 26.1752 -6.08873 0.410389
20 61 kc 1730 19.9329 -1.24902 21.182 0.489514
21 61 kc 1985 19.8185 8.27296 11.5455 0.540325
22 61 kc 1094 19.3023 5.01517 14.2871 0.492764
23 61 kc 1982 19.1645 13.5391 5.62534 0.591963
24 61 kc 1764 18.6153 2.27754 16.3378 0.553634
25 61 kc 2366 18.0543 31.9787 -13.9244 0.510501
26 61 kc 1800 17.2088 24.9953 -7.78652 0.504144
27 61 kc 1825 16.1765 20.9599 -4.78342 0.496396
28 61 kc 2201 16.0283 35.101 -19.0728 0.432585
29 61 kc 2874 15.8302 16.2921 -0.461924 0.490957
30 61 kc 1810 15.7056 11.0075 4.69812 0.472816
31 61 kc 2345 15.5414 17.5654 -2.02393 0.495084
32 61 kc 1802 15.144 18.9532 -3.80921 0.480733
33 61 kc 931 14.533 29.6693 -15.1363 0.474964
34 61 kc 1776 14.2853 20.6854 -6.40009 0.516442
35 61 kc 2167 14.2307 9.11924 5.11145 0.475504
36 61 kc 1996 13.7879 2.85948 10.9284 0.580096
37 61 kc 1992 12.7378 18.0906 -5.35282 0.484797
38 61 kc 938 12.735 12.2086 0.526481 0.484248
39 61 kc 2799 12.6263 44.4617 -31.8354 0.468969
40 61 kc 2001 12.0712 13.714 -1.6428 0.526264
41 61 kc 1769 12.0104 21.7988 -9.78841 0.488677
42 61 kc 2894 11.9806 18.0836 -6.10303 0.500029
43 61 kc 2353 11.7636 26.9371 -15.1735 0.483413
44 61 kc 1737 11.5084 -1.58796 13.0963 0.524754
45 61 kc 1763 11.4758 12.3006 -0.824805 0.471704
46 61 kc 2560 10.8397 15.0123 -4.17259 0.398222
47 61 kc 1098 10.7942 20.4299 -9.6357 0.443849
48 61 kc 2177 10.7595 4.64685 6.11261 0.563143
49 61 kc 2346 9.77563 29.676 -19.9003 0.344882
50 61 kc 1710 9.18276 -1.28976 10.4725 0.571359
51 61 kc 2334 9.02649 27.7162 -18.6897 0.486504
52 61 kc 2335 8.28686 4.82184 3.46502 0.471105
53 61 kc 1805 7.33787 25.2708 -17.9329 0.452221
54 61 kc 1847 5.09031 29.0703 -23.98 0.468819
55 61 kc 1994 2.77666 25.6997 -22.9231 0.444584
56 61 kc 537 2.51291 11.9701 -9.45716 0.502738
57 61 kc 2457 -0.544046 34.748 -35.2921 0.410131
58 61 kc 1782 -0.757197 24.2376 -24.9948 0.454937
59 61 kc 1984 -1.31875 13.4341 -14.7528 0.475659
60 61 kc 2357 -1.64948 27.4938 -29.1433 0.469459
61 61 kc 2008 -12.3133 16.4633 -28.7765 0.37349
1 59 on 188 54.8454 20.1327 34.7127 0.606606
2 59 on 2056 48.8918 8.98663 39.9052 0.619678
3 59 on 1114 34.516 11.1734 23.3426 0.531504
4 59 on 2386 33.961 2.10167 31.8593 0.621064
5 59 on 610 33.2707 17.1356 16.1352 0.570747
6 59 on 1503 33.0993 12.0785 21.0208 0.541568
7 59 on 1126 32.6056 17.8517 14.754 0.521051
8 59 on 1141 31.1227 3.41049 27.7122 0.522872
9 59 on 772 28.7774 31.3252 -2.54786 0.493484
10 59 on 2625 28.3546 22.3965 5.95817 0.517007
11 59 on 2200 27.7983 2.30793 25.4904 0.515181
12 59 on 1241 25.869 12.2174 13.6517 0.512651
13 59 on 854 25.4401 21.5575 3.8826 0.57824
14 59 on 2361 25.0423 10.3198 14.7225 0.478506
15 59 on 1310 23.5855 10.9669 12.6186 0.544426
16 59 on 886 23.5667 13.7587 9.80799 0.511241
17 59 on 1305 22.5284 27.9254 -5.39696 0.517104
18 59 on 1244 21.4576 36.9551 -15.4975 0.491933
19 59 on 1219 21.2337 8.90821 12.3255 0.577973
20 59 on 3117 21.0902 17.1868 3.90336 0.477793
21 59 on 1006 20.9014 20.0291 0.872234 0.540557
22 59 on 781 20.1785 29.9166 -9.73807 0.465813
23 59 on 2852 19.8415 16.0344 3.80707 0.506237
24 59 on 2809 19.4044 25.2875 -5.88309 0.546606
25 59 on 2505 19.0277 12.0269 7.00082 0.547673
26 59 on 2166 18.9514 26.5083 -7.55683 0.48297
27 59 on 2198 18.9183 14.3635 4.55479 0.457442
28 59 on 1535 18.0582 8.27375 9.78445 0.557943
29 59 on 1334 17.9872 5.18729 12.8 0.546712
30 59 on 2076 16.8631 17.7665 -0.903471 0.497861
31 59 on 2935 16.7217 37.1408 -20.4191 0.483738
32 59 on 1605 16.4245 22.4556 -6.03112 0.526173
33 59 on 1846 15.7142 27.5082 -11.7939 0.443499
34 59 on 1075 15.0236 14.0354 0.988181 0.491583
35 59 on 2013 14.5088 15.0915 -0.582691 0.535436
36 59 on 2994 14.2357 2.34451 11.8911 0.413479
37 59 on 677 14.1976 2.81744 11.3801 0.485846
38 59 on 1518 13.8889 25.2581 -11.3692 0.511929
39 59 on 1559 13.7832 22.356 -8.57278 0.480471
40 59 on 1547 13.696 13.6963 -0.000324249 0.529993
41 59 on 2626 13.5433 28.2256 -14.6823 0.443538
42 59 on 1404 13.5305 21.6218 -8.09133 0.520131
43 59 on 1312 12.2419 15.9158 -3.67384 0.465242
44 59 on 919 11.6764 36.4368 -24.7604 0.475998
45 59 on 1835 10.7791 6.87518 3.90387 0.503955
46 59 on 1514 10.7266 32.29 -21.5634 0.421039
47 59 on 1558 10.6766 31.0299 -20.3533 0.41148
48 59 on 2634 8.86438 22.7321 -13.8678 0.44543
49 59 on 1325 8.59273 13.6599 -5.0672 0.502041
50 59 on 2185 8.50867 29.1764 -20.6678 0.492032
51 59 on 771 7.85468 7.58999 0.264695 0.524004
52 59 on 1482 7.19423 11.0677 -3.87344 0.504039
53 59 on 907 6.93794 13.1205 -6.18259 0.435557
54 59 on 843 5.35 31.3512 -26.0012 0.432592
55 59 on 865 5.15013 14.3252 -9.17505 0.448685
56 59 on 1053 3.10232 38.5109 -35.4085 0.408296
57 59 on 2670 1.63005 33.2534 -31.6234 0.420281
58 59 on 1246 1.47727 38.4821 -37.0049 0.39202
59 59 on 1815 1.03729 -7.78935 8.82664 0.440189
1 33 hi 192 35.1158 15.1916 19.9242 0.567298
2 33 hi 2348 31.9748 9.61963 22.3552 0.561263
3 33 hi 368 29.2539 9.66567 19.5883 0.558528
4 33 hi 1138 24.5903 10.3091 14.2812 0.561231
5 33 hi 2445 22.8143 10.3831 12.4311 0.524666
6 33 hi 359 22.2934 11.1106 11.1827 0.534871
7 33 hi 2438 20.3046 17.4779 2.82669 0.491933
8 33 hi 2090 19.5264 21.7943 -2.26793 0.51533
9 33 hi 2439 18.1916 11.501 6.69061 0.521574
10 33 hi 2932 18.1368 19.7471 -1.61032 0.473504
11 33 hi 2853 17.291 17.536 -0.245072 0.484909
12 33 hi 2453 17.2691 6.0205 11.2486 0.545651
13 33 hi 2455 17.002 22.9552 -5.95329 0.485173
14 33 hi 1859 15.7459 8.77898 6.96692 0.462752
15 33 hi 2813 15.5221 17.3637 -1.84167 0.480287
16 33 hi 3105 15.2299 20.6108 -5.38085 0.495737
17 33 hi 2467 14.6571 15.3017 -0.64459 0.467096
18 33 hi 2444 14.4159 18.3246 -3.90868 0.482846
19 33 hi 2504 12.7882 5.06072 7.72747 0.502012
20 33 hi 2628 12.7306 16.3105 -3.57992 0.438247
21 33 hi 2441 12.6802 8.09349 4.58671 0.532189
22 33 hi 2454 12.491 22.7894 -10.2984 0.489278
23 33 hi 1834 11.1243 12.8757 -1.75139 0.45151
24 33 hi 2460 10.8858 12.3773 -1.49155 0.457608
25 33 hi 2459 10.2913 25.9196 -15.6283 0.420825
26 33 hi 2896 10.1623 10.4097 -0.247433 0.457083
27 33 hi 2077 10.1499 11.6516 -1.5017 0.505475
28 33 hi 2443 9.10743 18.8433 -9.73589 0.50441
29 33 hi 2437 8.3856 14.865 -6.47938 0.422513
30 33 hi 2477 6.01409 27.5216 -21.5075 0.385416
31 33 hi 2465 5.68256 22.1569 -16.4744 0.418169
32 33 hi 2629 5.1546 21.577 -16.4224 0.396557
33 33 hi 3008 -0.241073 13.5014 -13.7424 0.375636
1 47 is 1574 31.6449 15.6054 16.0395 0.576319
2 47 is 3076 30.2341 12.3631 17.871 0.517887
3 47 is 1690 28.4349 16.2058 12.229 0.557848
4 47 is 1957 26.8164 21.1068 5.70964 0.532126
5 47 is 1657 26.2531 6.76499 19.4881 0.5572
6 47 is 2630 26.1552 7.00625 19.149 0.614272
7 47 is 1946 25.3529 13.8695 11.4834 0.537759
8 47 is 1573 23.327 16.0975 7.22943 0.540697
9 47 is 3052 23.1626 7.15735 16.0053 0.561745
10 47 is 3075 21.9892 8.36332 13.6259 0.56227
11 47 is 3063 21.1797 11.378 9.80169 0.53532
12 47 is 2217 20.2281 16.9074 3.32067 0.476745
13 47 is 2230 20.0976 17.3864 2.71112 0.515412
14 47 is 2214 19.1114 10.7271 8.38423 0.493592
15 47 is 3089 18.9627 4.57007 14.3926 0.49224
16 47 is 2231 18.8768 3.79721 15.0796 0.565758
17 47 is 2215 18.1006 11.6247 6.47582 0.52097
18 47 is 2669 17.6338 3.99099 13.6428 0.513814
19 47 is 3065 16.7632 11.3665 5.39674 0.501634
20 47 is 2650 16.5843 18.0731 -1.48888 0.519738
21 47 is 1576 16.5197 17.2017 -0.681967 0.483943
22 47 is 3077 14.949 20.4076 -5.45861 0.498789
23 47 is 3073 14.8494 16.3542 -1.50471 0.511566
24 47 is 1943 13.8066 16.325 -2.5184 0.441771
25 47 is 1577 13.664 5.41902 8.24499 0.53494
26 47 is 1955 13.57 13.2845 0.285538 0.473377
27 47 is 1579 13.1509 18.0036 -4.85276 0.472329
28 47 is 3064 13.0044 13.0803 -0.075891 0.567037
29 47 is 3083 12.9951 5.45305 7.54204 0.518877
30 47 is 2211 12.57 8.22436 4.34568 0.476168
31 47 is 2212 12.3639 7.96508 4.39881 0.524481
32 47 is 1942 12.2817 24.6835 -12.4018 0.493239
33 47 is 3034 11.7179 15.7433 -4.02544 0.49554
34 47 is 3088 10.4222 26.8306 -16.4084 0.456685
35 47 is 1580 9.15304 27.9962 -18.8431 0.400065
36 47 is 1937 8.18072 12.6522 -4.47147 0.510534
37 47 is 1952 8.17979 15.705 -7.52526 0.449185
38 47 is 1954 7.6572 17.3905 -9.7333 0.456133
39 47 is 3092 7.6207 11.2945 -3.67381 0.469941
40 47 is 3094 6.52387 19.8536 -13.3297 0.435078
41 47 is 1578 6.36967 19.8278 -13.4581 0.45898
42 47 is 3086 5.78405 21.7809 -15.9969 0.479974
43 47 is 1944 5.38622 31.6774 -26.2911 0.421017
44 47 is 2672 4.40175 15.7414 -11.3397 0.473038
45 47 is 2216 4.35853 20.5881 -16.2296 0.482464
46 47 is 3087 2.67523 18.3532 -15.6779 0.432224
47 47 is 3084 -3.48984 30.2132 -33.7031 0.39474
1 48 nv 254 40.492 16.9224 23.5696 0.623879
2 48 nv 987 38.0004 15.2481 22.7523 0.547252
3 48 nv 3006 34.1366 1.40399 32.7326 0.566695
4 48 nv 1622 33.261 11.2516 22.0094 0.588692
5 48 nv 973 32.7311 23.3403 9.39079 0.550056
6 48 nv 1538 29.9693 5.73298 24.2363 0.573302
7 48 nv 2543 28.5287 3.45796 25.0707 0.539407
8 48 nv 330 27.9633 15.7389 12.2244 0.557534
9 48 nv 585 27.8195 14.5527 13.2669 0.541918
10 48 nv 1266 27.0695 2.85148 24.2181 0.593389
11 48 nv 687 26.8724 12.3967 14.4757 0.585967
12 48 nv 2984 24.3858 13.081 11.3048 0.518059
13 48 nv 1572 23.7673 17.4789 6.28845 0.50872
14 48 nv 2339 23.0666 20.9257 2.14085 0.50417
15 48 nv 2061 22.2876 18.8024 3.48518 0.525604
16 48 nv 980 21.4405 15.0995 6.34093 0.50368
17 48 nv 1669 21.0825 34.7829 -13.7004 0.534196
18 48 nv 294 20.4782 20.379 0.0991966 0.442993
19 48 nv 3009 20.2296 14.7082 5.52131 0.510833
20 48 nv 1197 17.8309 18.4147 -0.58382 0.506957
21 48 nv 1540 17.554 22.0544 -4.50039 0.534006
22 48 nv 1013 17.3316 22.0441 -4.71244 0.496117
23 48 nv 1780 16.9735 25.4633 -8.48978 0.48439
24 48 nv 8 16.7273 7.2752 9.4521 0.482553
25 48 nv 3011 16.3175 21.2974 -4.97989 0.464359
26 48 nv 1631 15.6025 29.169 -13.5665 0.459319
27 48 nv 2037 14.6232 28.3179 -13.6947 0.445663
28 48 nv 988 14.4058 19.9929 -5.58712 0.455841
29 48 nv 473 13.3924 7.75364 5.63874 0.498812
30 48 nv 2057 13.2301 19.7603 -6.53021 0.499216
31 48 nv 2484 13.2153 13.5965 -0.38123 0.488953
32 48 nv 1548 12.4805 19.1253 -6.64476 0.51395
33 48 nv 3021 11.9738 17.5752 -5.60143 0.501451
34 48 nv 2993 11.7626 14.7148 -2.95221 0.503209
35 48 nv 1703 11.5322 15.6577 -4.12556 0.470587
36 48 nv 2069 10.8817 26.661 -15.7793 0.43663
37 48 nv 2034 10.7541 26.9791 -16.225 0.502235
38 48 nv 1160 10.5114 5.55051 4.96093 0.541703
39 48 nv 60 9.70666 17.3961 -7.68945 0.434763
40 48 nv 2485 8.74462 29.8264 -21.0818 0.421027
41 48 nv 1724 8.70762 28.903 -20.1954 0.460177
42 48 nv 2150 8.2446 26.3066 -18.062 0.423623
43 48 nv 2520 5.85559 23.3696 -17.514 0.438823
44 48 nv 522 5.40451 12.0834 -6.67887 0.460495
45 48 nv 1883 5.33226 20.2667 -14.9345 0.407787
46 48 nv 989 4.30557 23.2733 -18.9678 0.451646
47 48 nv 2139 3.38021 16.6298 -13.2496 0.430843
48 48 nv 362 1.63623 14.3873 -12.7511 0.480422
1 63 tx 704 39.4813 14.5526 24.9287 0.508908
2 63 tx 34 37.3649 5.42178 31.9431 0.529748
3 63 tx 624 36.3149 16.4033 19.9117 0.520057
4 63 tx 1421 36.299 15.3399 20.959 0.510327
5 63 tx 231 36.0453 13.2771 22.7682 0.561479
6 63 tx 2966 34.9673 19.776 15.1912 0.535188
7 63 tx 118 34.5175 12.707 21.8104 0.547499
8 63 tx 2587 33.5412 1.04327 32.4979 0.565829
9 63 tx 148 33.3532 32.0151 1.33808 0.487461
10 63 tx 1477 32.797 11.6404 21.1566 0.542571
11 63 tx 2157 31.0382 6.9161 24.1221 0.493845
12 63 tx 2468 29.2578 11.1877 18.0701 0.520584
13 63 tx 2745 28.9436 1.19363 27.7499 0.495465
14 63 tx 418 26.0371 -4.06242 30.0996 0.623568
15 63 tx 2991 24.7396 15.1508 9.58882 0.472668
16 63 tx 2585 23.6111 30.2601 -6.64893 0.482629
17 63 tx 3012 23.0446 11.177 11.8676 0.499514
18 63 tx 2979 22.3382 9.33949 12.9987 0.550265
19 63 tx 1801 22.055 14.2288 7.8262 0.514913
20 63 tx 2276 20.8693 15.3296 5.5397 0.512728
21 63 tx 922 20.581 18.272 2.30895 0.498854
22 63 tx 2833 20.0052 6.16469 13.8405 0.469332
23 63 tx 2936 19.5909 20.1142 -0.523339 0.451166
24 63 tx 2190 18.815 0.599901 18.2151 0.448872
25 63 tx 3080 18.7857 16.7049 2.08081 0.504102
26 63 tx 2072 18.6196 4.91311 13.7065 0.497478
27 63 tx 441 18.4276 9.48651 8.94105 0.608126
28 63 tx 1865 17.6466 18.2062 -0.559562 0.488539
29 63 tx 3029 16.6644 2.98791 13.6765 0.534446
30 63 tx 2737 15.6926 24.836 -9.14342 0.445592
31 63 tx 2938 14.6667 22.4533 -7.78667 0.418801
32 63 tx 57 14.2733 2.71865 11.5547 0.519452
33 63 tx 3028 14.091 11.8322 2.25878 0.548225
34 63 tx 434 13.8568 27.1128 -13.256 0.511702
35 63 tx 3016 13.1075 14.8365 -1.72891 0.429557
36 63 tx 1484 13.0224 33.5887 -20.5663 0.413697
37 63 tx 1818 12.8871 16.5831 -3.69601 0.499082
38 63 tx 1898 12.1093 23.9502 -11.8409 0.436211
39 63 tx 2880 10.6774 9.3769 1.3005 0.485451
40 63 tx 1867 10.5151 31.2635 -20.7484 0.484033
41 63 tx 2969 10.3613 22.4681 -12.1068 0.391938
42 63 tx 3103 9.72788 18.0203 -8.29242 0.445457
43 63 tx 1480 8.72593 5.59014 3.13579 0.518358
44 63 tx 2952 8.52678 13.9455 -5.41874 0.535674
45 63 tx 3071 8.20573 31.519 -23.3132 0.373907
46 63 tx 2843 8.20192 18.7276 -10.5257 0.460508
47 63 tx 2956 7.78828 22.1464 -14.3581 0.468458
48 63 tx 499 7.20118 7.738 -0.536823 0.428045
49 63 tx 2583 7.1302 15.2102 -8.08004 0.532299
50 63 tx 3035 6.31046 19.9995 -13.689 0.392103
51 63 tx 2582 6.23354 24.5966 -18.3631 0.541977
52 63 tx 1817 5.85541 20.6452 -14.7898 0.470333
53 63 tx 2664 4.67252 16.5806 -11.9081 0.447603
54 63 tx 653 3.97144 36.2441 -32.2726 0.386135
55 63 tx 2934 2.73151 4.92456 -2.19305 0.49572
56 63 tx 2613 2.20699 10.637 -8.43005 0.489754
57 63 tx 1429 0.914883 26.622 -25.7071 0.494117
58 63 tx 1255 0.35404 28.5118 -28.1577 0.402965
59 63 tx 2882 -0.333345 8.90251 -9.23585 0.465921
60 63 tx 2158 -0.576133 22.8122 -23.3883 0.417596
61 63 tx 2881 -0.72399 24.3171 -25.0411 0.447751
62 63 tx 2597 -2.32695 29.4137 -31.7406 0.408363
63 63 tx 1513 -5.7119 18.7144 -24.4263 0.47835
1 60 ca 399 53.8913 5.26321 48.6281 0.589569
2 60 ca 1717 40.7522 2.9988 37.7534 0.551493
3 60 ca 1382 38.3571 11.1279 27.2292 0.502173
4 60 ca 848 36.6786 5.73183 30.9468 0.5274
5 60 ca 207 35.9848 3.84369 32.1411 0.594766
6 60 ca 1388 34.2508 2.16774 32.083 0.60941
7 60 ca 1047 34.2333 14.2901 19.9432 0.497071
8 60 ca 597 32.3008 8.88823 23.4126 0.600529
9 60 ca 1726 28.3036 6.77101 21.5326 0.596088
10 60 ca 2404 26.0666 29.6702 -3.60361 0.466553
11 60 ca 1860 25.8713 20.1787 5.69262 0.472317
12 60 ca 294 25.1118 11.4871 13.6246 0.416289
13 60 ca 1661 24.072 1.72601 22.346 0.481481
14 60 ca 295 24.0465 9.74506 14.3014 0.516818
15 60 ca 1644 23.2954 -0.269569 23.565 0.590797
16 60 ca 687 22.3779 2.42487 19.9531 0.479403
17 60 ca 1682 20.7867 14.0238 6.76296 0.519274
18 60 ca 973 19.935 13.0559 6.87917 0.541194
19 60 ca 2174 19.764 30.5539 -10.7899 0.453326
20 60 ca 4 18.1733 15.946 2.22726 0.493103
21 60 ca 1515 17.5694 20.7478 -3.17837 0.463813
22 60 ca 330 16.7254 10.5181 6.20735 0.580593
23 60 ca 2429 16.3006 14.6342 1.6664 0.544785
24 60 ca 1759 16.2845 10.9791 5.30542 0.448129
25 60 ca 1197 16.0724 15.0671 1.00532 0.461451
26 60 ca 2658 16.0094 23.2217 -7.21228 0.457577
27 60 ca 1323 15.9136 8.01494 7.89866 0.449074
28 60 ca 702 15.7661 20.2929 -4.52687 0.543651
29 60 ca 606 15.5942 19.2765 -3.6823 0.481198
30 60 ca 2659 15.5701 19.4242 -3.85406 0.506897
31 60 ca 1160 15.3163 6.35216 8.96414 0.548942
32 60 ca 2637 14.8168 6.29953 8.51722 0.514078
33 60 ca 1148 14.6475 29.2267 -14.5792 0.484788
34 60 ca 1138 14.4893 9.01247 5.4768 0.537887
35 60 ca 599 14.4007 43.863 -29.4622 0.470805
36 60 ca 3001 14.0349 16.3719 -2.33703 0.497638
37 60 ca 580 12.7794 11.6357 1.14371 0.527211
38 60 ca 3020 11.4904 3.66275 7.82766 0.525605
39 60 ca 691 11.3798 10.6552 0.724597 0.551493
40 60 ca 995 10.3264 -3.64746 13.9739 0.469293
41 60 ca 696 9.54341 28.6788 -19.1354 0.48545
42 60 ca 1438 8.89675 22.5463 -13.6496 0.545918
43 60 ca 980 8.77871 33.6852 -24.9065 0.511432
44 60 ca 3120 8.70203 24.4425 -15.7405 0.397959
45 60 ca 362 7.34773 24.2284 -16.8807 0.424036
46 60 ca 1671 6.83274 24.121 -17.2883 0.455215
47 60 ca 589 6.50048 12.9711 -6.47064 0.469577
48 60 ca 1070 6.46711 32.8622 -26.3951 0.492725
49 60 ca 2584 5.87436 14.8927 -9.01832 0.474773
50 60 ca 1452 5.6875 3.3395 2.348 0.459845
51 60 ca 2496 4.73654 24.2008 -19.4643 0.493953
52 60 ca 2272 4.60309 35.8639 -31.2608 0.44624
53 60 ca 1836 4.59145 26.6221 -22.0307 0.371693
54 60 ca 3027 4.11706 13.7008 -9.58372 0.470994
55 60 ca 981 4.08269 40.3503 -36.2677 0.391912
56 60 ca 1702 2.16179 25.6473 -23.4855 0.458617
57 60 ca 867 1.26441 15.2003 -13.9359 0.41695
58 60 ca 2576 0.511068 8.4673 -7.95623 0.448318
59 60 ca 1692 0.00215901 41.5113 -41.5091 0.413171
60 60 ca 2919 -8.15576 13.7206 -21.8764 0.378685
1 64 wa 1983 39.3778 29.9866 9.39113 0.454998
2 64 wa 2471 35.9651 8.83619 27.1289 0.570308
3 64 wa 1425 33.9212 13.1069 20.8143 0.583804
4 64 wa 1318 31.3524 17.6619 13.6904 0.562821
5 64 wa 2865 30.5608 13.8209 16.7399 0.545716
6 64 wa 2898 29.7258 12.288 17.4379 0.564494
7 64 wa 2374 27.9501 9.04505 18.905 0.475249
8 64 wa 3070 27.8238 -2.41262 30.2365 0.627676
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11 64 wa 948 24.7797 11.1246 13.6551 0.536954
12 64 wa 1280 24.6607 3.31109 21.3496 0.55986
13 64 wa 945 24.407 10.3997 14.0073 0.534106
14 64 wa 2905 24.3798 16.4718 7.90803 0.516129
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16 64 wa 1517 24.0941 9.89263 14.2014 0.553193
17 64 wa 1346 23.3943 16.5591 6.83519 0.536929
18 64 wa 1294 23.1114 18.686 4.42542 0.471767
19 64 wa 360 22.7511 9.92554 12.8256 0.562645
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21 64 wa 1510 21.542 9.12946 12.4125 0.544218
22 64 wa 2903 20.3557 5.95869 14.397 0.489607
23 64 wa 488 19.7492 19.8582 -0.108983 0.53951
24 64 wa 1569 19.4247 3.22395 16.2007 0.526821
25 64 wa 2922 19.3008 18.424 0.876865 0.529465
26 64 wa 2148 19.1191 7.79211 11.327 0.486312
27 64 wa 2927 18.9956 6.33507 12.6606 0.551402
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29 64 wa 1778 18.5703 30.7102 -12.1398 0.43724
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1 53 il 71 63.5486 13.6863 49.8623 0.568321
2 53 il 1625 48.8205 13.9918 34.8287 0.55816
3 53 il 1114 43.1829 11.252 31.9309 0.60419
4 53 il 111 41.126 15.0597 26.0663 0.530607
5 53 il 1732 34.6587 9.51569 25.143 0.543849
6 53 il 135 34.6011 20.157 14.4441 0.56755
7 53 il 2741 32.5915 14.5523 18.0392 0.540043
8 53 il 2041 32.358 7.2362 25.1218 0.558451
9 53 il 217 31.7378 3.8509 27.8869 0.56888
10 53 il 16 30.6358 17.1285 13.5073 0.508561
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12 53 il 2781 27.6268 12.802 14.8248 0.533552
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15 53 il 1652 24.4893 10.5024 13.987 0.497287
16 53 il 648 24.1911 22.7156 1.47543 0.541822
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19 53 il 2022 22.6722 17.3182 5.35405 0.425657
20 53 il 2739 22.2575 11.8647 10.3929 0.515474
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22 53 il 2358 21.5007 20.1226 1.37819 0.479039
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25 53 il 1675 19.2176 8.01631 11.2013 0.487394
26 53 il 2433 19.2144 31.9104 -12.696 0.466646
27 53 il 1741 18.5572 32.899 -14.3418 0.48088
28 53 il 2381 17.7135 44.005 -26.2915 0.458023
29 53 il 2136 17.7085 26.082 -8.3735 0.449599
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38 53 il 2338 11.9582 17.024 -5.06574 0.420833
39 53 il 3067 11.6608 8.2051 3.45569 0.549972
40 53 il 2364 11.5705 29.5291 -17.9586 0.463604
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52 53 il 2115 0.248251 25.4132 -25.1649 0.377639
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1 60 va 346 41.8008 12.1037 29.6971 0.59127
2 60 va 612 35.1541 19.3379 15.8163 0.602419
3 60 va 88 34.323 15.6007 18.7222 0.542517
4 60 va 1539 33.5941 16.5729 17.0211 0.499717
5 60 va 122 29.7363 11.6426 18.0937 0.567082
6 60 va 2363 29.1327 3.60673 25.526 0.535998
7 60 va 975 27.7134 14.8014 12.912 0.550359
8 60 va 1522 26.5451 15.1867 11.3584 0.585223
9 60 va 1413 24.1331 13.407 10.7261 0.592971
10 60 va 1095 24.1241 14.2254 9.89873 0.567649
11 60 va 1033 23.9479 18.194 5.75383 0.57294
12 60 va 1086 23.4159 8.22485 15.1911 0.532502
13 60 va 2106 23.3989 17.1061 6.29276 0.509732
14 60 va 422 23.3223 19.2875 4.03478 0.530329
15 60 va 2640 23.2297 9.60014 13.6296 0.525227
16 60 va 388 23.1503 18.8241 4.32624 0.520975
17 60 va 2998 22.1213 24.5229 -2.40156 0.39144
18 60 va 3072 21.9386 19.5688 2.36972 0.519369
19 60 va 435 21.5741 17.3554 4.21868 0.49178
20 60 va 2890 21.513 4.96461 16.5484 0.511905
21 60 va 384 21.4832 27.8226 -6.33941 0.426209
22 60 va 2021 21.3448 17.1295 4.21523 0.459467
23 60 va 2028 20.7858 26.2755 -5.48964 0.431595
24 60 va 539 20.1971 18.3091 1.88803 0.512755
25 60 va 977 20.1106 18.1714 1.93925 0.515495
26 60 va 1236 19.9008 14.6504 5.25035 0.450586
27 60 va 3079 19.1751 25.3601 -6.18501 0.422808
28 60 va 1541 18.4929 15.2008 3.29208 0.536376
29 60 va 116 17.8953 9.32343 8.57188 0.573507
30 60 va 2186 17.4853 18.6444 -1.15906 0.49726
31 60 va 617 17.1248 5.36375 11.7611 0.58494
32 60 va 1262 17.0011 21.3905 -4.38938 0.503496
33 60 va 2068 16.6002 16.0203 0.579937 0.514267
34 60 va 1137 16.3762 23.0898 -6.71356 0.529006
35 60 va 620 16.3714 10.206 6.1654 0.485261
36 60 va 1793 16.1158 20.0699 -3.95414 0.457577
37 60 va 1895 16.1109 31.0945 -14.9837 0.430367
38 60 va 405 15.4261 28.1383 -12.7122 0.396825
39 60 va 401 13.9619 12.8919 1.07009 0.482521
40 60 va 1829 13.5515 20.2156 -6.66406 0.485828
41 60 va 540 13.5135 2.87951 10.634 0.518235
42 60 va 843 12.9033 30.5629 -17.6596 0.436508
43 60 va 1900 12.4072 0.185253 12.222 0.506236
44 60 va 619 11.775 19.0745 -7.2995 0.433485
45 60 va 2642 11.7219 27.404 -15.6821 0.462113
46 60 va 2107 11.6348 18.0866 -6.45173 0.509259
47 60 va 383 11.6166 27.3287 -15.712 0.380574
48 60 va 1915 11.5203 23.7782 -12.258 0.501606
49 60 va 1907 11.4377 12.8716 -1.43389 0.558957
50 60 va 1598 10.3847 8.32239 2.06233 0.492914
51 60 va 1222 9.95868 18.7187 -8.76002 0.413265
52 60 va 2108 9.59374 26.5331 -16.9393 0.45805
53 60 va 2988 7.46705 38.7944 -31.3274 0.425454
54 60 va 1599 6.23593 23.0944 -16.8585 0.446618
55 60 va 414 3.55499 -1.56785 5.12284 0.446429
56 60 va 2074 2.33693 29.2002 -26.8632 0.354308
57 60 va 1908 1.96414 8.12945 -6.16531 0.490741
58 60 va 1655 -0.116019 19.6729 -19.789 0.416856
59 60 va 2434 -0.62926 11.1951 -11.8243 0.499339
60 60 va 2402 -3.37544 27.5202 -30.8957 0.382937
1 61 nj 2753 42.3403 6.48984 35.8505 0.602738
2 61 nj 1923 41.2117 17.904 23.3077 0.561464
3 61 nj 1218 38.6738 7.20077 31.4731 0.629508
4 61 nj 25 38.025 5.65634 32.3686 0.551201
5 61 nj 708 32.0644 9.82594 22.2385 0.507138
6 61 nj 102 31.1846 5.79238 25.3922 0.506573
7 61 nj 422 27.2053 12.5707 14.6346 0.539811
8 61 nj 1367 26.3474 5.9078 20.4396 0.571517
9 61 nj 219 25.9504 28.2516 -2.30123 0.437495
10 61 nj 869 25.498 40.3558 -14.8578 0.539021
11 61 nj 41 23.2347 35.0665 -11.8318 0.507673
12 61 nj 1807 22.5075 -1.26301 23.7705 0.505298
13 61 nj 1228 21.9537 13.7285 8.22523 0.532434
14 61 nj 223 21.9324 30.6676 -8.73521 0.487603
15 61 nj 2363 21.6731 18.6354 3.03774 0.493258
16 61 nj 816 20.8639 19.7612 1.10263 0.528245
17 61 nj 752 20.8061 14.65 6.15617 0.496671
18 61 nj 2344 20.066 34.0963 -14.0302 0.508729
19 61 nj 75 19.8305 -5.43756 25.268 0.523349
20 61 nj 136 19.6694 27.4959 -7.82656 0.551599
21 61 nj 714 19.43 10.7156 8.71442 0.514829
22 61 nj 522 19.3248 12.2783 7.04653 0.470005
23 61 nj 612 19.2939 2.67394 16.6199 0.62817
24 61 nj 1366 19.1374 17.7792 1.35815 0.505037
25 61 nj 896 18.999 2.9886 16.0104 0.508154
26 61 nj 2191 18.9113 14.6477 4.26357 0.456723
27 61 nj 423 18.0958 -14.5936 32.6894 0.526192
28 61 nj 103 17.1013 15.0624 2.0389 0.571142
29 61 nj 1563 16.9132 27.7738 -10.8606 0.448143
30 61 nj 1811 16.4489 22.9575 -6.50862 0.412687
31 61 nj 1391 16.1995 25.0816 -8.88212 0.436481
32 61 nj 484 15.6009 23.4347 -7.83384 0.476212
33 61 nj 303 15.5924 9.46927 6.12316 0.500245
34 61 nj 1676 15.2471 8.59421 6.65288 0.487341
35 61 nj 2180 15.1603 14.054 1.1063 0.478418
36 61 nj 1006 14.781 18.6728 -3.89183 0.507883
37 61 nj 1672 13.3104 -0.449566 13.7599 0.52861
38 61 nj 293 12.9119 16.0071 -3.09521 0.504668
39 61 nj 11 12.6956 35.2117 -22.5162 0.472239
40 61 nj 296 11.7342 26.6357 -14.9016 0.356649
41 61 nj 2590 11.3268 8.42047 2.90635 0.534351
42 61 nj 2458 11.3097 19.0288 -7.71903 0.537243
43 61 nj 1403 10.7523 22.5524 -11.8001 0.413176
44 61 nj 555 9.88008 14.436 -4.5559 0.369071
45 61 nj 2600 9.75751 26.2353 -16.4777 0.386356
46 61 nj 834 9.10985 23.3154 -14.2056 0.434277
47 61 nj 1656 8.89507 14.2996 -5.40452 0.490118
48 61 nj 613 8.86853 22.8143 -13.9458 0.515762
49 61 nj 224 8.86157 28.4176 -19.556 0.489162
50 61 nj 1980 8.85515 -3.97326 12.8284 0.483504
51 61 nj 2607 8.569 -0.321359 8.89036 0.456376
52 61 nj 1881 8.50645 21.4167 -12.9102 0.51394
53 61 nj 1089 8.03813 5.39818 2.63995 0.526047
54 61 nj 204 7.1963 20.4448 -13.2485 0.409228
55 61 nj 1617 6.63569 16.9244 -10.2887 0.487731
56 61 nj 2016 4.67393 12.0685 -7.39459 0.454122
57 61 nj 1048 3.43666 28.5984 -25.1617 0.485148
58 61 nj 486 2.4309 27.7115 -25.2806 0.423064
59 61 nj 1689 -0.773993 21.2223 -21.9963 0.448585
60 61 nj 1616 -5.49722 42.7484 -48.2456 0.399464
61 61 nj 2495 -8.01623 16.5549 -24.5711 0.444377
1 66 ny 694 48.4503 16.4318 32.0186 0.536565
2 66 ny 2753 40.4087 10.7805 29.6283 0.553949
3 66 ny 1155 40.1333 7.70772 32.4256 0.581066
4 66 ny 2344 37.7084 11.3163 26.3921 0.597978
5 66 ny 56 34.8224 13.5008 21.3216 0.583617
6 66 ny 395 34.5666 17.6641 16.9025 0.543084
7 66 ny 271 33.6195 10.6166 23.0029 0.524943
8 66 ny 555 31.7302 16.1261 15.604 0.504724
9 66 ny 354 30.655 5.93434 24.7206 0.536281
10 66 ny 41 29.0759 20.4935 8.5823 0.478175
11 66 ny 375 28.3928 22.8205 5.57235 0.593348
12 66 ny 743 28.1465 13.6152 14.5313 0.485072
13 66 ny 237 27.4751 16.5406 10.9344 0.561224
14 66 ny 2933 27.0589 14.3566 12.7023 0.488095
15 66 ny 1660 25.1928 16.7438 8.44899 0.573696
16 66 ny 1796 24.278 17.4388 6.83926 0.529289
17 66 ny 371 24.1865 0.0481585 24.1383 0.548942
18 66 ny 2285 23.4682 21.8107 1.65753 0.431973
19 66 ny 1807 23.0964 10.6952 12.4012 0.574546
20 66 ny 1563 22.475 31.9726 -9.4976 0.45068
21 66 ny 263 20.9636 37.0314 -16.0678 0.456727
22 66 ny 2577 20.4488 30.1219 -9.67317 0.502362
23 66 ny 335 19.4845 3.61496 15.8695 0.52825
24 66 ny 1302 19.3132 3.41296 15.9003 0.567744
25 66 ny 2601 18.978 17.409 1.56893 0.494426
26 66 ny 1257 18.6947 12.1209 6.57381 0.487434
27 66 ny 1396 16.8985 -1.69016 18.5886 0.544218
28 66 ny 527 16.8561 13.2594 3.59671 0.499906
29 66 ny 3059 16.4608 -0.881929 17.3428 0.476946
30 66 ny 806 16.1849 7.06617 9.11871 0.532785
31 66 ny 270 16.1585 6.91038 9.24807 0.502646
32 66 ny 2681 14.2192 8.44713 5.77206 0.534108
33 66 ny 1881 14.216 10.5937 3.62227 0.476474
34 66 ny 1211 14.0279 7.45778 6.5701 0.544407
35 66 ny 2265 13.5851 0.0297039 13.5554 0.478647
36 66 ny 3111 12.7464 22.4402 -9.69378 0.429422
37 66 ny 1237 12.7141 9.29182 3.42228 0.422241
38 66 ny 1156 12.0698 9.8408 2.22904 0.476568
39 66 ny 2205 11.6272 24.0264 -12.3991 0.446618
40 66 ny 1600 11.6108 23.9547 -12.3439 0.494615
41 66 ny 1230 11.2772 15.17 -3.89281 0.55376
42 66 ny 1340 10.1355 28.0666 -17.9311 0.427627
43 66 ny 3053 9.43993 26.1985 -16.7585 0.467215
44 66 ny 358 9.30389 -3.0067 12.3106 0.439153
45 66 ny 3017 9.20039 1.35335 7.84704 0.518046
46 66 ny 369 9.11328 13.5659 -4.45261 0.555272
47 66 ny 640 8.65669 11.4659 -2.80921 0.479308
48 66 ny 1635 8.2932 35.3695 -27.0763 0.391818
49 66 ny 333 7.73318 16.3124 -8.5792 0.444161
50 66 ny 2070 7.2978 6.5656 0.732195 0.486678
51 66 ny 2573 6.82124 19.9478 -13.1266 0.428949
52 66 ny 3004 6.55504 30.2022 -23.6472 0.433957
53 66 ny 2579 5.33936 12.701 -7.36159 0.485639
54 66 ny 2554 4.92333 24.9255 -20.0022 0.457389
55 66 ny 1880 3.64792 19.5329 -15.885 0.384921
56 66 ny 1989 2.75915 13.6415 -10.8824 0.493386
57 66 ny 759 2.52109 22.7836 -20.2625 0.511621
58 66 ny 2895 2.32686 31.5905 -29.2637 0.519936
59 66 ny 1520 2.06671 14.4327 -12.366 0.41336
60 66 ny 421 1.93626 25.2011 -23.2648 0.52003
61 66 ny 380 0.985275 21.5759 -20.5907 0.435091
62 66 ny 3112 0.703753 33.294 -32.5903 0.410147
63 66 ny 1862 -0.630036 6.9259 -7.55594 0.454837
64 66 ny 1698 -1.64305 39.2146 -40.8577 0.357332
65 66 ny 329 -3.85906 9.24157 -13.1006 0.515495
66 66 ny 334 -6.96036 32.7999 -39.7602 0.412509
1 50 ok 2436 34.0392 13.1551 20.8841 0.562702
2 50 ok 1561 28.7919 6.10969 22.6822 0.5709
3 50 ok 2469 25.5739 14.7135 10.8603 0.530821
4 50 ok 1742 24.6686 11.8848 12.7838 0.574686
5 50 ok 2369 24.3301 9.10787 15.2222 0.602442
6 50 ok 2376 23.8736 16.1775 7.69612 0.507868
7 50 ok 2391 23.6073 8.33028 15.277 0.591532
8 50 ok 2773 21.1916 12.4921 8.69954 0.527376
9 50 ok 2372 20.3914 18.1509 2.24051 0.417538
10 50 ok 2333 20.3625 13.7177 6.64472 0.528838
11 50 ok 2389 19.5805 10.7728 8.80767 0.535173
12 50 ok 31 19.1853 16.928 2.25735 0.472911
13 50 ok 2354 19.1221 17.5178 1.60427 0.48342
14 50 ok 2829 18.9762 8.70584 10.2703 0.56473
15 50 ok 2398 18.8384 14.0201 4.81826 0.491636
16 50 ok 2382 18.3308 16.6127 1.71802 0.44597
17 50 ok 2821 18.282 12.1234 6.15855 0.456286
18 50 ok 932 18.0593 8.87325 9.18603 0.513383
19 50 ok 2461 17.8983 2.75965 15.1387 0.537821
20 50 ok 2793 17.7735 19.5847 -1.81128 0.459404
21 50 ok 2373 17.0226 12.4516 4.571 0.50948
22 50 ok 2352 16.8469 6.62018 10.2267 0.521654
23 50 ok 2424 16.7965 20.2942 -3.49771 0.47198
24 50 ok 2341 16.4678 10.3722 6.09565 0.443481
25 50 ok 2842 16.2697 12.3864 3.88329 0.515887
26 50 ok 1750 16.2359 12.9586 3.27728 0.452524
27 50 ok 2723 15.8208 15.5275 0.293315 0.496834
28 50 ok 2759 15.0468 25.809 -10.7622 0.491739
29 50 ok 2795 14.9957 26.1746 -11.1789 0.450121
30 50 ok 2004 14.8419 22.4977 -7.65587 0.474745
31 50 ok 2435 14.3475 15.9838 -1.63628 0.501279
32 50 ok 1209 13.8604 21.9591 -8.0987 0.384351
33 50 ok 2343 13.7582 16.8506 -3.09242 0.464312
34 50 ok 476 13.3452 17.7676 -4.42241 0.584233
35 50 ok 2165 13.3311 12.9798 0.351359 0.508799
36 50 ok 2395 13.287 14.2099 -0.922898 0.515574
37 50 ok 2332 12.01 20.795 -8.78507 0.444009
38 50 ok 1429 11.4266 15.9224 -4.49586 0.40144
39 50 ok 2986 10.5145 21.1424 -10.6279 0.469194
40 50 ok 1666 10.5011 17.6339 -7.13272 0.426983
41 50 ok 2571 9.80428 27.9027 -18.0984 0.453854
42 50 ok 2765 9.71233 16.8129 -7.1006 0.415303
43 50 ok 2763 9.10438 14.2176 -5.11317 0.451607
44 50 ok 2777 8.26463 21.3789 -13.1143 0.485162
45 50 ok 2396 6.81205 12.3965 -5.58443 0.415655
46 50 ok 2468 5.70605 17.0846 -11.3786 0.453104
47 50 ok 2779 5.68207 21.5514 -15.8693 0.40197
48 50 ok 2330 5.64684 23.7924 -18.1456 0.438728
49 50 ok 2359 5.13549 17.0397 -11.9042 0.429342
50 50 ok 2388 0.645936 21.2737 -20.6278 0.39306
1 54 or 1823 38.7781 5.13572 33.6424 0.593726
2 54 or 1318 34.7254 8.6934 26.032 0.604214
3 54 or 2811 33.0349 5.57981 27.4551 0.499811
4 54 or 2865 31.6869 20.3938 11.2931 0.535809
5 54 or 360 31.1202 11.2192 19.901 0.569161
6 54 or 488 30.7177 17.5639 13.1538 0.483749
7 54 or 359 29.2891 21.3056 7.98344 0.55565
8 54 or 1983 29.2703 8.9194 20.3509 0.486584
9 54 or 2122 25.4351 7.17351 18.2616 0.494142
10 54 or 2046 25.3446 7.32226 18.0223 0.558201
11 54 or 2517 25.1203 28.87 -3.74972 0.386527
12 54 or 2130 24.8644 17.8321 7.03233 0.4572
13 54 or 2915 22.9164 11.2524 11.6641 0.472128
14 54 or 2471 22.5232 12.8723 9.65091 0.584467
15 54 or 997 21.6889 18.7331 2.95577 0.486017
16 54 or 2733 20.4318 11.2245 9.20733 0.525416
17 54 or 955 19.9397 7.02853 12.9112 0.590325
18 54 or 1595 19.8146 39.1368 -19.3222 0.373205
19 54 or 2002 19.6106 28.8886 -9.27797 0.477419
20 54 or 2521 19.198 14.6316 4.56648 0.402305
21 54 or 1540 19.0744 13.7601 5.31433 0.460317
22 54 or 956 18.8536 13.3693 5.48429 0.514172
23 54 or 2374 18.2234 9.0226 9.20082 0.494142
24 54 or 2635 16.5216 15.8539 0.667657 0.4572
25 54 or 2990 16.4757 5.4408 11.0349 0.5411
26 54 or 1571 16.4095 15.0058 1.40362 0.558485
27 54 or 2542 15.909 24.5947 -8.68572 0.401644
28 54 or 192 15.8263 37.8357 -22.0094 0.436602
29 54 or 1425 14.987 35.7267 -20.7396 0.469199
30 54 or 1130 14.0642 30.0338 -15.9696 0.391818
31 54 or 948 13.7724 20.5387 -6.7663 0.548091
32 54 or 2594 13.7517 11.9202 1.83143 0.466364
33 54 or 2192 13.4845 8.70591 4.77861 0.56472
34 54 or 2898 13.2263 22.7092 -9.48293 0.536565
35 54 or 2850 13.094 15.827 -2.73307 0.513416
36 54 or 1432 12.6982 13.3412 -0.64296 0.466931
37 54 or 1891 12.6707 14.6305 -1.95979 0.474395
38 54 or 2147 11.0519 26.0313 -14.9795 0.382748
39 54 or 1569 10.8418 17.4782 -6.6364 0.452475
40 54 or 847 10.8278 12.1176 -1.28978 0.455026
41 54 or 2557 9.94761 17.3697 -7.42208 0.430933
42 54 or 1544 9.87307 8.01187 1.8612 0.461735
43 54 or 568 9.6387 12.8023 -3.16364 0.552343
44 54 or 1566 8.43022 26.0273 -17.5971 0.453137
45 54 or 1778 8.31997 11.183 -2.86308 0.474112
46 54 or 753 7.3274 13.0522 -5.72481 0.508881
47 54 or 1510 6.32063 21.5444 -15.2238 0.465797
48 54 or 957 5.19237 31.9653 -26.7729 0.39692
49 54 or 3024 4.28907 3.08073 1.20834 0.429233
50 54 or 2550 1.66334 8.90082 -7.23748 0.435847
51 54 or 2951 1.59612 14.7638 -13.1676 0.438398
52 54 or 2411 -0.408178 19.393 -19.8012 0.460506
53 54 or 2522 -2.24119 10.2648 -12.506 0.465231
54 54 or 2439 -4.50892 16.6354 -21.1443 0.448318
1 44 sc 1771 36.0153 8.79554 27.2198 0.595183
2 44 sc 425 33.5066 12.0571 21.4494 0.527441
3 44 sc 337 33.4614 17.4285 16.0329 0.537705
4 44 sc 343 32.7055 20.0001 12.7054 0.534649
5 44 sc 342 32.3602 15.6793 16.6809 0.552622
6 44 sc 2614 28.563 13.4539 15.1091 0.518433
7 44 sc 2483 28.4323 20.1672 8.26512 0.47153
8 44 sc 1319 28.298 17.8844 10.4136 0.508377
9 44 sc 900 28.0871 20.0881 7.99902 0.508132
10 44 sc 3025 27.5182 1.58366 25.9345 0.616586
11 44 sc 2415 27.3273 21.9676 5.35973 0.540754
12 44 sc 1369 26.2721 27.3564 -1.08435 0.545647
13 44 sc 1051 25.1055 20.0867 5.01877 0.558764
14 44 sc 801 24.8493 17.7893 7.06 0.529805
15 44 sc 2815 23.9057 14.0729 9.83272 0.538776
16 44 sc 1293 23.5126 18.8563 4.65628 0.534814
17 44 sc 1287 23.3372 23.912 -0.574831 0.499743
18 44 sc 2751 22.9246 22.5627 0.36187 0.4824
19 44 sc 1553 22.6279 17.8532 4.77469 0.54471
20 44 sc 1746 21.8271 19.2151 2.61199 0.513858
21 44 sc 1379 21.3796 31.8436 -10.464 0.463128
22 44 sc 1676 21.0767 11.4039 9.67279 0.545641
23 44 sc 1398 20.167 20.8438 -0.676764 0.472192
24 44 sc 281 19.6991 15.6038 4.09531 0.504838
25 44 sc 2430 19.5108 30.1426 -10.6318 0.436153
26 44 sc 1102 19.1318 23.0771 -3.94531 0.511084
27 44 sc 2362 18.305 23.7655 -5.46053 0.516057
28 44 sc 1261 15.8961 20.3961 -4.49994 0.408118
29 44 sc 1249 15.6443 9.43754 6.20675 0.518078
30 44 sc 1758 15.1924 10.7678 4.4246 0.53839
31 44 sc 1618 15.1125 23.1329 -8.02043 0.459889
32 44 sc 1730 14.6664 8.64867 6.01774 0.529499
33 44 sc 804 14.163 26.7131 -12.5501 0.385668
34 44 sc 21 12.7475 19.5664 -6.81898 0.525794
35 44 sc 1225 12.3987 19.0745 -6.67575 0.481861
36 44 sc 1466 12.3604 25.3495 -12.9891 0.457739
37 44 sc 1026 12.1138 23.7018 -11.588 0.514238
38 44 sc 1959 10.1694 24.7222 -14.5528 0.449092
39 44 sc 442 9.1112 19.253 -10.1418 0.48567
40 44 sc 2187 5.44475 21.303 -15.8582 0.45943
41 44 sc 2092 5.37419 36.2795 -30.9053 0.420666
42 44 sc 1772 4.5579 28.8082 -24.2503 0.389752
43 44 sc 2973 2.35895 23.3193 -20.9604 0.412998
44 44 sc 1436 0.226264 19.4806 -19.2543 0.451119
1 47 ga 1771 41.8866 11.3181 30.5685 0.587144
2 47 ga 343 33.2684 16.3264 16.942 0.521606
3 47 ga 2918 30.8452 15.2264 15.6188 0.576957
4 47 ga 1102 28.0806 13.0469 15.0337 0.559161
5 47 ga 1319 25.1945 25.7076 -0.51311 0.494413
6 47 ga 1848 25.0928 12.9305 12.1623 0.565333
7 47 ga 1261 24.4859 11.1987 13.2872 0.527133
8 47 ga 57 24.1636 17.5092 6.65438 0.51878
9 47 ga 2007 24.0954 21.9157 2.17972 0.491835
10 47 ga 2967 23.5758 21.4197 2.1561 0.474325
11 47 ga 442 22.8739 10.0447 12.8292 0.555535
12 47 ga 342 22.5483 14.5991 7.94915 0.484267
13 47 ga 590 22.1453 9.83142 12.3138 0.522483
14 47 ga 1758 22.1335 14.3757 7.75784 0.540055
15 47 ga 1533 21.5143 17.9631 3.55124 0.523554
16 47 ga 1746 20.8567 9.99745 10.8592 0.62746
17 47 ga 1795 20.679 23.3561 -2.67707 0.452081
18 47 ga 2415 20.6026 25.1429 -4.54033 0.409954
19 47 ga 2887 20.592 21.4434 -0.851492 0.503093
20 47 ga 34 20.3097 16.4486 3.86108 0.482439
21 47 ga 1002 19.3182 11.5616 7.75659 0.499802
22 47 ga 2119 18.8408 19.3725 -0.531737 0.461831
23 47 ga 1999 18.7413 12.489 6.2523 0.449555
24 47 ga 832 18.5367 13.0447 5.49196 0.502971
25 47 ga 3091 18.0782 19.6808 -1.60262 0.511918
26 47 ga 281 17.8047 24.1943 -6.3896 0.479064
27 47 ga 2038 17.5285 16.5783 0.95015 0.468159
28 47 ga 2420 17.4404 12.9249 4.51549 0.5573
29 47 ga 1304 15.5057 14.5308 0.974977 0.456268
30 47 ga 1877 15.4972 23.0074 -7.51019 0.454159
31 47 ga 2655 15.4767 16.1514 -0.674718 0.536204
32 47 ga 587 14.355 17.0118 -2.65673 0.433464
33 47 ga 2362 13.4445 18.7954 -5.35084 0.463581
34 47 ga 1414 13.0572 17.4128 -4.35561 0.403862
35 47 ga 1683 12.3923 29.4605 -17.0682 0.450983
36 47 ga 2974 11.8972 26.7238 -14.8266 0.445658
37 47 ga 1648 11.3493 20.7501 -9.40083 0.445313
38 47 ga 2958 11.2928 22.3798 -11.087 0.435103
39 47 ga 1439 10.3545 29.9541 -19.5996 0.392695
40 47 ga 1788 10.1553 24.2472 -14.0919 0.439269
41 47 ga 1311 9.20828 9.17307 0.0352135 0.488407
42 47 ga 1398 8.926 24.9788 -16.0528 0.369978
43 47 ga 900 8.26 19.3812 -11.1212 0.490069
44 47 ga 2393 7.10382 16.8213 -9.71748 0.462046
45 47 ga 1415 5.65733 17.3505 -11.6931 0.489703
46 47 ga 1127 5.2856 22.7892 -17.5036 0.439925
47 47 ga 547 3.28285 12.8415 -9.5587 0.402736
1 53 pa 103 47.671 1.65085 46.0202 0.611837
2 53 pa 1279 44.2944 19.2321 25.0623 0.581121
3 53 pa 395 43.3477 9.05531 34.2924 0.507756
4 53 pa 1391 38.8635 14.605 24.2585 0.537552
5 53 pa 1507 37.8788 4.01668 33.8621 0.577517
6 53 pa 2729 32.7224 23.3601 9.36228 0.482012
7 53 pa 378 32.5318 10.5564 21.9754 0.573262
8 53 pa 1153 30.9509 0.758399 30.1925 0.609112
9 53 pa 222 30.8606 11.7253 19.1353 0.586201
10 53 pa 816 28.1909 13.6693 14.5216 0.5425
11 53 pa 56 27.817 24.6718 3.14517 0.459076
12 53 pa 1923 27.7176 25.5387 2.17898 0.505544
13 53 pa 272 26.8151 17.6654 9.14973 0.544407
14 53 pa 834 25.004 23.0302 1.9738 0.477803
15 53 pa 250 24.8553 13.0016 11.8537 0.504191
16 53 pa 11 24.1162 16.5822 7.53405 0.566504
17 53 pa 1143 23.3132 15.6318 7.68137 0.473148
18 53 pa 1027 22.7576 32.8641 -10.1066 0.474701
19 53 pa 223 22.5986 10.8732 11.7255 0.588831
20 53 pa 204 21.4907 17.6824 3.80832 0.542804
21 53 pa 84 20.8887 42.3557 -21.4671 0.467022
22 53 pa 104 18.8632 29.1845 -10.3213 0.473295
23 53 pa 896 18.762 21.5025 -2.74054 0.464149
24 53 pa 2229 18.0191 19.7475 -1.72842 0.496575
25 53 pa 708 17.4052 14.7862 2.61906 0.458852
26 53 pa 341 16.8062 18.9008 -2.09457 0.417503
27 53 pa 284 16.2726 16.7603 -0.487711 0.460118
28 53 pa 316 15.7512 24.116 -8.36479 0.474697
29 53 pa 365 15.5891 21.535 -5.94595 0.495856
30 53 pa 486 15.0328 21.7337 -6.70092 0.468107
31 53 pa 224 14.6944 20.9044 -6.21002 0.454333
32 53 pa 484 13.755 24.5637 -10.8087 0.544098
33 53 pa 1089 13.5399 17.0567 -3.51686 0.499416
34 53 pa 1495 13.3044 22.3062 -9.00182 0.456719
35 53 pa 87 11.9661 7.83961 4.12648 0.49091
36 53 pa 321 11.9423 24.0847 -12.1425 0.46638
37 53 pa 433 11.3668 2.41867 8.94815 0.512388
38 53 pa 1403 11.2897 14.2685 -2.97878 0.463067
39 53 pa 304 11.2436 18.4526 -7.20902 0.466312
40 53 pa 809 11.0418 18.3263 -7.28445 0.469056
41 53 pa 357 10.8038 15.1484 -4.34453 0.434872
42 53 pa 2559 10.4474 16.8802 -6.4328 0.458487
43 53 pa 1647 10.0414 28.995 -18.9536 0.461813
44 53 pa 1370 9.50441 12.4065 -2.90205 0.493894
45 53 pa 2539 9.21732 42.8946 -33.6772 0.394163
46 53 pa 293 9.08751 14.219 -5.1315 0.395543
47 53 pa 1634 9.08094 6.24852 2.83243 0.41867
48 53 pa 1791 7.84659 29.957 -22.1104 0.496363
49 53 pa 423 6.6078 32.8492 -26.2414 0.45797
50 53 pa 509 6.23359 25.3987 -19.1651 0.407632
51 53 pa 225 3.57276 27.0447 -23.4719 0.356015
52 53 pa 709 2.75864 16.9995 -14.2409 0.425003
53 53 pa 2607 -0.983559 25.1376 -26.1212 0.407046
1 37 pit 1218 43.2221 12.7554 30.4667 0.549055
2 37 pit 222 33.7259 13.5258 20.2001 0.562749
3 37 pit 2603 30.7909 3.91995 26.8709 0.554645
4 37 pit 48 27.9006 15.9588 11.9418 0.532661
5 37 pit 3062 27.1408 13.4136 13.7272 0.564866
6 37 pit 2534 25.609 14.7832 10.8258 0.551186
7 37 pit 302 25.3649 6.94077 18.4242 0.481695
8 37 pit 1629 25.0746 14.5715 10.5031 0.545573
9 37 pit 291 24.0844 7.34683 16.7375 0.537814
10 37 pit 2614 21.4198 22.572 -1.15223 0.474949
11 37 pit 337 20.8383 19.1707 1.6676 0.510481
12 37 pit 2901 20.6771 16.4361 4.24093 0.526132
13 37 pit 2644 19.5386 18.4258 1.11282 0.470424
14 37 pit 379 19.5078 12.9952 6.51253 0.505595
15 37 pit 63 19.1987 7.46891 11.7298 0.533445
16 37 pit 1990 17.8881 11.5111 6.37703 0.486405
17 37 pit 2407 16.7873 15.1926 1.5947 0.422255
18 37 pit 2399 16.4282 12.1119 4.31626 0.508265
19 37 pit 128 15.3476 12.075 3.27259 0.54499
20 37 pit 2252 15.1965 23.3281 -8.13161 0.470932
21 37 pit 117 14.1411 22.1879 -8.04676 0.446892
22 37 pit 1708 13.8288 16.4396 -2.61083 0.449268
23 37 pit 3108 13.8054 21.5645 -7.75911 0.464074
24 37 pit 1367 13.7251 19.7489 -6.02382 0.493841
25 37 pit 2656 13.4939 27.9433 -14.4494 0.377215
26 37 pit 440 12.4712 33.0127 -20.5415 0.396708
27 37 pit 2544 12.3621 18.3292 -5.96713 0.477217
28 37 pit 2172 12.1342 28.0198 -15.8856 0.462137
29 37 pit 2641 12.0919 19.6118 -7.5199 0.503004
30 37 pit 869 12.0176 15.9437 -3.92609 0.477517
31 37 pit 1249 11.8813 12.9301 -1.04874 0.500104
32 37 pit 1743 11.8655 33.8676 -22.002 0.415812
33 37 pit 2051 10.7565 16.3386 -5.58213 0.464647
34 37 pit 2279 8.86279 20.7035 -11.8407 0.451459
35 37 pit 2428 8.83822 21.7598 -12.9216 0.421542
36 37 pit 306 -0.118423 22.1546 -22.2731 0.417132
37 37 pit 2618 -0.818717 24.0298 -24.8486 0.33484
1 44 sac 1717 38.905 17.5156 21.3894 0.622599
2 44 sac 852 33.6386 10.6157 23.0229 0.572451
3 44 sac 675 33.2511 13.752 19.4991 0.559346
4 44 sac 115 32.1336 17.8206 14.313 0.48586
5 44 sac 1868 31.8411 17.9038 13.9373 0.557405
6 44 sac 2035 31.0682 19.3528 11.7154 0.559952
7 44 sac 604 30.6133 3.84699 26.7663 0.507777
8 44 sac 599 29.0989 12.7873 16.3116 0.558262
9 44 sac 2854 28.6963 12.6839 16.0124 0.559769
10 44 sac 692 26.578 8.63959 17.9384 0.520692
11 44 sac 2122 26.2839 20.8778 5.40609 0.538329
12 44 sac 2063 25.4356 7.26361 18.1719 0.555347
13 44 sac 2473 25.0839 26.0517 -0.967786 0.501954
14 44 sac 668 24.8041 31.8997 -7.09559 0.50248
15 44 sac 1678 23.4333 19.8717 3.56167 0.459448
16 44 sac 1700 21.1887 19.6276 1.56116 0.485003
17 44 sac 2367 20.8379 24.2188 -3.38089 0.462565
18 44 sac 2073 20.6717 8.28116 12.3905 0.487771
19 44 sac 2085 20.3681 5.53562 14.8325 0.505169
20 44 sac 295 19.2689 22.3296 -3.0607 0.490863
21 44 sac 1458 18.9988 28.3797 -9.38096 0.486325
22 44 sac 1323 18.7806 26.5816 -7.80102 0.40982
23 44 sac 1671 17.6944 23.0265 -5.33212 0.483766
24 44 sac 2144 17.4479 13.4972 3.95074 0.571625
25 44 sac 2551 17.4451 24.8155 -7.37036 0.417751
26 44 sac 701 16.8681 17.4389 -0.570785 0.543657
27 44 sac 2390 16.3153 15.2434 1.0719 0.436643
28 44 sac 100 15.6355 11.9628 3.67276 0.572751
29 44 sac 766 15.3455 21.3977 -6.05225 0.44905
30 44 sac 1072 15.262 18.6987 -3.43669 0.474745
31 44 sac 2892 14.9829 26.3811 -11.3982 0.455051
32 44 sac 2489 14.3448 31.258 -16.9133 0.438762
33 44 sac 1662 13.5307 26.1551 -12.6244 0.450795
34 44 sac 1351 13.1513 33.0516 -19.9003 0.420072
35 44 sac 3013 12.834 26.8758 -14.0418 0.437016
36 44 sac 1147 12.6564 26.2014 -13.545 0.421315
37 44 sac 2761 12.1253 -1.29219 13.4175 0.496485
38 44 sac 1359 10.7992 6.9931 3.8061 0.495658
39 44 sac 1516 9.78286 14.8678 -5.08497 0.437261
40 44 sac 981 9.15031 33.7876 -24.6373 0.510949
41 44 sac 2204 5.87698 9.24611 -3.36913 0.49771
42 44 sac 2456 5.72448 19.1732 -13.4487 0.471206
43 44 sac 2156 1.78231 29.5899 -27.8076 0.439362
44 44 sac 1974 -3.73504 41.7938 -45.5289 0.365771
1 37 sdc 968 52.8536 12.8229 40.0307 0.640392
2 37 sdc 1622 44.2074 10.3862 33.8212 0.582763
3 37 sdc 1332 33.1353 19.982 13.1532 0.54796
4 37 sdc 1388 29.4532 3.26152 26.1916 0.625103
5 37 sdc 812 25.3843 15.2098 10.1745 0.522331
6 37 sdc 341 24.1072 4.30557 19.8017 0.542544
7 37 sdc 1828 23.9248 19.5763 4.34854 0.489474
8 37 sdc 2485 20.2773 22.2153 -1.93804 0.510615
9 37 sdc 2658 18.5583 12.0033 6.55498 0.433992
10 37 sdc 2493 18.0087 15.369 2.63968 0.431012
11 37 sdc 3032 17.7953 22.3695 -4.57416 0.486973
12 37 sdc 2339 17.3853 12.6015 4.78371 0.550445
13 37 sdc 1972 17.1988 7.58253 9.61632 0.579068
14 37 sdc 2984 16.0846 19.004 -2.91935 0.533958
15 37 sdc 1538 15.2125 16.3785 -1.16605 0.461915
16 37 sdc 2599 15.0031 11.7187 3.28442 0.487405
17 37 sdc 2827 14.7344 27.9999 -13.2655 0.461668
18 37 sdc 1266 14.4538 18.686 -4.23217 0.515992
19 37 sdc 1159 14.0132 24.3878 -10.3745 0.517958
20 37 sdc 3041 13.239 24.0944 -10.8554 0.421874
21 37 sdc 1011 13.2373 34.1189 -20.8816 0.492466
22 37 sdc 1072 12.9807 13.3636 -0.382888 0.507586
23 37 sdc 1527 12.8405 13.3859 -0.545374 0.513502
24 37 sdc 2839 12.68 7.37803 5.30198 0.561854
25 37 sdc 393 12.2648 19.2113 -6.94645 0.436795
26 37 sdc 2029 11.5654 12.6006 -1.03518 0.540451
27 37 sdc 1348 11.4205 20.1767 -8.75618 0.468502
28 37 sdc 2032 10.9144 16.4111 -5.49666 0.501557
29 37 sdc 2066 10.913 26.1346 -15.2216 0.446786
30 37 sdc 3021 10.5707 23.1351 -12.5644 0.458831
31 37 sdc 2543 9.85212 3.62449 6.22762 0.485414
32 37 sdc 2193 9.23167 18.0681 -8.83646 0.491294
33 37 sdc 2637 8.34473 8.11492 0.229806 0.485425
34 37 sdc 2102 7.25479 20.5547 -13.2999 0.460889
35 37 sdc 2486 6.45365 22.1797 -15.7261 0.47242
36 37 sdc 2404 5.21559 23.6401 -18.4245 0.368232
37 37 sdc 1572 3.4859 15.0423 -11.5564 0.466489
1 46 li 2010 36.552 15.2305 21.3214 0.57238
2 46 li 870 33.9558 3.41488 30.5409 0.592628
3 46 li 287 33.6627 12.6724 20.9903 0.547443
4 46 li 102 33.231 11.1866 22.0444 0.570386
5 46 li 1606 29.2824 14.867 14.4154 0.550411
6 46 li 28 27.2231 15.5497 11.6733 0.50807
7 46 li 2161 26.2133 10.7033 15.5101 0.554259
8 46 li 533 22.474 19.5836 2.89041 0.489698
9 46 li 358 21.8365 8.54192 13.2945 0.526502
10 46 li 564 21.3625 13.3911 7.97139 0.540219
11 46 li 263 20.6413 26.5419 -5.90061 0.50431
12 46 li 417 20.4062 23.6275 -3.22131 0.507809
13 46 li 2875 19.8498 15.6995 4.15037 0.496974
14 46 li 271 19.2075 10.3816 8.82585 0.570704
15 46 li 2872 18.2288 16.6852 1.54363 0.465743
16 46 li 527 17.6274 2.30187 15.3256 0.575579
17 46 li 884 17.4604 23.0198 -5.55934 0.44734
18 46 li 352 17.274 12.3847 4.88925 0.461588
19 46 li 1358 15.6874 16.6384 -0.951036 0.517634
20 46 li 1554 15.2054 16.3332 -1.12779 0.486079
21 46 li 569 15.0267 25.9393 -10.9125 0.478869
22 46 li 1803 14.8997 14.1287 0.770945 0.479878
23 46 li 806 14.7394 5.13875 9.60068 0.52036
24 46 li 545 14.3328 13.4863 0.846588 0.44047
25 46 li 2638 13.5802 16.158 -2.57779 0.497704
26 46 li 496 13.5799 16.1488 -2.56895 0.47017
27 46 li 1468 12.9526 9.01989 3.93268 0.520668
28 46 li 270 12.0137 15.4925 -3.47879 0.517175
29 46 li 329 11.744 13.7277 -1.98367 0.508111
30 46 li 1607 11.0999 21.3959 -10.296 0.498205
31 46 li 2476 11.037 15.9803 -4.94333 0.415377
32 46 li 2347 10.5317 13.1891 -2.65745 0.445082
33 46 li 1546 9.28638 15.3363 -6.04989 0.451125
34 46 li 1537 8.84895 13.126 -4.27708 0.461241
35 46 li 810 8.63701 20.3387 -11.7017 0.476497
36 46 li 2869 8.55784 18.3442 -9.78634 0.422956
37 46 li 514 7.96969 14.1361 -6.16643 0.472893
38 46 li 353 7.55283 22.0232 -14.4704 0.425414
39 46 li 1203 7.53739 19.9879 -12.4505 0.445286
40 46 li 1751 7.45174 19.5529 -12.1012 0.443208
41 46 li 1808 7.31606 14.767 -7.45094 0.409908
42 46 li 2487 6.97542 18.7958 -11.8203 0.429933
43 46 li 1601 6.06476 17.5337 -11.469 0.43295
44 46 li 371 4.75963 13.3909 -8.6313 0.439972
45 46 li 2027 3.36547 17.7132 -14.3477 0.435545
46 46 li 871 0.537923 26.3461 -25.8082 0.426859
1 47 sj 670 42.6066 8.66751 33.939 0.500623
2 47 sj 971 41.9873 15.9871 26.0002 0.526181
3 47 sj 100 40.8825 18.8915 21.991 0.544604
4 47 sj 192 35.6857 9.19613 26.4896 0.569171
5 47 sj 987 34.7988 13.0579 21.7409 0.556077
6 47 sj 1280 32.347 19.6752 12.6717 0.51786
7 47 sj 114 28.4846 15.4634 13.0212 0.463723
8 47 sj 675 27.0949 1.36945 25.7255 0.481078
9 47 sj 115 26.2427 23.0641 3.17853 0.493244
10 47 sj 846 25.7897 8.65878 17.131 0.559805
11 47 sj 1868 24.9492 29.3978 -4.44861 0.513538
12 47 sj 254 24.4121 5.42756 18.9845 0.558359
13 47 sj 692 23.8122 20.1968 3.61537 0.542238
14 47 sj 766 23.1483 16.6694 6.4789 0.540392
15 47 sj 668 23.0625 1.17884 21.8836 0.45257
16 47 sj 359 23.0422 2.61178 20.4304 0.552582
17 47 sj 1516 22.719 13.0115 9.70744 0.418783
18 47 sj 649 21.8798 14.4663 7.41351 0.481732
19 47 sj 2489 21.7243 20.8942 0.83011 0.443579
20 47 sj 604 21.6845 13.0288 8.65575 0.531183
21 47 sj 852 20.3941 6.47946 13.9146 0.493528
22 47 sj 2135 20.0568 19.6281 0.428623 0.489955
23 47 sj 2035 19.4248 15.9329 3.49186 0.546924
24 47 sj 2813 16.9452 29.1244 -12.1792 0.490857
25 47 sj 1967 16.4675 21.0978 -4.63031 0.45359
26 47 sj 2473 14.4762 21.475 -6.99877 0.43705
27 47 sj 1351 12.9185 18.0891 -5.17053 0.42806
28 47 sj 3013 12.8518 11.2187 1.63313 0.504278
29 47 sj 253 11.6337 28.0096 -16.3759 0.425515
30 47 sj 3045 10.5363 19.7676 -9.2313 0.44169
31 47 sj 3022 10.2294 10.4502 -0.220861 0.469287
32 47 sj 1834 9.74394 34.757 -25.013 0.394947
33 47 sj 1120 9.60773 -0.391861 9.99959 0.545948
34 47 sj 8 9.57117 12.1648 -2.59363 0.511489
35 47 sj 2367 8.91056 25.0689 -16.1584 0.432963
36 47 sj 581 8.73524 28.0478 -19.3126 0.449128
37 47 sj 1458 8.72199 4.48243 4.23956 0.466859
38 47 sj 2159 8.05982 14.5054 -6.44558 0.441068
39 47 sj 1641 7.57017 32.4661 -24.896 0.391565
40 47 sj 2144 6.05103 17.8804 -11.8294 0.424043
41 47 sj 840 5.80798 31.1695 -25.3615 0.420431
42 47 sj 841 3.49397 19.5741 -16.0802 0.409082
43 47 sj 2141 2.92318 38.3907 -35.4675 0.402829
44 47 sj 256 1.83133 26.0149 -24.1836 0.427329
45 47 sj 2643 0.779088 15.3464 -14.5673 0.465743
46 47 sj 1700 -2.72726 16.3189 -19.0462 0.393803
47 47 sj 2628 -2.99661 32.1254 -35.122 0.360628
1 36 mo 71 37.9779 16.0299 21.948 0.586637
2 36 mo 1806 36.1878 15.5192 20.6687 0.576504
3 36 mo 16 36.116 0.307612 35.8084 0.595453
4 36 mo 2041 31.3868 18.786 12.6008 0.564132
5 36 mo 1208 31.1796 17.8443 13.3353 0.598562
6 36 mo 2775 28.9725 15.0572 13.9153 0.521754
7 36 mo 931 25.4991 10.598 14.9011 0.534306
8 36 mo 1182 25.4692 16.667 8.80219 0.528031
9 36 mo 1756 24.4994 22.0488 2.45062 0.493673
10 36 mo 1723 21.9683 21.3416 0.626712 0.450238
11 36 mo 1094 21.1827 16.8607 4.32192 0.479213
12 36 mo 2359 20.8277 19.7527 1.07496 0.507964
13 36 mo 1098 20.4929 8.2615 12.2314 0.495869
14 36 mo 1985 18.4254 17.4859 0.939482 0.445339
15 36 mo 3000 18.0123 6.30271 11.7096 0.477899
16 36 mo 967 17.8547 17.5576 0.297086 0.480665
17 36 mo 1108 16.6244 18.6784 -2.05396 0.48572
18 36 mo 2838 16.2957 22.6653 -6.36961 0.455042
19 36 mo 1706 16.1269 18.7059 -2.57895 0.495682
20 36 mo 1288 15.2609 19.1133 -3.85246 0.506782
21 36 mo 1764 15.1048 14.5343 0.570547 0.500069
22 36 mo 2219 15.0992 9.30408 5.79511 0.479
23 36 mo 1444 15.0155 32.3548 -17.3393 0.496328
24 36 mo 1329 14.7137 21.3732 -6.65946 0.434345
25 36 mo 1996 14.1595 17.8385 -3.67901 0.47011
26 36 mo 2408 13.9313 24.6042 -10.6729 0.399923
27 36 mo 1810 13.0346 17.516 -4.48138 0.499806
28 36 mo 1785 12.7608 14.9993 -2.23846 0.495107
29 36 mo 2978 10.8089 21.2513 -10.4424 0.437453
30 36 mo 1178 9.64051 19.0837 -9.44316 0.487334
31 36 mo 2893 8.03822 30.6933 -22.655 0.424894
32 36 mo 2014 7.2016 22.9566 -15.755 0.420518
33 36 mo 2902 7.00998 22.2667 -15.2567 0.40278
34 36 mo 1827 6.24692 16.7328 -10.4859 0.403201
35 36 mo 1658 6.07659 21.3989 -15.3224 0.417103
36 36 mo 1609 3.79767 26.5086 -22.711 0.418915
1 65 dc 2199 44.7381 26.4954 18.2427 0.54878
2 65 dc 365 35.4451 13.8145 21.6306 0.544137
3 65 dc 45 34.3671 -0.726691 35.0938 0.628874
4 65 dc 2377 32.0478 7.85589 24.1919 0.586971
5 65 dc 234 31.5472 23.5264 8.02078 0.598432
6 65 dc 118 30.727 15.1605 15.5665 0.535552
7 65 dc 836 27.565 18.9007 8.66433 0.481981
8 65 dc 1712 27.5568 5.28298 22.2739 0.561063
9 65 dc 1731 26.9318 19.1679 7.76382 0.4934
10 65 dc 1629 26.9185 11.276 15.6425 0.601145
11 65 dc 176 26.655 10.9396 15.7154 0.5274
12 65 dc 7 25.9454 9.38115 16.5642 0.575194
13 65 dc 272 25.3673 7.42165 17.9457 0.560086
14 65 dc 181 24.4079 19.2291 5.17885 0.480753
15 65 dc 2913 24.1739 15.2211 8.9528 0.530175
16 65 dc 2068 23.9676 7.84333 16.1243 0.584332
17 65 dc 2914 23.9436 19.4936 4.44995 0.478768
18 65 dc 2819 23.2823 4.28493 18.9974 0.492058
19 65 dc 1446 23.2523 23.8498 -0.597452 0.475678
20 65 dc 346 23.1621 9.17419 13.9879 0.498394
21 65 dc 122 22.9188 14.545 8.37382 0.533987
22 65 dc 614 22.6642 23.4044 -0.740231 0.429759
23 65 dc 449 22.3897 14.7865 7.60315 0.514064
24 65 dc 597 22.3047 8.86159 13.4431 0.558768
25 65 dc 1915 21.4844 11.047 10.4374 0.464173
26 65 dc 2963 21.1232 28.7206 -7.59743 0.433479
27 65 dc 339 19.7606 13.958 5.80257 0.57182
28 65 dc 3046 19.4664 9.10023 10.3662 0.535237
29 65 dc 53 19.3212 -0.861838 20.1831 0.470603
30 65 dc 1418 19.03 12.9887 6.04136 0.477689
31 65 dc 623 18.3651 16.2989 2.06615 0.483582
32 65 dc 1748 18.3234 11.0597 7.2637 0.464164
33 65 dc 587 18.0707 32.2489 -14.1782 0.425138
34 65 dc 401 18.0203 27.0582 -9.03785 0.43698
35 65 dc 1872 17.5511 23.0072 -5.45606 0.476131
36 65 dc 1522 17.2399 29.6243 -12.3844 0.485544
37 65 dc 2962 14.2553 24.2086 -9.95332 0.458036
38 65 dc 2961 13.2068 19.9271 -6.72026 0.488266
39 65 dc 538 12.935 -4.48408 17.4191 0.538562
40 65 dc 2964 12.896 9.94122 2.95482 0.491389
41 65 dc 2729 12.6058 21.1071 -8.50136 0.473189
42 65 dc 116 12.5993 8.32355 4.27572 0.473464
43 65 dc 1279 11.9165 10.7602 1.15628 0.573791
44 65 dc 768 11.4372 3.38489 8.05236 0.557292
45 65 dc 1111 10.5388 12.739 -2.20024 0.528237
46 65 dc 1727 10.1372 12.4698 -2.33255 0.501269
47 65 dc 1123 9.80412 25.3721 -15.568 0.424765
48 65 dc 357 9.38413 22.1994 -12.8153 0.496796
49 65 dc 1719 9.0731 16.5207 -7.44758 0.480559
50 65 dc 2421 8.42457 32.753 -24.3285 0.445803
51 65 dc 1699 8.09539 13.4908 -5.39545 0.554125
52 65 dc 1370 7.41718 16.8962 -9.47897 0.422174
53 65 dc 620 7.21647 15.733 -8.51655 0.439243
54 65 dc 2912 6.69525 16.8889 -10.1937 0.411308
55 65 dc 709 6.68292 26.9818 -20.2989 0.471394
56 65 dc 2911 6.45493 9.02788 -2.57295 0.523621
57 65 dc 1793 6.36205 17.5136 -11.1516 0.481792
58 65 dc 611 5.56875 22.8221 -17.2534 0.496882
59 65 dc 2900 3.35319 40.8627 -37.5095 0.447112
60 65 dc 1900 1.20576 18.4986 -17.2929 0.515908
61 65 dc 2537 1.11876 20.5584 -19.4396 0.439072
62 65 dc 615 -0.028106 18.306 -18.3341 0.502807
63 65 dc 1885 -1.73993 28.6129 -30.3528 0.463633
64 65 dc 1849 -4.79702 31.9433 -36.7403 0.427352
65 65 dc 2121 -9.29036 30.2223 -39.5127 0.415447
1 26 wat 2056 45.2946 3.26659 42.028 0.619405
2 26 wat 2505 31.6984 16.0284 15.67 0.550544
3 26 wat 2609 29.8992 4.96614 24.9331 0.611085
4 26 wat 2166 29.6311 19.1076 10.5234 0.523142
5 26 wat 1310 29.1885 14.0056 15.1828 0.511708
6 26 wat 1565 24.6068 23.6854 0.921416 0.469516
7 26 wat 1141 24.3896 8.44865 15.9409 0.5543
8 26 wat 1334 20.7281 13.5408 7.18731 0.487226
9 26 wat 1605 20.589 32.9814 -12.3924 0.431665
10 26 wat 1404 19.988 20.412 -0.424002 0.484634
11 26 wat 296 17.7575 22.0404 -4.28295 0.484799
12 26 wat 1075 17.2582 17.3371 -0.0789062 0.45305
13 26 wat 2935 17.1391 18.3396 -1.2005 0.459652
14 26 wat 2013 16.0906 27.5001 -11.4096 0.431861
15 26 wat 3040 16.0734 23.2458 -7.1724 0.434361
16 26 wat 781 15.8749 23.328 -7.45307 0.514834
17 26 wat 1558 13.6615 10.5964 3.06507 0.539838
18 26 wat 854 13.1961 9.34128 3.85482 0.494201
19 26 wat 2076 12.0564 11.9147 0.141667 0.540698
20 26 wat 2702 11.3331 25.9218 -14.5888 0.446977
21 26 wat 1305 11.1759 22.1756 -10.9997 0.429965
22 26 wat 2185 10.6696 23.9122 -13.2426 0.419875
23 26 wat 1219 10.2456 31.66 -21.4144 0.41346
24 26 wat 2200 7.95397 17.5238 -9.56979 0.45503
25 26 wat 1815 7.95206 19.9957 -12.0436 0.444944
26 26 wat 2361 7.0519 16.4453 -9.39344 0.502156
1 53 wi 1625 43.3181 14.1392 29.1789 0.56705
2 53 wi 2970 40.7325 12.8175 27.915 0.586256
3 53 wi 2506 36.4193 17.7351 18.6842 0.6046
4 53 wi 2039 32.7118 11.8575 20.8544 0.616402
5 53 wi 1652 32.2436 7.29001 24.9535 0.577609
6 53 wi 2574 26.8989 19.3638 7.53512 0.510947
7 53 wi 2062 26.5823 26.4994 0.0829269 0.533216
8 53 wi 2481 26.5808 8.33083 18.2499 0.511548
9 53 wi 269 26.3146 18.6544 7.66026 0.505914
10 53 wi 2338 26.0467 15.5264 10.5202 0.535526
11 53 wi 1732 25.8536 6.05023 19.8034 0.568665
12 53 wi 537 25.741 23.6881 2.05281 0.496373
13 53 wi 1675 25.5683 11.6964 13.8719 0.542158
14 53 wi 1024 25.0322 12.2812 12.751 0.532676
15 53 wi 2826 22.9285 16.1218 6.80669 0.537601
16 53 wi 1736 22.3112 18.669 3.64211 0.552065
17 53 wi 1306 20.4494 23.4233 -2.97396 0.492255
18 53 wi 2547 20.2532 19.2461 1.00714 0.515308
19 53 wi 1535 19.9744 25.9736 -5.99921 0.474338
20 53 wi 2077 19.8092 31.1779 -11.3686 0.440965
21 53 wi 930 19.8076 24.4392 -4.63163 0.422531
22 53 wi 1714 19.5986 25.1057 -5.50712 0.53895
23 53 wi 1091 19.5165 17.1921 2.32441 0.48724
24 53 wi 2830 19.4411 18.3369 1.10429 0.500264
25 53 wi 1103 19.1883 20.9267 -1.73845 0.501341
26 53 wi 1739 18.8226 16.7907 2.03193 0.49109
27 53 wi 2194 18.7348 9.35077 9.38404 0.497074
28 53 wi 2530 18.5733 9.97496 8.59832 0.505108
29 53 wi 706 18.5719 24.7879 -6.21599 0.520609
30 53 wi 167 18.3031 14.4094 3.89371 0.558927
31 53 wi 2022 17.6402 19.9983 -2.35807 0.455575
32 53 wi 93 17.0298 19.1012 -2.07142 0.497988
33 53 wi 1850 15.8338 20.1154 -4.28166 0.514673
34 53 wi 1816 15.4916 6.24703 9.2446 0.561155
35 53 wi 2538 15.1215 22.5942 -7.47267 0.505955
36 53 wi 1259 14.4966 31.8558 -17.3592 0.398084
37 53 wi 1268 14.4813 8.45552 6.02582 0.529212
38 53 wi 2709 14.4743 27.8947 -13.4204 0.539525
39 53 wi 2817 14.3311 16.2528 -1.92171 0.477973
40 53 wi 141 13.9517 30.168 -16.2163 0.431778
41 53 wi 2940 13.9138 10.6178 3.29592 0.525089
42 53 wi 1864 10.555 30.6027 -20.0477 0.463051
43 53 wi 2549 10.5357 17.349 -6.81328 0.44839
44 53 wi 2437 10.2606 24.7207 -14.4601 0.40701
45 53 wi 2500 9.92773 25.0289 -15.1011 0.490232
46 53 wi 120 9.68168 18.69 -9.00828 0.44451
47 53 wi 2202 8.73271 26.5726 -17.8399 0.444039
48 53 wi 2116 8.32741 16.2094 -7.88203 0.488612
49 53 wi 2946 7.49635 15.494 -7.99768 0.399485
50 53 wi 3110 4.9799 24.6926 -19.7127 0.413946
51 53 wi 1716 2.42017 26.3927 -23.9726 0.411353
52 53 wi 447 0.986408 8.23944 -7.25303 0.497826
53 53 wi 171 -1.68947 17.5597 -19.2492 0.419462
1 40 dt1 67 50.9408 0.617258 50.3235 0.610938
2 40 dt1 1701 42.7287 -1.5429 44.2716 0.522997
3 40 dt1 217 38.8964 11.7323 27.1641 0.591317
4 40 dt1 1250 33.0338 16.0094 17.0244 0.550296
5 40 dt1 123 33.007 19.5863 13.4207 0.498937
6 40 dt1 280 29.0679 24.3662 4.70164 0.512084
7 40 dt1 503 26.1412 13.9333 12.2079 0.485986
8 40 dt1 1213 25.8765 17.6612 8.21529 0.49587
9 40 dt1 469 24.6276 18.0015 6.62607 0.465963
10 40 dt1 1856 24.247 16.1394 8.10754 0.503491
11 40 dt1 573 22.3855 17.8113 4.57423 0.515494
12 40 dt1 2851 22.0031 16.9111 5.09207 0.462879
13 40 dt1 2137 18.8976 12.7101 6.18746 0.510165
14 40 dt1 247 18.2062 13.8473 4.35885 0.475731
15 40 dt1 326 17.4643 6.39291 11.0714 0.527777
16 40 dt1 3098 17.1058 17.0529 0.0529156 0.474498
17 40 dt1 1998 17.0195 14.31 2.70948 0.519474
18 40 dt1 2431 16.8988 15.6144 1.28438 0.42871
19 40 dt1 453 16.612 8.09499 8.51703 0.509032
20 40 dt1 313 16.3467 15.8071 0.539601 0.469582
21 40 dt1 515 15.0104 17.1334 -2.12303 0.494462
22 40 dt1 2627 14.6539 22.4174 -7.76347 0.507613
23 40 dt1 2832 14.3867 8.90919 5.4775 0.525357
24 40 dt1 3095 14.2315 14.1329 0.0986253 0.497401
25 40 dt1 1528 13.8842 20.9135 -7.02929 0.484569
26 40 dt1 2048 13.4341 16.3903 -2.95624 0.449316
27 40 dt1 3069 13.2431 19.7851 -6.54203 0.467867
28 40 dt1 406 11.9244 25.3601 -13.4356 0.446086
29 40 dt1 1941 11.92 25.3079 -13.3879 0.447186
30 40 dt1 308 11.6373 15.8925 -4.25522 0.473001
31 40 dt1 3002 10.9996 22.4666 -11.4671 0.501085
32 40 dt1 519 10.0882 14.5831 -4.49482 0.43257
33 40 dt1 2224 8.58913 21.7994 -13.2103 0.408354
34 40 dt1 3096 7.52393 20.5767 -13.0527 0.413449
35 40 dt1 2673 6.44138 25.6906 -19.2492 0.504136
36 40 dt1 2719 5.32445 36.7354 -31.411 0.396716
37 40 dt1 903 4.99002 21.8457 -16.8556 0.427676
38 40 dt1 2050 3.90767 40.471 -36.5633 0.33891
39 40 dt1 240 2.4205 14.0401 -11.6197 0.45445
40 40 dt1 2676 0.883273 27.493 -26.6098 0.43456
1 40 dt 910 35.5577 10.321 25.2367 0.537777
2 40 dt 2719 28.8329 19.7821 9.05076 0.498642
3 40 dt 280 27.2832 19.5475 7.7357 0.524141
4 40 dt 3096 26.9987 25.8728 1.12588 0.485884
5 40 dt 1189 26.3344 11.8607 14.4738 0.496992
6 40 dt 66 25.9226 16.1788 9.74372 0.484259
7 40 dt 835 25.8593 19.8613 5.99796 0.514699
8 40 dt 548 25.6312 15.6208 10.0104 0.459084
9 40 dt 201 25.4676 8.56697 16.9006 0.546474
10 40 dt 1025 25.1448 13.8969 11.2479 0.507383
11 40 dt 2834 23.829 19.0759 4.75319 0.513109
12 40 dt 1941 23.3796 15.7977 7.58182 0.491303
13 40 dt 818 23.307 12.0746 11.2324 0.554686
14 40 dt 2612 21.7292 11.3571 10.3721 0.501915
15 40 dt 1856 21.3737 15.3534 6.02035 0.525987
16 40 dt 2224 18.7937 17.494 1.29969 0.445183
17 40 dt 226 18.4434 15.0442 3.39916 0.465704
18 40 dt 65 17.7981 24.7182 -6.92015 0.48187
19 40 dt 1998 17.6341 12.7485 4.88557 0.5442
20 40 dt 2620 17.4348 13.4513 3.98356 0.467937
21 40 dt 313 15.7424 17.7329 -1.9905 0.517442
22 40 dt 3115 15.0983 31.7064 -16.6081 0.424621
23 40 dt 440 15.0869 14.9817 0.105195 0.451003
24 40 dt 2960 14.7552 16.5601 -1.80484 0.494692
25 40 dt 406 14.518 18.3453 -3.82726 0.415868
26 40 dt 3097 14.323 24.3474 -10.0244 0.423383
27 40 dt 1602 13.7532 20.2706 -6.51738 0.429576
28 40 dt 815 13.6231 17.9885 -4.36541 0.446364
29 40 dt 2431 13.429 15.985 -2.55601 0.431771
30 40 dt 240 12.9145 10.7061 2.20836 0.456706
31 40 dt 2591 12.775 22.8753 -10.1004 0.43603
32 40 dt 3069 12.4615 18.8972 -6.43568 0.452611
33 40 dt 519 11.1622 9.0606 2.10159 0.515942
34 40 dt 1528 10.6025 17.9423 -7.3398 0.433042
35 40 dt 515 10.5205 14.3101 -3.78956 0.495811
36 40 dt 2048 10.2548 16.593 -6.33817 0.438943
37 40 dt 3002 8.44696 32.9278 -24.4809 0.393487
38 40 dt 2050 7.54353 32.3815 -24.838 0.372195
39 40 dt 3119 7.19737 19.4874 -12.29 0.484753
40 40 dt 903 5.87036 25.1104 -19.24 0.432343
1 40 gg 245 40.4226 3.78881 36.6338 0.597182
2 40 gg 862 34.3199 7.49911 26.8208 0.588873
3 40 gg 27 29.2825 15.1376 14.1448 0.522803
4 40 gg 107 27.2443 5.97075 21.2735 0.560995
5 40 gg 1718 25.6096 20.5286 5.08106 0.491427
6 40 gg 70 23.9959 17.3193 6.67661 0.557011
7 40 gg 910 23.8959 23.2087 0.687149 0.46969
8 40 gg 66 22.6589 30.6864 -8.02746 0.470058
9 40 gg 68 22.3997 21.0829 1.31686 0.519823
10 40 gg 1025 22.3589 14.0034 8.35552 0.492671
11 40 gg 33 21.5963 18.4356 3.16071 0.53408
12 40 gg 65 20.96 10.5997 10.3602 0.47164
13 40 gg 1504 19.6166 26.3629 -6.7463 0.564035
14 40 gg 1 19.49 7.79829 11.6917 0.557729
15 40 gg 494 18.5108 14.4711 4.0397 0.496397
16 40 gg 302 18.4788 22.2495 -3.77066 0.488952
17 40 gg 49 17.7741 18.0022 -0.22803 0.454551
18 40 gg 818 17.5764 12.6571 4.91925 0.54259
19 40 gg 470 16.7152 24.335 -7.61988 0.524587
20 40 gg 548 16.2421 11.7628 4.47931 0.521058
21 40 gg 2627 15.6175 15.6034 0.0141213 0.498963
22 40 gg 1783 15.1466 12.5846 2.562 0.472027
23 40 gg 322 14.9585 13.3784 1.58012 0.498935
24 40 gg 2771 13.7884 11.0618 2.72659 0.483655
25 40 gg 1506 13.0529 20.5716 -7.51866 0.482019
26 40 gg 1189 12.8654 9.19028 3.67517 0.458855
27 40 gg 2619 12.4849 14.6089 -2.12397 0.486126
28 40 gg 2586 11.7099 8.21228 3.49766 0.522234
29 40 gg 468 11.6667 27.5725 -15.9058 0.445217
30 40 gg 1243 11.4418 16.0925 -4.65069 0.48645
31 40 gg 1684 11.4111 12.8307 -1.41962 0.480898
32 40 gg 314 10.2534 18.6053 -8.35193 0.500271
33 40 gg 1322 10.0676 23.9148 -13.8472 0.425251
34 40 gg 894 9.56795 14.8368 -5.26887 0.489138
35 40 gg 830 8.68055 18.4143 -9.73378 0.433813
36 40 gg 2163 8.57121 21.3959 -12.8247 0.423808
37 40 gg 397 7.6006 27.6209 -20.0203 0.446081
38 40 gg 2337 7.47861 14.1012 -6.62254 0.49941
39 40 gg 3060 7.4171 27.8537 -20.4366 0.367256
40 40 gg 2145 6.82061 25.4004 -18.5798 0.422555
1 40 grl 67 55.2469 7.51402 47.7329 0.638985
2 40 grl 245 34.7433 10.3961 24.3472 0.555268
3 40 grl 1 33.8331 10.5596 23.2736 0.584339
4 40 grl 123 33.5941 18.8708 14.7233 0.547015
5 40 grl 27 31.4401 10.7528 20.6874 0.568272
6 40 grl 1918 29.1261 17.2071 11.919 0.567346
7 40 grl 830 26.7203 13.2407 13.4796 0.536276
8 40 grl 216 26.5022 20.528 5.97421 0.519121
9 40 grl 288 26.3743 21.6272 4.74708 0.497835
10 40 grl 68 25.4509 13.1846 12.2662 0.510322
11 40 grl 2767 23.7931 5.74618 18.0469 0.486587
12 40 grl 1502 23.6665 18.4988 5.16777 0.520743
13 40 grl 494 23.4166 16.3959 7.02063 0.51967
14 40 grl 2611 22.8294 16.2506 6.57885 0.506445
15 40 grl 2145 22.1357 28.1172 -5.98146 0.514586
16 40 grl 397 21.6306 6.49725 15.1334 0.519965
17 40 grl 1504 21.2198 16.7749 4.44483 0.493135
18 40 grl 1188 21.1108 25.4019 -4.29107 0.468237
19 40 grl 3098 21.0686 18.4115 2.65707 0.498693
20 40 grl 70 20.9052 26.499 -5.59381 0.490969
21 40 grl 470 20.3089 8.1799 12.129 0.475954
22 40 grl 3114 19.707 34.5496 -14.8425 0.447202
23 40 grl 2075 17.8825 13.007 4.87555 0.486414
24 40 grl 2337 15.618 15.7117 -0.0936665 0.454661
25 40 grl 94 14.7252 30.8881 -16.163 0.452818
26 40 grl 1711 14.56 12.1984 2.36161 0.47311
27 40 grl 894 13.334 16.5512 -3.21717 0.484706
28 40 grl 2054 11.6064 18.2229 -6.61653 0.503819
29 40 grl 1896 10.938 23.5407 -12.6028 0.475037
30 40 grl 2474 10.3984 19.0594 -8.66108 0.482165
31 40 grl 858 10.2203 25.4564 -15.2361 0.469755
32 40 grl 2617 10.0156 22.5479 -12.5324 0.495923
33 40 grl 2163 9.60457 21.5002 -11.8957 0.451222
34 40 grl 74 9.09085 34.5886 -25.4977 0.438922
35 40 grl 1940 9.05437 24.9715 -15.9171 0.415668
36 40 grl 1023 7.0082 23.553 -16.5448 0.433517
37 40 grl 2015 6.47701 29.3344 -22.8574 0.422543
38 40 grl 1677 6.37179 20.1779 -13.8061 0.489395
39 40 grl 518 5.72735 28.8765 -23.1492 0.457713
40 40 grl 468 5.71058 27.7771 -22.0666 0.40032
1 38 gt 85 34.5003 13.0162 21.4841 0.2701
2 38 gt 2612 26.5521 28.951 -2.3989 0.188356
3 38 gt 216 26.4229 26.6125 -0.189525 0.18575
4 38 gt 2188 25.7741 31.7306 -5.95649 0.20228
5 38 gt 2153 25.218 26.5453 -1.32739 0.225472
6 38 gt 2771 24.9264 22.2528 2.67356 0.207582
7 38 gt 314 24.8423 29.0949 -4.25261 0.205199
8 38 gt 1918 23.6647 17.6274 6.03731 0.22258
9 38 gt 1216 22.6535 22.2024 0.4511 0.223304
10 38 gt 904 22.6488 9.03411 13.6147 0.282008
11 38 gt 2245 22.2967 21.9019 0.394873 0.219428
12 38 gt 201 22.1252 21.1652 0.960045 0.22278
13 38 gt 2604 21.3618 22.2961 -0.934272 0.179473
14 38 gt 857 20.8829 18.6834 2.19949 0.206441
15 38 gt 1896 20.8817 27.5093 -6.62758 0.183782
16 38 gt 123 20.2003 12.5926 7.6077 0.276579
17 38 gt 2645 20.0962 11.9003 8.19591 0.288992
18 38 gt 1711 19.7153 23.2249 -3.50963 0.1672
19 38 gt 141 19.1799 21.1642 -1.98431 0.194807
20 38 gt 247 17.8614 14.9326 2.92882 0.196257
21 38 gt 1254 17.5119 22.7091 -5.19718 0.161648
22 38 gt 2586 17.3279 22.6134 -5.28551 0.21107
23 38 gt 1596 16.5429 11.8293 4.71354 0.242289
24 38 gt 47 16.2417 14.9793 1.26238 0.228351
25 38 gt 288 15.5272 16.5314 -1.00426 0.212958
26 38 gt 703 15.0539 12.9435 2.11043 0.261706
27 38 gt 2405 14.5561 14.9727 -0.416573 0.249425
28 38 gt 2246 14.2661 11.9693 2.2968 0.242575
29 38 gt 2834 12.3157 13.8618 -1.54603 0.27442
30 38 gt 3115 11.9433 10.757 1.18632 0.203442
31 38 gt 1506 11.7504 12.465 -0.714541 0.194483
32 38 gt 2619 11.4601 11.6635 -0.203398 0.224673
33 38 gt 1322 10.9926 14.9582 -3.96559 0.212876
34 38 gt 440 9.97468 16.0529 -6.07824 0.15921
35 38 gt 858 9.92487 22.7787 -12.8538 0.184561
36 38 gt 1783 9.09683 10.803 -1.70619 0.227196
37 38 gt 49 4.5987 8.45688 -3.85818 0.226823
38 38 gt 2959 4.27712 12.384 -8.10685 0.194281
1 40 oc 217 49.0695 16.2635 32.806 0.61046
2 40 oc 67 44.7387 11.5185 33.2202 0.580594
3 40 oc 68 37.167 17.8018 19.3652 0.520449
4 40 oc 469 35.1246 19.6071 15.5175 0.532866
5 40 oc 1250 33.6805 17.5031 16.1774 0.514874
6 40 oc 1701 33.588 11.465 22.123 0.54301
7 40 oc 910 31.1499 21.8166 9.33332 0.491751
8 40 oc 2591 25.8762 29.9904 -4.11423 0.441412
9 40 oc 226 25.5628 21.9705 3.59224 0.480194
10 40 oc 47 24.6242 14.8756 9.7486 0.491141
11 40 oc 326 24.4643 8.72201 15.7423 0.521246
12 40 oc 302 23.9714 16.2322 7.7392 0.559187
13 40 oc 1188 23.7041 18.6455 5.0586 0.515424
14 40 oc 94 23.3424 5.74291 17.5995 0.530423
15 40 oc 2620 23.0945 24.6762 -1.58176 0.458965
16 40 oc 2960 21.7904 22.5434 -0.753061 0.530287
17 40 oc 2832 20.5464 14.8352 5.71118 0.516582
18 40 oc 573 20.3691 12.565 7.80414 0.544857
19 40 oc 2137 20.3029 17.6766 2.62628 0.509342
20 40 oc 2337 18.4126 18.632 -0.219321 0.443533
21 40 oc 815 18.3168 18.4438 -0.126991 0.508941
22 40 oc 247 17.8926 17.9092 -0.0165773 0.513461
23 40 oc 2851 17.7348 24.8248 -7.09006 0.469875
24 40 oc 397 16.244 15.3137 0.930264 0.484158
25 40 oc 3095 15.434 22.1289 -6.69496 0.486585
26 40 oc 3119 15.3031 19.9706 -4.66745 0.509246
27 40 oc 1213 14.6797 20.2086 -5.5288 0.462395
28 40 oc 857 14.0266 22.4294 -8.40281 0.441267
29 40 oc 1596 13.3045 12.1852 1.11936 0.478216
30 40 oc 308 12.0962 11.37 0.726169 0.51206
31 40 oc 453 11.5128 29.3861 -17.8733 0.433522
32 40 oc 3114 11.1958 25.5479 -14.3521 0.483808
33 40 oc 2673 10.0655 35.6366 -25.5711 0.405442
34 40 oc 1684 9.83394 27.4708 -17.6368 0.386702
35 40 oc 1023 9.62352 28.2043 -18.5808 0.419068
36 40 oc 1216 9.0172 20.953 -11.9358 0.443011
37 40 oc 3060 8.74868 25.2834 -16.5347 0.41488
38 40 oc 2676 5.91581 29.9943 -24.0785 0.412843
39 40 oc 1602 4.9739 28.5293 -23.5554 0.435044
40 40 oc 3097 4.6675 22.2935 -17.6259 0.436997
1 39 mi 503 36.9697 4.32521 32.6445 0.604308
2 39 mi 1918 32.696 18.7109 13.9852 0.548224
3 39 mi 85 29.9544 13.6277 16.3267 0.571161
4 39 mi 904 29.3865 9.86426 19.5222 0.567356
5 39 mi 2612 28.3603 21.5925 6.76787 0.484545
6 39 mi 216 27.3627 15.935 11.4277 0.573908
7 39 mi 703 26.8705 14.8665 12.004 0.532895
8 39 mi 2474 24.6791 8.83762 15.8415 0.558996
9 39 mi 2075 23.7383 12.408 11.3303 0.472073
10 39 mi 141 22.3676 3.86282 18.5048 0.566496
11 39 mi 74 20.8496 19.5807 1.26892 0.475063
12 39 mi 2405 20.6428 17.8143 2.82847 0.447813
13 39 mi 1243 20.494 19.1729 1.3211 0.497207
14 39 mi 862 19.2779 13.4916 5.78626 0.526125
15 39 mi 2617 19.1051 24.6375 -5.53237 0.45652
16 39 mi 1504 19.0489 19.6574 -0.608494 0.496722
17 39 mi 2767 18.7602 18.9382 -0.177939 0.48677
18 39 mi 33 18.3202 22.7402 -4.42007 0.494654
19 39 mi 107 18.2105 21.551 -3.34058 0.450852
20 39 mi 1254 17.9691 16.8351 1.134 0.427096
21 39 mi 2645 17.9577 16.5935 1.3642 0.501548
22 39 mi 2771 17.8575 12.3416 5.51591 0.490398
23 39 mi 2246 17.6795 13.8413 3.83819 0.506735
24 39 mi 288 17.6524 30.3404 -12.688 0.45262
25 39 mi 1940 16.8409 17.3617 -0.520842 0.524135
26 39 mi 1718 15.0575 16.3011 -1.24354 0.513434
27 39 mi 2015 15.0271 16.9899 -1.96278 0.438304
28 39 mi 1502 14.3124 26.1921 -11.8797 0.411496
29 39 mi 548 14.183 20.8988 -6.71575 0.484791
30 39 mi 858 13.7794 26.764 -12.9846 0.466239
31 39 mi 518 11.7567 24.6309 -12.8741 0.446571
32 39 mi 2054 11.0412 19.6102 -8.56901 0.456556
33 39 mi 2604 10.5629 22.9612 -12.3983 0.403131
34 39 mi 1677 10.1022 23.1322 -13.03 0.438183
35 39 mi 322 9.98479 31.8518 -21.867 0.42483
36 39 mi 2611 8.76651 15.4064 -6.63985 0.451076
37 39 mi 2245 7.48425 29.8022 -22.3179 0.40639
38 39 mi 2959 5.56616 15.8671 -10.301 0.4522
39 39 mi 2188 5.24094 16.5809 -11.34 0.489169
Awesome job! This is a very cool and very powerful program. When used in conjunction with more detailed scouting reports this program could be very useful.
Gaurav27
30-03-2009, 23:06
Bongle, i understand how you show all results into command prompt.
However, the CP window automatically closes right after it outputs the results. Also, when i type: "oprnet all 2009 all r q > allRegionals.txt" it does not do anything but show all results, followed by immediately closing itself.
What is the problem here? Am i doing something wrong or missing out on some step?
familyguyfreak
30-03-2009, 23:35
hey this is really an awesome program. i have three questions.
1) if it's not much of a problem, you think you could incorporate a way to search for stats of specific teams by just entering their team number?
2) you think there is away to average a certain team's over all stats from all of the regionals they have participated in
3) will there be a way to use this program for championships?
awesome work and if its a hassel to any of those, don't stress. lol
thanks
engunneer
30-03-2009, 23:40
when i type: "oprnet all 2009 all r q > allRegionals.txt" it does not do anything but show all results, followed by immediately closing itself.
It ought to not show the results, but instead write them to the file called allRegionals.txt in the same folder as OPRNet. Are you actually typing quotes, or is that added just for the post?
familyguyfreak
30-03-2009, 23:40
oh...and one more thing...i think, if you could, try to rank all the teams in every regional based on the stats to see which team is the best out of everyone. it would help majorly in a lot of debates. lol
just another idea
Bongle, great work!
Pretty much repeating what everyone else has suggested, but with a methodology attached in case they're unclear :P
Can you load all the matches into one matrix and solve OPR/RPI from there?
By the way, before the all regional option got in there, I dumped them one by one and threw them into a spreadsheet, then did some other analysis by hand.
http://www.chiefdelphi.com/forums/showthread.php?t=76194&page=7
Interesting statistical points about the top 25 OPR:
Only 12 went on from setting that high OPR to win that regional.
Also, team 71's 63.55 OPR at the Midwest regional stands out beyond the rest, but their performance (which probably did involve quite a lot of scoring) didn't seem to add up to that. This is just an easy example of the inaccuracy possible in this analysis.
1) if it's not much of a problem, you think you could incorporate a way to search for stats of specific teams by just entering their team number?
2) you think there is away to average a certain team's over all stats from all of the regionals they have participated in
oh...and one more thing...i think, if you could, try to rank all the teams in every regional based on the stats to see which team is the best out of everyone. it would help majorly in a lot of debates. lol
The amount of programming needed to implement these features isn't that much, but the reason the stats all end up as tab-separated is so that you can copy-paste into excel, and sort by any parameter you want.
3) will there be a way to use this program for championships?
Currently, the divisions are available as 'regionals'. You just need to type cur, arc, new, or gal to output that data.
Bongle, i understand how you show all results into command prompt.
However, the CP window automatically closes right after it outputs the results. Also, when i type: "oprnet all 2009 all r q > allRegionals.txt" it does not do anything but show all results, followed by immediately closing itself.
What is the problem here? Am i doing something wrong or missing out on some step?
Try launching it from the actual command prompt (start->run->cmd), or try making a .bat file in the same directory, putting "oprnet all 2009 all r q > allregionals.txt" in it, then launching that. All the data should end up in a text file call allRegionals.txt. Of course, it is kind of redundant: all the regional data is available in my post.
Anders Horn
03-04-2009, 19:39
I had my brother write a very similar program before I knew this one existed, one way we tested our results was by using the stats we calculated to predict what the results of matches would be.
In our program offensive score had some predictive power but defense had no relation to reality.
Did you find differently when you tested your results?
[our graphs if you want to analyze them yourself] http://kamocat.com/scouting/moredata.html
Gaurav27
05-04-2009, 13:16
Thanks for all your help Bongle! I finally got it. :)
Below is the attachment to AllRegionals' data.
There are all entries and NOT averages of each team's data, which is what I have to work on.
There's a master worksheet with all entries and all regionals' worksheets seperately.
Please let me know if there are any defects in the spreadsheet.
Thanks once again, Bongle for all the help. I hope it comes in handy for teams attending World's!
Chief Pride
08-04-2009, 21:46
Is it just me or is Dallas not working?
Edit: It seems BAE isnt working also...
Joe Ross
09-04-2009, 15:36
Has anyone tried to combine the matches from all regionals into one giant matrix, and solve that?
It took me a little while but here is a Mac version of an OPR program. Requires OS X version 10.5.
Michael Corsetto
11-05-2009, 19:46
It took me a little while but here is a Mac version of an OPR program. Requires OS X version 10.5.
This is great, thanks for putting the time in to making this thing work! One general recommendation, could you have a column on the left that always has the numbers 1-X(however many teams there are) so you know where each team ranks? Looks great though, hopefully this application can be adapted to next years game fairly quickly!
Bump: Thanks to FIRST not updating the format of the online results this year, I just want to point out that OPRNet (and I'm assuming the other implementations) work in 2010 as well.
Notable rankings:
1114 [Pittsburgh]: 6.8
63 [Pittsburgh]: 3.7
217 [Cass Tech]: 4.9
469 [Cass Tech]: 2.4 (this seems low, but it is probably because 469 is dependent on good alliance partners supplying it with balls, so it quals they probably end up with lower effectiveness)
billbo911
15-03-2010, 10:25
Fantastic!!
I was about to dig out your code to see if it would work this year as well. We used it last year with excellent results.
Now that we know it works, you can count on us using it again this year. All we have to do is wait until week 5.
Nawaid Ladak
15-03-2010, 10:38
It worked last weekend when i was using it at the Florida regional. The only part that bugs me is the "predict" section. you have to predict the seeding score by yourself because it still does it in WLT format.
fordchrist675
15-03-2010, 13:14
I love this program, our team has done something similar to this.
It tells you everything you really need to know and you don't need the extra stuff.
Great job.
It worked last weekend when i was using it at the Florida regional. The only part that bugs me is the "predict" section. you have to predict the seeding score by yourself because it still does it in WLT format.
I can take a look at fixing it, but I misplaced the source code (and didn't attach anything beyond v6), so the best I can do is work from v6, unless there are people I PMed source code to post-v6.
It needs updating anyway, because the regional list won't work with new or name-changed regionals.
The Lucas
15-03-2010, 13:52
I can take a look at fixing it, but I misplaced the source code (and didn't attach anything beyond v6), so the best I can do is work from v6, unless there are people I PMed source code to post-v6.
It needs updating anyway, because the regional list won't work with new or name-changed regionals.
You released v7 in this post (http://www.chiefdelphi.com/forums/showpost.php?p=835778&postcount=95). I guess me bugging you for source was good for something :D I found out there was wifi at Philly so I never implemented the offline option. Plus I've never done .NET programming so I didnt want to setup the environment.
Kristian Calhoun
15-03-2010, 15:24
It took me a little while but here is a Mac version of an OPR program. Requires OS X version 10.5.
Thanks for the Mac Version!
I just ran the data for the 2010 New Jersey Regional and figured I would post the results:
Seed Team # OPR SAA +/-
1 25 6.401610347932085 1.063761665157571 5.337849
2 422 2.254846421054722 0.7917893261239222 1.463057
3 303 3.496353780535462 0.4103956967706686 3.085958
4 709 0.2485902762437386 1.536787881146741 -1.288198
5 1923 1.918282483508905 1.922396766589092 -0.00411427
6 1672 1.974737752942523 0.145660464866258 1.829077
7 1279 1.764929841307056 -0.7990712317406506 2.564001
8 870 2.306026742135704 0.4803629631386594 1.825664
9 1676 2.627860402464438 0.8595179597767183 1.768342
10 2590 1.793287315868592 1.595875809285964 0.1974114
11 224 2.126467393765244 0.404411786991265 1.722056
12 75 0.5341691967227997 3.050175689151065 -2.516006
13 2607 0.1817870568086065 -0.3960684230867369 0.5778555
14 41 0.1071730804421981 0.2937202426748263 -0.1865472
15 223 0.9125425049561782 2.684162332647792 -1.77162
16 293 1.343841815595809 -0.6223732204944771 1.966215
17 2016 2.317256967356212 -0.3417684318910283 2.659025
18 486 1.948404416357168 3.008755289210832 -1.060351
19 1807 1.004704265868846 -0.2484066556456418 1.253111
20 1860 1.303983370258202 0.4375293174088174 0.866454
21 752 1.3930097675295 0.1210917747787422 1.271918
22 1089 2.153812997671896 -0.06564317367935771 2.219456
23 56 2.287472736963714 0.926848060399948 1.360625
24 2458 1.085208077846458 1.485165988031718 -0.3999579
25 2495 2.445740166507706 0.4188788716105148 2.026861
26 613 1.254155978305673 0.3131623267842687 0.9409937
27 11 1.334384863419665 1.497880377670121 -0.1634954
28 555 1.028491286566071 0.3666698271910944 0.6618214
29 834 1.728689547460161 1.581988392511743 0.1467012
30 714 0.2673804821596022 2.739851557976847 -2.472471
31 1382 -0.007066540361709374 1.047449972942374 -1.054516
32 2753 1.362336571039709 1.584438935913565 -0.2221024
33 3231 0.419863715229353 0.2492343170053663 0.1706294
34 2265 -0.1358273933803141 2.350029461714916 -2.485857
35 2180 2.545235952008568 0.6989073588089524 1.846328
36 136 0.3731544889568303 2.815498787535494 -2.442344
37 1811 1.329742352966351 -0.2654778563890701 1.59522
38 237 0.1178980688713144 1.898895509854473 -1.780997
39 1872 0.9973754594635658 0.02779847880451964 0.969577
40 219 1.800412973538224 1.026869103774027 0.773544
41 2577 -0.1916628984180219 -0.04636067284746017 -0.1453022
42 1563 -0.6626363464787126 -0.4251070350894005 -0.2375293
43 423 -0.4151511338057186 2.51051314820927 -2.925664
44 335 -0.05660564155512169 1.108022104372928 -1.164628
45 3059 0.4553537370670253 1.146883582393113 -0.6915299
46 2344 0.2505583401530093 0.8191699560066874 -0.5686116
47 102 0.7022521040889705 0.3263160644703582 0.375936
48 816 1.382543581738802 1.073104347670353 0.3094392
49 869 -0.1213719904748385 1.349761953271257 -1.471134
50 2191 -1.316450896185367 2.796712713236501 -4.113163
51 1881 1.080428706697298 0.2303600472853828 0.8500687
52 1616 -0.1920799853403433 0.9075870552225288 -1.099667
53 203 0.6275316516882863 0.8703176484238624 -0.242786
54 1367 -0.2715298497986134 1.007171281871124 -1.278701
55 1257 -1.066110954290831 0.7775186804097176 -1.84363
56 1155 -0.6725974579240466 2.948571076342111 -3.621168
57 3314 0.00202229424332078 -0.8444811451892285 0.8465034
58 2600 -1.113662998481091 1.059702426510045 -2.173365
59 1228 -0.204278883337306 1.781750566926853 -1.986029
60 1403 -0.580624049583941 0.8869603075379122 -1.467584
61 2789 -0.7434964315856768 0.05580599710176955 -0.7993024
cziggy343
15-03-2010, 22:31
anyway that someone could post this info for the florida regional? :)
Bigcheese
16-03-2010, 00:20
You released v7 in this post (http://www.chiefdelphi.com/forums/showpost.php?p=835778&postcount=95). I guess me bugging you for source was good for something :D I found out there was wifi at Philly so I never implemented the offline option. Plus I've never done .NET programming so I didnt want to setup the environment.
It's not .NET. It's a simple Windows Console program. Good ol' C++.
billbo911
16-03-2010, 02:18
anyway that someone could post this info for the florida regional? :)
As requested.
Pos Reg Team OPR SAA PM
1 fl 1592 5.03224 1.24397 3.78827 0.585938
2 fl 179 4.13721 0.742135 3.39508 0.561606
3 fl 1065 3.88558 1.04967 2.83592 0.533653
4 fl 103 3.38683 -1.15054 4.53737 0.563721
5 fl 86 2.95725 -0.094547 3.05179 0.579361
6 fl 1345 2.76322 0.294283 2.46894 0.534846
7 fl 386 2.75877 1.01765 1.74112 0.49888
8 fl 69 2.51997 1.88496 0.63501 0.500446
9 fl 343 2.414 1.19305 1.22095 0.520403
10 fl 1902 2.3262 0.893034 1.43317 0.449398
11 fl 1612 2.2989 0.864216 1.43469 0.546353
12 fl 1649 2.16378 -0.409722 2.5735 0.526357
13 fl 945 2.15929 0.957908 1.20138 0.502232
14 fl 801 1.99003 2.02116 -0.0311221 0.448412
15 fl 2425 1.9703 2.09285 -0.122547 0.475432
16 fl 1557 1.95257 1.50568 0.446892 0.473086
17 fl 744 1.83611 1.03206 0.804051 0.514185
18 fl 442 1.64027 0.22 1.42027 0.465133
19 fl 180 1.61842 0.674641 0.943779 0.48149
20 fl 364 1.60951 0.934307 0.6752 0.478197
21 fl 79 1.60742 -0.212951 1.82037 0.469588
22 fl 1144 1.5017 2.2469 -0.745207 0.49574
23 fl 2564 1.49668 1.35369 0.142988 0.45793
24 fl 2729 1.44323 2.17198 -0.728746 0.464723
25 fl 665 1.4023 2.96434 -1.56204 0.463978
26 fl 1523 1.14791 1.21078 -0.0628724 0.508035
27 fl 2483 1.05684 1.1391 -0.0822591 0.512172
28 fl 1102 0.990982 2.92717 -1.93619 0.405318
29 fl 233 0.983991 -0.226166 1.21016 0.514574
30 fl 118 0.979039 2.35481 -1.37577 0.486781
31 fl 1876 0.860311 0.530326 0.329985 0.380229
32 fl 3164 0.745038 2.10099 -1.35596 0.461521
33 fl 1270 0.714899 1.42364 -0.708741 0.442476
34 fl 3149 0.646925 1.51433 -0.867409 0.387674
35 fl 1543 0.635379 0.184985 0.450394 0.507527
36 fl 2757 0.596436 2.95641 -2.35997 0.433238
37 fl 3332 0.592347 -1.10186 1.69421 0.509816
38 fl 2152 0.543008 -0.302732 0.84574 0.439497
39 fl 2023 0.161071 0.890905 -0.729834 0.473019
40 fl 1251 0.132449 0.930066 -0.797617 0.440771
41 fl 2797 0.0772379 2.24386 -2.16662 0.445741
42 fl 2916 -0.0235663 1.99863 -2.0222 0.461513
43 fl 1369 -0.0526677 2.00756 -2.06023 0.406847
44 fl 3376 -0.0678656 2.51899 -2.58686 0.429551
45 fl 168 -0.181792 0.215763 -0.397556 0.471395
46 fl 3242 -0.39675 1.78542 -2.18217 0.429955
47 fl 1859 -0.510264 0.70999 -1.22025 0.409151
48 fl 1875 -0.551142 2.09859 -2.64973 0.456348
49 fl 1390 -0.688922 2.17895 -2.86787 0.390113
50 fl 108 -0.704005 2.22552 -2.92953 0.38198
51 fl 2383 -0.767259 0.975299 -1.74256 0.460403
52 fl 21 -0.880018 0.755322 -1.63534 0.391082
53 fl 408 -1.77172 1.47511 -3.24683 0.385777
The Lucas
16-03-2010, 13:12
It's not .NET. It's a simple Windows Console program. Good ol' C++.
I didn't really look at the code. I know it requires .NET to run after helping install it on scouting laptops last year and figured that was why it was named OprNET. I do most programming in my Linux boot and I still havent installed Visual Studio Express like my old laptop (which I used to work with the Bongle's old '08 OPR code (http://www.chiefdelphi.com/forums/showpost.php?p=732341&postcount=146) among other things). I'm glad that team update 16 made OPR relevant again (though it is still not a great fit for the game)
I didn't really look at the code. I know it requires .NET to run after helping install it on scouting laptops last year and figured that was why it was named OprNET. I do most programming in my Linux boot and I still havent installed Visual Studio Express like my old laptop (which I used to work with the Bongle's old '08 OPR code (http://www.chiefdelphi.com/forums/showpost.php?p=732341&postcount=146) among other things). I'm glad that team update 16 made OPR relevant again (though it is still not a great fit for the game)
It should just require the MSVC runtimes (I think, I'm not good at this redistributing thing), which I imagine are included in the .NET distributable. Probably won't help with your linux needs though, since it uses the Win32 WinINet functions rather than an OSS standard.
I called it OPRNet because it was (inter)net-capable, rather than having the user manually create text files to parse.
fordchrist675
16-03-2010, 13:53
I have a question about Oregon for 2010. I was trying to find out opr and pm for teams at OR this year. and it failed. any ideas?
I have a question about Oregon for 2010. I was trying to find out opr and pm for teams at OR this year. and it failed. any ideas?
Mine failed from USFIRST but managed to use TBA as a backup.
Pos Reg Team OPR SAA PM RPI
1 or 997 4.44 2.997 1.443 0.2869
2 or 753 3.342 2.472 0.8707 0.2321
3 or 3165 3.214 2.257 0.9566 0.2528
4 or 1540 2.621 1.439 1.182 0.2585
5 or 3192 2.537 2.571-0.03447 0.1906
6 or 2910 2.168 0.6331 1.535 0.2883
7 or 2865 2.045 2.172 -0.1265 0.1994
8 or 948 1.979 2.207 -0.2276 0.2096
9 or 2471 1.975 1.27 0.7048 0.2358
10 or 1432 1.922 1.494 0.4277 0.213
11 or 368 1.915 2.293 -0.3781 0.2302
12 or 8 1.825 1.703 0.1226 0.271
13 or 3145 1.814 1.986 -0.1718 0.2204
14 or 957 1.791 2.599 -0.8078 0.1842
15 or 847 1.709 0.6439 1.066 0.2785
16 or 2811 1.701 0.1783 1.522 0.3023
17 or 3223 1.692 1.6860.005676 0.2277
18 or 2046 1.685 1.653 0.03189 0.1667
19 or 1983 1.631 0.7979 0.8326 0.2701
20 or 2557 1.466 0.9125 0.5539 0.3004
21 or 488 1.444 1.262 0.1814 0.2307
22 or 2733 1.373 1.67 -0.2969 0.2069
23 or 2130 1.37 1.268 0.1024 0.2588
24 or 3024 1.366 2.677 -1.312 0.1901
25 or 1595 1.33 2.216 -0.8864 0.2402
26 or 949 1.251 2.401 -1.15 0.2016
27 or 1823 1.191 1.527 -0.336 0.2294
28 or 2542 1.172 1.343 -0.1711 0.2331
29 or 1700 1.089 1.579 -0.4898 0.2202
30 or 3131 1.004 1.263 -0.259 0.1614
31 or 3210 0.938 0.4483 0.4896 0.2581
32 or 2374 0.914 0.3753 0.5387 0.255
33 or 2951 0.8851 2.232 -1.347 0.1808
34 or 1515 0.8275 0.6605 0.167 0.177
35 or 2147 0.7307 1.34 -0.6097 0.2248
36 or 2002 0.6813 0.3311 0.3502 0.2314
37 or 1510 0.6691 0.7407-0.07164 0.2381
38 or 2605 0.6604 1.997 -1.337 0.2139
39 or 1425 0.5979 1.283 -0.685 0.2014
40 or 2517 0.5943 0.2731 0.3212 0.2188
41 or 3070 0.5522 0.4322 0.12 0.2002
42 or 2898 0.5402 0.4317 0.1084 0.2305
43 or 2522 0.5236 0.7541 -0.2305 0.199
44 or 2192 0.5206 0.8281 -0.3075 0.2332
45 or 955 0.5094 0.50780.001674 0.2162
46 or 3311 0.4487 -0.1401 0.5888 0.1892
47 or 2922 0.4001 1.29 -0.8898 0.221
48 or 2411 0.3854 0.5043 -0.119 0.2797
49 or 3188 0.3425 0.7973 -0.4548 0.2466
50 or 2915 0.3389 -0.1069 0.4458 0.2668
51 or 2550 0.2831 0.6419 -0.3587 0.2233
52 or 3213 0.2749 0.5467 -0.2718 0.2069
53 or 1571 0.2742 -0.2833 0.5575 0.218
54 or 956 0.2567 0.5675 -0.3108 0.2512
55 or 2521 0.07498-0.08733 0.1623 0.2696
56 or 3600.008782 -0.4343 0.4431 0.2718
57 or 2635 -0.1431 0.3721 -0.5152 0.1756
58 or 2990 -0.1594 -0.3548 0.1954 0.2182
59 or 1778 -0.2436 0.6652 -0.9088 0.1684
60 or 3013 -0.3261 -0.2129 -0.1132 0.2016
61 or 1318 -0.7963-0.01821 -0.7781 0.2565
fordchrist675
16-03-2010, 14:17
Mine failed from USFIRST but managed to use TBA as a backup.
Pos Reg Team OPR SAA PM RPI
1 or 997 4.44 2.997 1.443 0.2869
2 or 753 3.342 2.472 0.8707 0.2321
3 or 3165 3.214 2.257 0.9566 0.2528
4 or 1540 2.621 1.439 1.182 0.2585
5 or 3192 2.537 2.571-0.03447 0.1906
6 or 2910 2.168 0.6331 1.535 0.2883
7 or 2865 2.045 2.172 -0.1265 0.1994
8 or 948 1.979 2.207 -0.2276 0.2096
9 or 2471 1.975 1.27 0.7048 0.2358
10 or 1432 1.922 1.494 0.4277 0.213
11 or 368 1.915 2.293 -0.3781 0.2302
12 or 8 1.825 1.703 0.1226 0.271
13 or 3145 1.814 1.986 -0.1718 0.2204
14 or 957 1.791 2.599 -0.8078 0.1842
15 or 847 1.709 0.6439 1.066 0.2785
16 or 2811 1.701 0.1783 1.522 0.3023
17 or 3223 1.692 1.6860.005676 0.2277
18 or 2046 1.685 1.653 0.03189 0.1667
19 or 1983 1.631 0.7979 0.8326 0.2701
20 or 2557 1.466 0.9125 0.5539 0.3004
21 or 488 1.444 1.262 0.1814 0.2307
22 or 2733 1.373 1.67 -0.2969 0.2069
23 or 2130 1.37 1.268 0.1024 0.2588
24 or 3024 1.366 2.677 -1.312 0.1901
25 or 1595 1.33 2.216 -0.8864 0.2402
26 or 949 1.251 2.401 -1.15 0.2016
27 or 1823 1.191 1.527 -0.336 0.2294
28 or 2542 1.172 1.343 -0.1711 0.2331
29 or 1700 1.089 1.579 -0.4898 0.2202
30 or 3131 1.004 1.263 -0.259 0.1614
31 or 3210 0.938 0.4483 0.4896 0.2581
32 or 2374 0.914 0.3753 0.5387 0.255
33 or 2951 0.8851 2.232 -1.347 0.1808
34 or 1515 0.8275 0.6605 0.167 0.177
35 or 2147 0.7307 1.34 -0.6097 0.2248
36 or 2002 0.6813 0.3311 0.3502 0.2314
37 or 1510 0.6691 0.7407-0.07164 0.2381
38 or 2605 0.6604 1.997 -1.337 0.2139
39 or 1425 0.5979 1.283 -0.685 0.2014
40 or 2517 0.5943 0.2731 0.3212 0.2188
41 or 3070 0.5522 0.4322 0.12 0.2002
42 or 2898 0.5402 0.4317 0.1084 0.2305
43 or 2522 0.5236 0.7541 -0.2305 0.199
44 or 2192 0.5206 0.8281 -0.3075 0.2332
45 or 955 0.5094 0.50780.001674 0.2162
46 or 3311 0.4487 -0.1401 0.5888 0.1892
47 or 2922 0.4001 1.29 -0.8898 0.221
48 or 2411 0.3854 0.5043 -0.119 0.2797
49 or 3188 0.3425 0.7973 -0.4548 0.2466
50 or 2915 0.3389 -0.1069 0.4458 0.2668
51 or 2550 0.2831 0.6419 -0.3587 0.2233
52 or 3213 0.2749 0.5467 -0.2718 0.2069
53 or 1571 0.2742 -0.2833 0.5575 0.218
54 or 956 0.2567 0.5675 -0.3108 0.2512
55 or 2521 0.07498-0.08733 0.1623 0.2696
56 or 3600.008782 -0.4343 0.4431 0.2718
57 or 2635 -0.1431 0.3721 -0.5152 0.1756
58 or 2990 -0.1594 -0.3548 0.1954 0.2182
59 or 1778 -0.2436 0.6652 -0.9088 0.1684
60 or 3013 -0.3261 -0.2129 -0.1132 0.2016
61 or 1318 -0.7963-0.01821 -0.7781 0.2565
Thank you oh so very much :D
The Lucas
16-03-2010, 14:19
It should just require the MSVC runtimes (I think, I'm not good at this redistributing thing), which I imagine are included in the .NET distributable. Probably won't help with your linux needs though, since it uses the Win32 WinINet functions rather than an OSS standard.
I called it OPRNet because it was (inter)net-capable, rather than having the user manually create text files to parse.
OK, that explains the name. Installing .NET is probably a simple solution for people having trouble running OPRNet (particularly on old XP laptops).
Also, I dont want/need a Linux version, the Windows version is great. Thanks Bongle! I have a dual boot machine and the Windows boot is what I use at competitions anyway to run Windriver, Excel and save my battery. Windows is the right choice since all of the KOP software is Windows.
cziggy343
16-03-2010, 14:37
As requested.
thank you! :D
Jacob Plicque
16-03-2010, 16:39
Did the OPR miss the mark for the Florida Regional? The alliance of 1251 + 1612 + 86 won the whole shebang with a combined OPR of 5.4 versus alliances with group OPRs of 9.9, 9.2, 7.1, 6.4, 5.6, 5.2, and 5.10. If OPR were a good predictor wouldn't the team of 1592 + 179 + 3164 be a virtual lock with a group OPR of 9.9? In the past OPR usually was a good indicator of the strongest alliance in the elimination rounds. In the Quarterfinals, the top three teams by group OPR were knocked off.
billbo911
16-03-2010, 17:10
Did the OPR miss the mark for the Florida Regional? The alliance of 1251 + 1612 + 86 won the whole shebang with a combined OPR of 5.4 versus alliances with group OPRs of 9.9, 9.2, 7.1, 6.4, 5.6, 5.2, and 5.10. If OPR were a good predictor wouldn't the team of 1592 + 179 + 3164 be a virtual lock with a group OPR of 9.9? In the past OPR usually was a good indicator of the strongest alliance in the elimination rounds. In the Quarterfinals, the top three teams by group OPR were knocked off.
Great observation.
You need to understand, OPR is just one tool to help you decide. I'll bet in qualifications, 1251, 1612 and 86 were not able to compete along side teams that would compliment their game strategies or abilities. Look at it as a perfect storm. When you bring three teams together that fully complimented each others abilities and were able to play as a single unit, their performance as an alliance would be way better than they were able to show individually during qualifications.
This is why raw numbers is not always your best predictor. Observation and paying attention to all input is a scout's best approach. Leaning on one detail, like OPR, can be mis-leading.
Another reason OPR might be a poor elimination predictor is because the rules essentially change in eliminations.
In qualifying, it isn't really in anyone's interest for teams to play heavy-handed defense. In eliminations, defense is a key factor. So teams with a pneumatic-tire 8-motor, rocket-powered 8WD suddenly are much more useful, while teams with highly mobile feather-light (and light on grip, like mechanum/omni) robots suddenly find it much harder to score.
A perfect example is 469: they have a low OPR (well... compared to their reputation) because they are only at maximum effectiveness when they're playing with highly effective robots that can get their ball loop going. In qualifying, that might not happen often. An ball-supplier bot is limited in offensive power by its home-zone teammate that is trying to get balls in the net. 469 is a defense-proof near-perfect ball supplier. When defense ramps up and solid ball-deliverers become available, suddenly 469 is an unstoppable force.
Jacob Plicque
17-03-2010, 21:58
At the Oregon, New Jersey, and Pittsburgh regionals, the alliances with the best OPR were the winners. Over the years, it has been consistant that the OPR team score was a 90%ile indicator of sucess. Bongle makes a great point about the defense as the 1251+1612+86 alliance was the number 2 rated defense in the eliminations. I am curious about how many of the regional winning teams were predicted by OPR for weeks 1 & 2 in 2010. At a glance, Florida seems the exception.:confused:
Also, OPR cannot take into account teams that are playing the "seeding points game" by scoring goals for their opponents. There are several very high performing teams I know of that have abysmal OPRs for this reason - because 2 or 3 times a match they were scoring for the other alliance. That's a huge hit to your OPR, SAA and ultimately your PM.
Nawaid Ladak
17-03-2010, 22:30
I think you need to take a look at all four stats to determine who the best robot is on the field.
High OPR + Unusually High SAA + mediocre PM + Strong RPI = a really good robot
High OPR + Low SAA + strong PM + Strong RPI = Good Robot
thats how i look at the stats.
Jacob Plicque
18-03-2010, 00:17
I have not used RPI in the past since it has such a narrow range of data like 0.16 to 0.40. Obviously higher is better as an indicator of strength of schedule and wins. However its relationship to OPR, DPR, & PM is not easy to compare since these valus are often 20 times larger
I noticed this weekend that this is the year of the prediction feature. Running it for KC, the self-check indicates it would have been 70% correct after only 39 matches, and consistently 80% correct after 48 matches. For Lunacy it does much worse. This seems to indicate that this game is much more predictable, and that good robots in one match will often do well in subsequent matches. Note that this is only for predicting the winner. So although it is better at predicting the winner of a match than last year, that's a less useful thing to do than it was last year.
After 10 matches, OPR would not have been computable
After 11 matches, OPR would not have been computable
After 12 matches, OPR would not have been computable
After 13 matches, OPR would not have been computable
After 14 matches, OPR would not have been computable
After 15 matches, OPR would not have been computable
After 16 matches, OPR would not have been computable
After 17 matches, OPR would not have been computable
After 18 matches, OPR would not have been computable
After 19 matches, OPR would not have been computable
With 20 matches of data, match prediction would have been 50% of the time
With 21 matches of data, match prediction would have been 56% of the time
With 22 matches of data, match prediction would have been 48% of the time
With 23 matches of data, match prediction would have been 63% of the time
With 24 matches of data, match prediction would have been 62% of the time
With 25 matches of data, match prediction would have been 55% of the time
With 26 matches of data, match prediction would have been 58% of the time
With 27 matches of data, match prediction would have been 50% of the time
With 28 matches of data, match prediction would have been 67% of the time
With 29 matches of data, match prediction would have been 50% of the time
With 30 matches of data, match prediction would have been 50% of the time
With 31 matches of data, match prediction would have been 52% of the time
With 32 matches of data, match prediction would have been 61% of the time
With 33 matches of data, match prediction would have been 69% of the time
With 34 matches of data, match prediction would have been 64% of the time
With 35 matches of data, match prediction would have been 60% of the time
With 36 matches of data, match prediction would have been 66% of the time
With 37 matches of data, match prediction would have been 66% of the time
With 38 matches of data, match prediction would have been 65% of the time
With 39 matches of data, match prediction would have been 71% of the time
With 40 matches of data, match prediction would have been 71% of the time
With 41 matches of data, match prediction would have been 77% of the time
With 42 matches of data, match prediction would have been 80% of the time
With 43 matches of data, match prediction would have been 75% of the time
With 44 matches of data, match prediction would have been 76% of the time
With 45 matches of data, match prediction would have been 74% of the time
With 46 matches of data, match prediction would have been 73% of the time
With 47 matches of data, match prediction would have been 75% of the time
With 48 matches of data, match prediction would have been 82% of the time
With 49 matches of data, match prediction would have been 80% of the time
With 50 matches of data, match prediction would have been 83% of the time
With 51 matches of data, match prediction would have been 87% of the time
With 52 matches of data, match prediction would have been 87% of the time
With 53 matches of data, match prediction would have been 78% of the time
With 54 matches of data, match prediction would have been 80% of the time
With 55 matches of data, match prediction would have been 77% of the time
With 56 matches of data, match prediction would have been 74% of the time
With 57 matches of data, match prediction would have been 73% of the time
With 58 matches of data, match prediction would have been 75% of the time
With 59 matches of data, match prediction would have been 75% of the time
With 60 matches of data, match prediction would have been 84% of the time
With 61 matches of data, match prediction would have been 81% of the time
With 62 matches of data, match prediction would have been 83% of the time
With 63 matches of data, match prediction would have been 80% of the time
With 64 matches of data, match prediction would have been 88% of the time
With 65 matches of data, match prediction would have been 88% of the time
With 66 matches of data, match prediction would have been 84% of the time
With 67 matches of data, match prediction would have been 81% of the time
With 68 matches of data, match prediction would have been 87% of the time
With 69 matches of data, match prediction would have been 86% of the time
With 70 matches of data, match prediction would have been 86% of the time
With 71 matches of data, match prediction would have been 85% of the time
With 72 matches of data, match prediction would have been 85% of the time
With 73 matches of data, match prediction would have been 84% of the time
With 74 matches of data, match prediction would have been 84% of the time
With 75 matches of data, match prediction would have been 83% of the time
With 76 matches of data, match prediction would have been 82% of the time
With 77 matches of data, match prediction would have been 81% of the time
With 78 matches of data, match prediction would have been 80% of the time
With 79 matches of data, match prediction would have been 80% of the time
With 80 matches of data, match prediction would have been 78% of the time
With 81 matches of data, match prediction would have been 77% of the time
With 82 matches of data, match prediction would have been 82% of the time
With 83 matches of data, match prediction would have been 81% of the time
With 84 matches of data, match prediction would have been 80% of the time
With 85 matches of data, match prediction would have been 78% of the time
With 86 matches of data, match prediction would have been 76% of the time
With 87 matches of data, match prediction would have been 75% of the time
With 88 matches of data, match prediction would have been 81% of the time
With 89 matches of data, match prediction would have been 80% of the time
With 90 matches of data, match prediction would have been 77% of the time
With 91 matches of data, match prediction would have been 87% of the time
With 92 matches of data, match prediction would have been 85% of the time
With 93 matches of data, match prediction would have been 83% of the time
With 94 matches of data, match prediction would have been 80% of the time
With 95 matches of data, match prediction would have been 100% of the time
With 96 matches of data, match prediction would have been 100% of the time
With 97 matches of data, match prediction would have been 100% of the time
With 98 matches of data, match prediction would have been 100% of the time
Man this code is awful.
Anyway, v12 (based on v7) is now ready. The prediction feature now has awareness of the new seeding system, though since it can't know penalties, the predicted seeding scores are too high. Even if I gave it an entire regional of match scores with no prediction, the rankings it would give out would still be incorrect because teams would not be getting as many points as they should.
Clinton Bolinger
24-03-2010, 01:46
Looks like you are missing the Ann Arbor District Event (WC is the abbreviation that FIRST uses) Last year it was the Lansing District.
-Clinton-
I knew there was something else I had to update last night.
v13 - Now includes new-or-renamed-regionals for 2010.
Nawaid Ladak
24-03-2010, 09:10
I knew there was something else I had to update last night.
v13 - Now includes new-or-renamed-regionals for 2010.
where is the output file? i forgot where OPRNet creates the file.
(Im so used to v11 where teh stats came up in the CommandPrompt window lol)
where is the output file? i forgot where OPRNet creates the file.
(Im so used to v11 where teh stats came up in the CommandPrompt window lol)
It should still come up in the command prompt window. I tested it this morning before I posted, and I just used the prompts. If you launch the EXE without parameters, things should work fine. I haven't tried the command-line parameters yet.
cziggy343
30-03-2010, 11:25
has anyone done this for week 4? :)
Gaurav27
30-03-2010, 16:49
After 4 weeks the following are the top 100 overall entries sorted by OPR:
Net Rank OPR RANK Rank @ Regional REG Team OPR SAA Net RPI
1 1 1 oc 469 10.2847 -1.0967 11.3814 0.5841
14 2 1 wat 1114 8.2622 3.4815 4.7808 0.2903
38 3 2 wat 2056 7.6386 3.9768 3.6618 0.2825
2 4 1 pit 1114 6.8567 0.4901 6.3666 0.5508
7 5 1 nj 25 6.4016 1.0638 5.3379 0.5787
15 6 1 mi 1718 6.2664 1.5087 4.7577 0.5745
29 7 1 dt 67 6.0281 1.9127 4.1154 0.5175
8 8 1 sj 971 5.8993 0.5804 5.3190 0.5721
4 9 1 da 148 5.7183 0.0558 5.6625 0.5525
19 10 1 gg 67 5.5703 0.9816 4.5886 0.5825
3 11 2 sj 254 5.5316 -0.1657 5.6973 0.5645
16 12 1 va 1676 5.4403 0.7395 4.7008 0.5687
46 13 2 oc 226 5.4215 2.0165 3.4050 0.5133
10 14 1 ca 330 5.3624 0.1479 5.2145 0.5838
17 15 2 ca 1717 5.2180 0.5195 4.6986 0.5152
5 16 1 roc 217 5.1753 -0.4623 5.6376 0.5003
6 17 1 is 2672 5.1579 -0.3132 5.4711 0.2096
25 18 1 mo 1208 5.0820 0.7504 4.3317 0.5819
36 19 1 fl 1592 5.0322 1.2440 3.7883 0.5859
30 20 1 md 1058 4.9486 0.8944 4.0542 0.5951
9 21 1 il 1732 4.9427 -0.3582 5.3009 0.5953
11 22 1 dt1 217 4.9140 -0.1534 5.0674 0.5621
63 23 2 il 16 4.8138 1.7093 3.1045 0.5472
54 24 3 il 1625 4.8095 1.5339 3.2755 0.5437
23 25 1 oh 3138 4.7388 0.3363 4.4025 0.5208
12 26 1 hi 359 4.6839 -0.2938 4.9777 0.5870
18 27 3 oc 2137 4.6726 0.0476 4.6249 0.5360
954 28 2 is 3065 4.6433 4.8050 -0.1617 0.2567
35 29 4 oc 33 4.5865 0.7873 3.7992 0.5884
119 30 3 is 3076 4.5224 2.1063 2.4161 0.2923
13 31 1 az 330 4.5124 -0.4230 4.9354 0.5375
124 32 1 pa 365 4.4768 2.1363 2.3405 0.5142
95 33 2 gg 910 4.4713 1.8643 2.6071 0.4521
288 34 1 or 997 4.4399 2.9965 1.4434 0.2869
241 35 2 mi 2771 4.3522 2.7459 1.6063 0.4862
83 36 2 pa 272 4.3040 1.5447 2.7593 0.5065
146 37 3 mi 1918 4.2479 2.0754 2.1726 0.5030
108 38 1 in 1501 4.2350 1.7470 2.4880 0.5370
39 39 1 wi 111 4.1591 0.5362 3.6229 0.5150
184 40 1 ma 3280 4.1569 2.3168 1.8401 0.4931
48 41 2 fl 179 4.1372 0.7421 3.3951 0.5616
486 42 3 wat 3396 4.1210 3.3153 0.8056 0.2202
59 43 3 ca 233 4.1149 0.9109 3.2040 0.4926
457 44 2 ma 1511 4.0744 3.1924 0.8819 0.4433
61 45 1 ok 2410 4.0337 0.8529 3.1808 0.5354
376 46 4 wat 610 4.0081 2.8868 1.1213 0.2280
55 47 2 oh 1629 4.0013 0.7342 3.2671 0.5550
535 48 4 is 2669 3.9975 3.3358 0.6617 0.3038
50 49 1 gt 1918 3.9924 0.6474 3.3450 0.4796
26 50 4 ca 294 3.9906 -0.3311 4.3217 0.5157
75 51 2 roc 145 3.9495 1.0688 2.8807 0.4881
53 52 1 ny 341 3.9464 0.6668 3.2795 0.4611
87 53 1 co 1592 3.9352 1.2632 2.6720 0.2042
179 54 2 dt 27 3.9124 2.0404 1.8720 0.5035
60 55 1 kc 1625 3.8903 0.6997 3.1906 0.5204
77 56 3 fl 1065 3.8856 1.0497 2.8359 0.5337
22 57 2 hi 368 3.8634 -0.6368 4.5002 0.6138
32 58 2 da 2016 3.8546 -0.0960 3.9506 0.5386
110 59 5 is 1662 3.8476 1.3739 2.4737 0.1487
67 60 3 gg 2619 3.8276 0.7634 3.0642 0.5244
24 61 1 wa 3221 3.7935 -0.5699 4.3634 0.5922
135 62 2 mo 2775 3.7875 1.5219 2.2656 0.5004
28 63 6 is 1573 3.7864 -0.3303 4.1167 0.2593
44 64 2 wi 2481 3.7814 0.3430 3.4383 0.5784
894 65 7 is 1578 3.7523 3.8000 -0.0477 0.3176
45 66 3 pa 2753 3.7513 0.3162 3.4351 0.5862
127 67 3 oh 1038 3.7445 1.4378 2.3068 0.5520
181 68 2 pit 63 3.7398 1.8879 1.8519 0.5073
27 69 2 in 868 3.7389 -0.4872 4.2261 0.5244
41 70 5 oc 3302 3.7353 0.1603 3.5750 0.5527
33 71 2 az 987 3.7289 -0.2134 3.9423 0.5603
299 72 5 ca 687 3.7206 2.3202 1.4003 0.4560
89 73 3 roc 1551 3.6981 1.0365 2.6616 0.5109
31 74 4 pa 56 3.6765 -0.3144 3.9908 0.5602
42 75 4 il 111 3.6330 0.0705 3.5625 0.5315
64 76 1 li 271 3.6047 0.5002 3.1044 0.5168
62 77 2 kc 2345 3.5996 0.4394 3.1602 0.5632
153 78 5 il 2949 3.5945 1.4820 2.1125 0.5031
244 79 2 va 293 3.5876 1.9855 1.6021 0.4432
102 80 3 in 45 3.5129 0.9644 2.5485 0.4845
66 81 2 nj 303 3.4964 0.4104 3.0860 0.5452
21 82 6 oc 573 3.4959 -1.0076 4.5036 0.5305
58 83 3 kc 234 3.4870 0.2650 3.2220 0.4838
175 84 4 mi 3234 3.4260 1.4888 1.9372 0.5038
132 85 3 mo 1806 3.4018 1.1261 2.2757 0.5221
203 86 3 va 1086 3.3994 1.6153 1.7841 0.4165
20 87 4 fl 103 3.3868 -1.1505 4.5374 0.5637
144 88 5 mi 2645 3.3719 1.1582 2.2137 0.5428
363 89 4 oh 291 3.3446 2.1827 1.1619 0.5155
52 90 2 li 358 3.3433 0.0312 3.3121 0.5549
459 91 2 or 753 3.3422 2.4715 0.8707 0.2321
47 92 8 is 1954 3.3310 -0.0688 3.3998 0.2778
79 93 4 kc 525 3.3070 0.4960 2.8110 0.4974
160 94 4 gg 33 3.3067 1.2528 2.0539 0.5236
445 95 1 nh 78 3.2905 2.3606 0.9300 0.2515
86 96 6 ca 599 3.2855 0.5855 2.6999 0.5066
138 97 2 ok 1939 3.2800 1.0450 2.2351 0.5145
218 98 5 wat 1305 3.2749 1.5839 1.6910 0.2500
72 99 3 da 1421 3.2603 0.3215 2.9388 0.4931
286 100 3 ma 88 3.2464 1.7986 1.4478 0.5018
bigbeezy
31-03-2010, 01:28
awesome! 1592 top 100! just wondering, what is the Net Rank mean? To me it would factor multiple regionals and somehow be averaged together, however there are different Net Ranks for the same team.
also, i'm curious to see how many of these teams either are not going to championships or are currently on the wait list.
unfortunately the Bionic Tigers, the last i heard, still are wait listed.
awesome! 1592 top 100! just wondering, what is the Net Rank mean? To me it would factor multiple regionals and somehow be averaged together, however there are different Net Ranks for the same team.
also, i'm curious to see how many of these teams either are not going to championships or are currently on the wait list.
unfortunately the Bionic Tigers, the last i heard, still are wait listed.
"Net Rank" I think is a bug. If you delete that and shift the rest of the headings over, they all match.
Edit: Nevermind, I just don't know what it is supposed to be.
Nawaid Ladak
31-03-2010, 10:31
awesome! 1592 top 100! just wondering, what is the Net Rank mean? To me it would factor multiple regionals and somehow be averaged together, however there are different Net Ranks for the same team.
also, i'm curious to see how many of these teams either are not going to championships or are currently on the wait list.
unfortunately the Bionic Tigers, the last i heard, still are wait listed.
"Net Rank" I think is a bug. If you delete that and shift the rest of the headings over, they all match.
Edit: Nevermind, I just don't know what it is supposed to be.
by looking at the table, it's pretty easy to see net rank is the ranking of each teams net category.
net = opr-ssa
bigbeezy
31-03-2010, 11:11
by looking at the table, it's pretty easy to see net rank is the ranking of each teams net category.
net = opr-ssa
o yeah, duh... thanks that makes sense
Joe Ross
31-03-2010, 11:43
If you assume 1114 and 2056's poor SAA is because they were scoring for the opponents, it gets even more scary. Both are scoring over 11 points a match.
Gaurav27
31-03-2010, 16:04
I took my compiled database with entries from weeks 1 to 4 and created a pdf. My excel file was too big to upload.
The attached file includes all 1850 entries, sorted by OPR.
Hooray, looks like this sucker still works, 3 years later! Big thanks to FIRST for not updating their scoring formatting.
I'll see about updating the regional list to the 2011 version tonight.
For those that don't want to read the whole thread, here is the latest version:
http://www.chiefdelphi.com/forums/attachment.php?attachmentid=8922&d=1269426199
Bongle, what are the chances you could put this into a web app, hosted on a free server like google apps? That way we could get to it from our mobile devices, web browsers at work (many companies use proxies that prevent this .exe from working), and public computers that have paranoid IT infrastructure.
Bongle, what are the chances you could put this into a web app, hosted on a free server like google apps? That way we could get to it from our mobile devices, web browsers at work (many companies use proxies that prevent this .exe from working), and public computers that have paranoid IT infrastructure.
Given that my expertise is in C++, the chances of me personally doing it are very slim. The best I could do would be a java applet embedded in a web page.
Ian Curtis
10-03-2011, 19:24
This is probably a stupid question. :)
If we do >results.csv when we enter a query, where does this text document get saved? I can't seem to find it.
Thanks!
The Lucas
10-03-2011, 22:31
This is probably a stupid question. :)
If we do >results.csv when we enter a query, where does this text document get saved? I can't seem to find it.
Thanks!
It should save it to whichever folder you run the command in. However, I wouldn't recommend writing it to a csv file, the output is not comma separated. You can save it to a txt file. I recommend piping it to the clipboard "| clip" then pasting it to excel. It is nice to have one sheet with all the regional. That is how I generated the Top 30.
Tom Bottiglieri
11-03-2011, 19:57
Given that my expertise is in C++, the chances of me personally doing it are very slim. The best I could do would be a java applet embedded in a web page.
Would you be willing to share the v13 source?
Would you be willing to share the v13 source?
The v12 source is earlier in the thread, and I think v13 just updated some regional names.
Nathan Streeter
12-03-2011, 08:52
It should save it to whichever folder you run the command in. However, I wouldn't recommend writing it to a csv file, the output is not comma separated. You can save it to a txt file. I recommend piping it to the clipboard "| clip" then pasting it to excel. It is nice to have one sheet with all the regional. That is how I generated the Top 30.
How do I get the results to output to a .txt? I tried enterring ">output.csv" and ">output.txt" after the results displayed in the command window, but the command window just closed and I couldn't find the output file. How do I get the results to output to something that I could put into an excel file?
Thanks!
Ian Curtis
12-03-2011, 11:36
How do I get the results to output to a .txt? I tried enterring ">output.csv" and ">output.txt" after the results displayed in the command window, but the command window just closed and I couldn't find the output file. How do I get the results to output to something that I could put into an excel file?
Thanks!
Are you running it from the command line, or double clicking the icon and running from there? I couldn't get the results to store after clicking the icon, but running it from the command line I could. So I just put oprnet on the desktop, opened the command line, type "cd desktop" hit enter, then "oprnet nh 2011 opr t q | clip" and I end up with the opr results by team on the clipboard. Then just paste it into an excel document.
Hope that helps!
For any Mac users out there I have updated my OPR program.
Is it just me or does the predict function not work for the 2011 season?
The Lucas
12-03-2011, 17:29
Is it just me or does the predict function not work for the 2011 season?
v13 is for last year with the different point based ranking scheme. That doesn't work on this year W L T.
Nathan Streeter
12-03-2011, 17:59
Are you running it from the command line, or double clicking the icon and running from there? I couldn't get the results to store after clicking the icon, but running it from the command line I could. So I just put oprnet on the desktop, opened the command line, type "cd desktop" hit enter, then "oprnet nh 2011 opr t q | clip" and I end up with the opr results by team on the clipboard. Then just paste it into an excel document.
Hope that helps!
Thanks a bunch, Ian! It's working very well now! :-) For being an FRC/scouting/strategy/excel person, I'm not particularly good with any "programming" but C++ and Robolab!
Is it just me or does the predict function not work for the 2011 season?
I found that it was crashing for me, too. I'll have to check the source to fix it (and get it to do WLT again)
Is it just me, or is the Chesapeake regional data not working at all.
Is it just me, or is the Chesapeake regional data not working at all.
Looks like they used the old software to generate the scores page, so it is a slightly different format than OPRNet expects and so it fails to load it. If it gets loaded to TBA (and TBA still uses the format OPRNet expects), then it might be loadable later.
The Lucas
20-03-2011, 22:16
Is it just me, or is the Chesapeake regional data not working at all.
This is what I got last night when it was working on MD (not working now)
0 836 39.8872
1 1218 37.4213
2 340 36.9526
3 365 33.9129
4 768 23.704
5 250 22.2095
6 888 19.9839
7 88 19.4081
8 846 17.8937
9 1111 16.8185
10 714 16.7085
11 549 16.585
12 1403 16.4453
13 2377 16.3261
14 1143 16.1828
15 1124 15.2863
16 1895 13.1584
17 2199 13.0146
18 134 13.0029
19 1699 12.3934
20 1980 10.724
21 2912 10.3563
22 1727 10.0474
23 316 8.89519
24 3389 8.32284
25 1719 8.18742
26 509 7.36567
27 1389 7.24434
28 237 6.76665
29 686 6.11233
30 2546 5.51429
31 53 5.14103
32 2849 4.78558
33 7 3.63541
34 3748 3.2073
35 225 3.00393
36 3733 2.44615
37 484 1.85067
38 3793 1.338
39 2789 1.29043
40 3154 1.17108
41 2528 0.820417
42 3714 0.423082
43 3650 -0.398794
44 422 -0.765758
45 2537 -1.58666
46 3150 -1.87487
47 2836 -2.34444
48 1748 -2.37804
49 1195 -2.41779
50 2866 -2.78222
51 1370 -2.85469
52 1446 -3.51208
53 204 -3.86119
54 708 -4.59569
55 1893 -6.41675
56 2641 -7.08657
57 87 -7.83013
58 178 -8.377
59 3307 -10.0841
Congrats your team (836) is the "Qualification Match MVP (http://www.chiefdelphi.com/forums/showpost.php?p=1041046&postcount=24)". Chesapeake is an interesting case study. A very clear top tier of 4 formed on the OPR, then was broken up by seeding and Alliance selections (all 4 had 2 or more losses). 1218 had 3 losses, 1 to 836, 1 to 340. 365 beat 340 but lost to 836. 836 seeded highest (4th) followed by 340 (5th), 365 (6th), 1218 (10th). They were then picked in this order with these results
1. 365 (decline AC5 QF)
2. 836 (accept A1 F)
3. 340 (decline AC4 SF)
4. 1218 (accept A2 W)
All the alliances that lost to an alliance that contained another of the 4. When there are no powerhouse alliances and heavy D, anything can happen :ahh:
Thank you Bryan. It was a pleasure working with you this weekend
V14 - Now parses the "fat" style of regional results, a la www.frclinks.com/e/m/il
billbo911
29-03-2011, 13:44
V14 - Now parses the "fat" style of regional results, a la www.frclinks.com/e/m/il
The next chance we will have to use this is at Nationals in St. Louis. What "regional" code would be used for the different fields?
The next chance we will have to use this is at Nationals in St. Louis. What "regional" code would be used for the different fields?
cmp FIRST Championship
arc FIRST Championship - Archimedes Division
cur FIRST Championship - Curie Division
gal FIRST Championship - Galileo Division
new FIRST Championship - Newton Division
ein FIRST Championship - Einstein Field
billbo911
29-03-2011, 14:00
cmp FIRST Championship
arc FIRST Championship - Archimedes Division
cur FIRST Championship - Curie Division
gal FIRST Championship - Galileo Division
new FIRST Championship - Newton Division
ein FIRST Championship - Einstein Field
Excellent, thanks!
Joe Ross
29-03-2011, 14:07
Here are the regional codes that are missing from v14:
stx Alamo
on2 Greater Toronto West
dmn Lake Superior
nc North Carolina
wa2 Seattle Cascade
tn Smoky Mountain
ut Utah
wor WPI
wc Ann Arbor MI District
ww Livonia MI District
swm Niles MI District
oc1 Waterford MI District
arc FIRST Championship - Archimedes Division
cur FIRST Championship - Curie Division
gal FIRST Championship - Galileo Division
new FIRST Championship - Newton Division
ein FIRST Championship - Einstein Field
An old executable I have (from 2009) also had the all option to calculate stats for all regionals. That was nice.
The Lucas
30-03-2011, 01:31
ein FIRST Championship - Einstein Field
An old executable I have (from 2009) also had the all option to calculate stats for all regionals. That was nice.
Since it ignores elim matches, there is no reason for it to look at Einstein. I also miss the 'all' option.
v15 - I realized that I wanted to know the OPR of "on2" and it wouldn't let me, so v15 disables the "correct regional code" checker, so it'll work on any regional code imaginable. Also updates the regional code list so that you see the 2011 set of regionals.
Sorry to fans of the "all" option. I don't have enough time to recover that feature, and I can't guarantee it'd get updated in future years (or that I'd get every regional). However, I keep posting the source in the hopes someone else can pick up the torch and add cool features.
Its also crashing on the predict option when it tries to calculate the final seeding, at least for GTREast
caltemus
01-04-2011, 23:15
Can someone fluent in java update the GUI found around post 5?
Grim Tuesday
02-04-2011, 01:21
Since it ignores elim matches, there is no reason for it to look at Einstein. I also miss the 'all' option.
Why you would ever want to scout Einstein is beyond me...
The Lucas
02-04-2011, 17:49
Its also crashing on the predict option when it tries to calculate the final seeding, at least for GTREast
Ya that is do to the crazy seeding system last year, mentioned a page or so back.
The Lucas
03-04-2011, 21:51
Version 15 crashes on Troy data. I found it works with version 11 so here is the data for convenience.
0 217 51.5663
1 33 46.2578
2 2337 41.6942
3 3539 37.3808
4 226 36.9186
5 469 34.1671
6 68 32.3696
7 1718 31.8445
8 910 28.6375
9 245 20.7588
10 703 20.6414
11 3302 19.7233
12 2851 16.076
13 503 14.2064
14 3538 12.4701
15 3115 11.0716
16 1188 10.7523
17 3548 10.0296
18 3450 9.26761
19 2586 7.78701
20 440 6.26845
21 3621 5.56059
22 216 5.53577
23 314 5.08476
24 288 4.82352
25 903 3.43038
26 322 3.4119
27 519 1.51176
28 3767 1.32039
29 244 0.542561
30 3657 -1.22599
31 3534 -1.24133
32 2048 -1.29143
33 2960 -1.57964
34 468 -1.90365
35 2604 -1.9788
36 2591 -2.61877
37 3421 -2.77179
38 3069 -5.12076
39 3619 -5.29505
Still works :-) I haven't updated the regional list for 2012, I'll try to do that tonight.
Latest version (v16) can be found in this (http://www.chiefdelphi.com/forums/showpost.php?p=1137823&postcount=208) post.
Here's v16. The only change is that the regional list it gives is the 2012 version.
Using predict makes the program crash. Any fix for it?
I have tried alamo kettering and other regionals.
I do
2012
gg
predict
t
Then I get errors also have tried to sort it by rank it crashes then.
It works if you use opr and other stuff but not predict.
I have tried alamo kettering and other regionals.
I do
2012
gg
predict
t
Then I get errors also have tried to sort it by rank it crashes then.
It works if you use opr and other stuff but not predict.
Fixed! See my previous post. The problem was pretty lame (related to the new competition year), I'm going to put in something so that next year I won't forget to update things.
Thanks your awesome. Also can you copy the values put of the program anyway?
Thanks your awesome. Also can you copy the values put of the program anyway?
If you want to copy to a text file, run it from a command line (start->run->cmd) and type "oprnet nh 2012 opr r q > output.txt" without the quotes. That will run it for the Granite State Regional and spit the result into output.txt in the same directory. You can then copy/paste that into excel or print it off.
If you run it normally, you can right-click on the program window, choose mark, then drag-select what you want to copy and press enter. Then paste it into notepad.
Another thing I noticed is the predict doesnt work by ranking. It just still prints out the teams in their numerical order even when I type in that I want ranking.
ProgramLuke
02-03-2012, 22:58
I ran the numbers for all of the regionals/districts have reported match results:
Team# OPR
341 … 31.7068
1477 … 30.2726
1218 … 27.2962
3528 … 26.8382
118 … 24.2948
3322 … 24.2459
1986 … 23.8057
716 … 21.63
16 … 18.7632
1208 … 18.4909
148 … 18.2347
1730 … 16.2517
1802 … 16.1124
2386 … 16.0739
488 … 15.9286
131 … 15.7566
1647 … 15.7327
1987 … 15.6483
2848 … 15.4478
58 … 15.3458
935 … 15.2741
357 … 14.965
234 … 14.7897
967 … 14.6359
231 … 14.5196
1918 … 14.5068
1108 … 14.3499
2393 … 14.2422
157 … 14.1474
486 … 13.8925
772 … 13.8551
885 … 13.824
2468 … 13.5467
525 … 13.3615
51 … 13.3428
704 … 12.9463
134 … 12.9165
811 … 12.7724
175 … 12.7659
3545 … 12.6576
1737 … 12.366
538 … 12.332
319 … 12.0706
3597 … 11.9401
1997 … 11.8106
2721 … 11.8018
85 … 11.7372
2949 … 11.5904
33 … 10.9742
95 … 10.9405
3035 … 10.8832
3467 … 10.8563
2246 … 10.5909
2791 … 10.5761
1982 … 10.4911
4362 … 10.3585
61 … 10.3194
126 … 10.2701
1775 … 10.2426
3618 … 10.2322
3546 … 10.2264
1806 … 10.0955
2751 … 9.8888
3284 … 9.78244
4092 … 9.7188
1712 … 9.64276
3507 … 9.50383
2342 … 9.44864
3323 … 9.3737
3609 … 9.31227
2395 … 9.28699
123 … 9.2249
3582 … 9.16537
225 … 9.10767
2283 … 9.03365
1504 … 8.99305
2985 … 8.85674
1684 … 8.78412
1506 … 8.75739
547 … 8.652
714 … 8.62731
2000 … 8.44431
451 … 8.35633
1247 … 8.25625
1923 … 8.0148
2016 … 7.86135
3843 … 7.85381
4098 … 7.82099
862 … 7.74976
2167 … 7.69582
1985 … 7.66287
2767 … 7.63255
1501 … 7.53925
3552 … 7.48174
337 … 7.33333
3798 … 7.30742
2345 … 7.23241
709 … 7.17513
4373 … 7.09246
1723 … 7.03194
1143 … 6.75226
314 … 6.73454
292 … 6.69446
447 … 6.67282
3516 … 6.642
3844 … 6.5543
1094 … 6.53681
4342 … 6.53665
2996 … 6.49677
1493 … 6.47983
1640 … 6.43865
3103 … 6.27779
4376 … 6.21473
3140 … 6.19044
2346 … 6.02757
3743 … 5.96222
1777 … 5.91672
70 … 5.90922
834 … 5.88165
2337 … 5.74106
1261 … 5.69842
1168 … 5.68302
1519 … 5.66322
1249 … 5.63615
2357 … 5.62071
3481 … 5.58216
1825 … 5.5493
4063 … 5.50045
78 … 5.42269
1940 … 5.40926
224 … 5.34363
3784 … 5.33882
3568 … 5.32605
166 … 5.32214
2952 … 5.31319
213 … 5.31008
1721 … 5.3037
494 … 5.28013
293 … 5.26783
2583 … 5.16687
138 … 5.15867
1391 … 5.14903
1319 … 5.02974
1764 … 4.95719
2607 … 4.9121
272 … 4.85022
3696 … 4.81452
4408 … 4.78452
3984 … 4.73541
894 … 4.73191
1769 … 4.69426
3656 … 4.69368
1448 … 4.67491
4409 … 4.67075
2137 … 4.61598
2936 … 4.60058
1782 … 4.42601
653 … 4.31294
2590 … 4.30019
1512 … 4.20306
247 … 4.15716
3856 … 4.11953
1831 … 4.11627
1322 … 3.99133
3452 … 3.98638
3167 … 3.98256
3973 … 3.97054
4375 … 3.94346
457 … 3.92749
2190 … 3.8696
2856 … 3.83691
1073 … 3.80954
3302 … 3.79677
3353 … 3.76899
2080 … 3.76847
4237 … 3.65466
1791 … 3.62083
3834 … 3.5852
3415 … 3.57888
3370 … 3.49635
2229 … 3.45694
1502 … 3.43532
3325 … 3.30526
869 … 3.28749
4020 … 3.27845
931 … 3.26875
4381 … 3.19231
4398 … 3.16853
2457 … 3.14301
662 … 3.13848
1729 … 3.09818
3028 … 3.05017
4208 … 3.04257
2982 … 3.02097
3029 … 2.98978
4403 … 2.9724
4004 … 2.96349
3861 … 2.93749
1984 … 2.93398
3534 … 2.91432
2004 … 2.89967
922 … 2.884
1243 … 2.86215
3943 … 2.84715
1677 … 2.77076
1824 … 2.70093
2789 … 2.57027
2771 … 2.55032
1277 … 2.47677
708 … 2.41994
2410 … 2.40479
2959 … 2.35867
3675 … 2.2474
1038 … 2.18793
703 … 2.18314
3478 … 2.14785
2200 … 2.11833
2817 … 2.10672
326 … 2.10635
87 … 2.10223
3700 … 2.04114
322 … 1.98571
1939 … 1.97978
133 … 1.96336
1547 … 1.95523
4245 … 1.93945
3240 … 1.92071
938 … 1.8909
3227 … 1.85331
1810 … 1.84672
302 … 1.83528
4327 … 1.79148
3769 … 1.78315
4285 … 1.76283
1922 … 1.69788
3335 … 1.57432
1811 … 1.51854
462 … 1.49814
3509 … 1.48125
2461 … 1.47757
3585 … 1.47471
1517 … 1.45816
904 … 1.45392
245 … 1.43911
4377 … 1.25083
3536 … 1.23027
501 … 1.23021
3451 … 1.22803
4265 … 1.10463
3417 … 1.04772
2833 … 0.858131
238 … 0.83566
3824 … 0.795549
4025 … 0.770932
4294 … 0.769346
2973 … 0.766425
4332 … 0.696361
1466 … 0.566471
4219 … 0.534509
3535 … 0.533594
1058 … 0.53275
3116 … 0.502378
2874 … 0.444486
3767 … 0.294256
1528 … 0.28603
1763 … 0.222096
2611 … 0.137548
1652 … -0.108502
3080 … -0.162151
4382 … -0.246186
4325 … -0.28284
2539 … -0.319302
3497 … -0.359499
1827 … -0.439216
3875 … -0.446344
3972 … -0.513003
2405 … -0.547059
4264 … -0.626333
2627 … -0.681864
2001 … -0.697355
1711 … -0.756725
2164 … -0.840833
1254 … -0.84697
2335 … -0.885908
20 … -0.901644
1994 … -0.949168
4396 … -0.965898
3561 … -0.989313
3259 … -1.0852
468 … -1.28553
4368 … -1.31306
3931 … -1.31767
3601 … -1.36808
151 … -1.38379
442 … -1.39272
1307 … -1.39558
4361 … -1.40511
2783 … -1.4066
2745 … -1.40708
4389 … -1.48964
3607 … -1.53166
3783 … -1.53914
3961 … -1.69764
1817 … -1.73063
2158 … -1.76095
3999 … -1.83683
2600 … -1.86961
2604 … -2.12964
3966 … -2.1528
4034 … -2.30661
1847 … -2.33761
3614 … -2.33972
3123 … -2.35324
4162 … -2.45965
3764 … -2.61266
3421 … -2.63307
937 … -2.63919
3485 … -2.67588
4306 … -2.7496
2972 … -2.78889
2969 … -2.89291
3821 … -2.97698
3797 … -3.04852
1701 … -3.06178
2787 … -3.14193
2353 … -3.20092
509 … -3.21476
1289 … -3.28647
415 … -3.37884
172 … -3.50717
3345 … -3.71748
1495 … -3.7531
3537 … -3.77946
4000 … -3.96245
2234 … -4.00817
2966 … -4.76436
2560 … -5.0293
499 … -5.62894
1153 … -5.71471
2483 … -6.24366
3366 … -6.27803
3658 … -6.74123
4282 … -7.94181
1785 … -8.05824
OPR
mean: 4.78140686
median: 3.803155
stdev: 6.27617293
I ran the numbers for all of the regionals/districts have reported match results:
Would you please post a ZIP'd copy of the raw data file you used as input for this calculation? Thank you.
BlacksmithWoods
02-03-2012, 23:23
Looks like something I should try out. Will get back with results!
Did you grab data from all of the events at once?
How?
ProgramLuke
03-03-2012, 00:09
Would you please post a ZIP'd copy of the raw data file you used as input for this calculation? Thank you.
I used the OPRNet Tool v16 (http://www.chiefdelphi.com/forums/showpost.php?p=1137823&postcount=208) to create the table, it downloads the data as it needs it so I do not have that data on hand.
Another thing I noticed is the predict doesnt work by ranking. It just still prints out the teams in their numerical order even when I type in that I want ranking.
I think if you do R instead of T for your sort order, it should work by W-L-T record. Though the predicted seed won't be accurate because teams will have coopertition points.
My output is:
Its not working right....
0 Ranking 16 8 1 0
1 Ranking 525 6 3 0
2 Ranking 662 5 4 0
3 Ranking 931 3 6 0
4 Ranking 935 8 1 0
5 Ranking 937 3 6 0
6 Ranking 938 3 6 0
7 Ranking 967 4 5 0
8 Ranking 1094 3 6 0
9 Ranking 1108 3 5 1
10 Ranking 1208 7 2 0
11 Ranking 1448 5 4 0
12 Ranking 1652 4 5 0
13 Ranking 1723 3 6 0
14 Ranking 1730 7 2 0
15 Ranking 1737 5 4 0
16 Ranking 1763 3 6 0
17 Ranking 1764 5 4 0
18 Ranking 1769 2 6 1
19 Ranking 1775 8 0 1
20 Ranking 1777 4 5 0
21 Ranking 1782 5 4 0
22 Ranking 1785 2 7 0
23 Ranking 1802 7 2 0
24 Ranking 1806 5 4 0
25 Ranking 1810 7 2 0
26 Ranking 1825 6 3 0
27 Ranking 1827 0 8 1
28 Ranking 1847 4 5 0
29 Ranking 1939 4 4 1
30 Ranking 1982 6 3 0
31 Ranking 1984 5 4 0
32 Ranking 1985 3 6 0
33 Ranking 1986 8 1 0
34 Ranking 1987 8 1 0
35 Ranking 1994 1 7 1
36 Ranking 1997 6 3 0
37 Ranking 2001 4 5 0
38 Ranking 2004 4 5 0
39 Ranking 2164 4 5 0
40 Ranking 2167 6 3 0
41 Ranking 2335 4 5 0
42 Ranking 2345 3 6 0
43 Ranking 2346 2 7 0
44 Ranking 2353 2 7 0
45 Ranking 2357 3 6 0
46 Ranking 2395 4 4 1
47 Ranking 2410 2 7 0
48 Ranking 2457 5 4 0
49 Ranking 2560 4 5 0
50 Ranking 2874 4 5 0
51 Ranking 2949 7 1 1
52 Ranking 2972 4 5 0
53 Ranking 2996 3 6 0
54 Ranking 3284 4 4 1
55 Ranking 3485 5 4 0
56 Ranking 3507 3 5 1
57 Ranking 3528 9 0 0
58 Ranking 3764 4 5 0
59 Ranking 3784 3 5 1
60 Ranking 3798 3 5 1
61 Ranking 3931 3 6 0
62 Ranking 3973 3 6 0
63 Ranking 4208 4 5 0
I ran the numbers for all of the regionals/districts have reported match results:
Would you please post a ZIP'd copy of the raw data file you used as input for this calculation? Thank you.
I used the OPRNet Tool v16 (http://www.chiefdelphi.com/forums/showpost.php?p=1137823&postcount=208) to create the table, it downloads the data as it needs it so I do not have that data on hand.
@Bongle: Is there a way to run your OPRNet Tool to output a file with the raw data in it?
@Bongle: Is there a way to run your OPRNet Tool to output a file with the raw data in it?
You can get it to output the OPRs from the command-line, but the parsed FRC match data is just thrown away once I download it. You can grab the v15 source code in one of my old posts and adapt it to your own needs though.
You're right the predicted standings don't seem to work - it might be ranking using 2010's strange method rather than a normal W-L-T. Due to coopertition bridges though, I wouldn't worry about the predicted standings - they'll be completely wrong anyway since the bridge points aren't taken into account.
You can get it to output the OPRs from the command-line, but the parsed FRC match data is just thrown away once I download it.
Actually, I wasn't looking for the OPR, or the parsed match data. I was looking for the raw match data. Could you post a link to where you're getting that raw data from?
Actually, I wasn't looking for the OPR, or the parsed match data. I was looking for the raw match data. Could you post a link to where you're getting that raw data from?
I just use the official FIRST match results.
frclinks.com gives you links to most of them.
Example: The Alamo results are here: http://www2.usfirst.org/2012comp/Events/stx/matchresults.html (stx is the short code for the regional). You can get different results by substituting different regional codes and years.
Is there a way to grab the data from all of the events?
ThirteenOfTwo
05-03-2012, 02:03
It strikes me that OPR might undervalue teams who exclusively pursue the Coopertition Bridge in qualification rounds, since that doesn't add to their score. Have you considered accounting for that, perhaps by adding twenty points to the score of any alliance that receives full coopertition points?
It strikes me that OPR might undervalue teams who exclusively pursue the Coopertition Bridge in qualification rounds, since that doesn't add to their score. Have you considered accounting for that, perhaps by adding twenty points to the score of any alliance that receives full coopertition points?
It would undervalue them for sure. Unfortunately, I don't actually have a way to determine which alliance earned coopertition points, since it's not in the full results and I don't have the time to implement a twitter parser.
Another thing it is semi-missing is foul points - in previous years, a team that tended to take penalties would end up with a negative OPR. But this year, since those penalties actually add points to your opponents, a penalty-heavy team might still have an apparently-high OPR. Or, if you are a team that tends to get fouled, you might have an elevated OPR despite never scoring a basket.
Here's all the OPRs for this week. The number on the left is that robot's rank at its regional.
0 OPR 341 32.8125
0 OPR 1986 26.2784
0 OPR 118 25.6594
1 OPR 1218 23.6265
1 OPR 16 22.9855
0 OPR 716 22.902
2 OPR 3528 22.6023
1 OPR 1477 22.3017
2 OPR 148 21.2954
0 OPR 3322 19.4138
3 OPR 488 18.699
3 OPR 1208 18.1549
1 OPR 58 17.088
2 OPR 131 16.7107
4 OPR 1730 16.511
0 OPR 3476 16.4207
2 OPR 486 16.3144
4 OPR 2468 16.3067
5 OPR 935 15.5293
3 OPR 885 15.4566
6 OPR 967 15.3269
0 OPR 234 15.0478
0 OPR 1918 14.9358
1 OPR 85 14.5958
7 OPR 1982 14.363
8 OPR 1987 14.3531
1 OPR 2496 14.3036
1 OPR 2751 14.2611
5 OPR 231 14.1442
4 OPR 319 14.0779
5 OPR 3467 13.725
6 OPR 2848 13.6591
9 OPR 1997 13.5443
2 OPR 2386 13.5017
3 OPR 772 13.4929
1 OPR 51 13.4107
4 OPR 2393 13.247
3 OPR 357 13.1717
6 OPR 3597 13.0425
2 OPR 1538 12.8677
5 OPR 4092 12.6507
10 OPR 3284 12.2517
7 OPR 126 12.1894
3 OPR 2485 12.1408
11 OPR 525 12.0171
2 OPR 33 11.9848
4 OPR 1726 11.9493
12 OPR 1108 11.8475
13 OPR 2345 11.8347
8 OPR 95 11.7941
14 OPR 1802 11.6632
9 OPR 175 11.3817
2 OPR 123 11.1897
5 OPR 2543 11.0539
6 OPR 538 10.9521
7 OPR 1501 10.915
3 OPR 3546 10.8166
3 OPR 1504 10.7889
6 OPR 1138 10.7744
10 OPR 811 10.5492
4 OPR 1647 10.3195
11 OPR 134 10.2537
12 OPR 3323 10.2166
13 OPR 2342 10.1822
4 OPR 862 10.131
15 OPR 1806 10.1184
7 OPR 3035 10.0895
7 OPR 1661 10.0641
8 OPR 399 9.98838
9 OPR 3328 9.98757
5 OPR 2016 9.9551
8 OPR 3103 9.88195
16 OPR 2949 9.75011
14 OPR 157 9.69735
10 OPR 1266 9.60731
11 OPR 3965 9.54659
15 OPR 3609 9.45004
8 OPR 337 9.36572
17 OPR 1985 9.10772
16 OPR 61 9.10239
18 OPR 3507 9.0431
9 OPR 447 9.03065
17 OPR 1493 9.00103
12 OPR 4161 8.93611
4 OPR 2246 8.92978
5 OPR 1684 8.91294
13 OPR 2984 8.8993
6 OPR 225 8.88361
9 OPR 3545 8.79667
19 OPR 1775 8.78996
10 OPR 704 8.76618
18 OPR 2791 8.74593
6 OPR 2337 8.68728
20 OPR 1825 8.67203
7 OPR 70 8.33683
14 OPR 3453 8.27547
7 OPR 87 8.26135
8 OPR 3568 8.25133
21 OPR 1984 8.24363
5 OPR 3618 8.22496
22 OPR 2996 8.2217
8 OPR 714 8.14243
15 OPR 4276 8.11717
9 OPR 2590 8.08921
9 OPR 1506 8.04759
16 OPR 3647 8.03452
17 OPR 4056 7.94523
10 OPR 834 7.79931
11 OPR 1923 7.77921
10 OPR 2137 7.67652
18 OPR 2827 7.55455
11 OPR 314 7.53413
23 OPR 2395 7.49949
11 OPR 3478 7.43161
19 OPR 1073 7.41635
12 OPR 4342 7.33981
10 OPR 1261 7.33809
6 OPR 2000 7.23826
12 OPR 3582 7.2377
7 OPR 4362 7.08925
13 OPR 1640 7.04481
11 OPR 547 6.94494
24 OPR 2346 6.81529
20 OPR 1519 6.7423
19 OPR 1372 6.74147
14 OPR 1143 6.66163
25 OPR 1723 6.5577
15 OPR 4373 6.55164
12 OPR 3302 6.52255
12 OPR 4098 6.45841
13 OPR 3415 6.39837
13 OPR 2721 6.39155
13 OPR 292 6.33222
14 OPR 2283 6.33006
26 OPR 2357 6.30804
21 OPR 78 6.29179
22 OPR 166 6.25887
15 OPR 245 6.25599
27 OPR 3798 6.24511
20 OPR 2029 6.08383
21 OPR 4014 6.04743
14 OPR 4265 6.01163
22 OPR 702 6.00616
16 OPR 3743 5.90888
15 OPR 451 5.81798
8 OPR 2959 5.75464
9 OPR 4237 5.74805
10 OPR 3656 5.74522
11 OPR 904 5.61683
23 OPR 1247 5.60367
16 OPR 1811 5.41299
17 OPR 709 5.38007
18 OPR 1391 5.36037
24 OPR 213 5.30229
23 OPR 3255 5.30163
12 OPR 247 5.2979
13 OPR 4375 5.29578
28 OPR 2167 5.22451
24 OPR 4322 5.20897
25 OPR 4160 5.17384
26 OPR 4139 5.15424
19 OPR 1712 5.14555
29 OPR 4208 5.10633
16 OPR 3516 5.08752
27 OPR 3341 5.0114
14 OPR 1322 4.98369
25 OPR 238 4.93879
30 OPR 2457 4.92861
17 OPR 3843 4.90281
18 OPR 3984 4.87914
26 OPR 1831 4.8529
28 OPR 3226 4.82304
29 OPR 1622 4.77857
31 OPR 1764 4.7483
17 OPR 3552 4.69901
30 OPR 2102 4.67774
14 OPR 2767 4.67592
27 OPR 138 4.65928
20 OPR 2607 4.61024
32 OPR 3784 4.5993
15 OPR 4409 4.57113
19 OPR 1038 4.5209
28 OPR 133 4.51385
33 OPR 3973 4.45533
20 OPR 3675 4.41823
18 OPR 2936 4.38089
21 OPR 2229 4.3218
16 OPR 4327 4.28979
34 OPR 1769 4.27853
19 OPR 1817 4.26613
21 OPR 3844 4.26344
17 OPR 3452 4.24254
35 OPR 1737 4.19178
36 OPR 662 4.14502
37 OPR 2001 4.07234
38 OPR 1777 4.02699
20 OPR 3335 4.01941
29 OPR 1058 3.90721
21 OPR 2952 3.85609
22 OPR 3370 3.8319
23 OPR 3696 3.82853
18 OPR 1677 3.78573
19 OPR 1940 3.76324
24 OPR 4219 3.74796
30 OPR 501 3.72605
15 OPR 4376 3.7115
25 OPR 3028 3.70648
39 OPR 1094 3.68128
22 OPR 1249 3.64641
22 OPR 708 3.64145
23 OPR 2190 3.58935
31 OPR 1160 3.58679
23 OPR 4285 3.57779
16 OPR 494 3.56116
32 OPR 3008 3.52971
24 OPR 3140 3.49907
25 OPR 2856 3.47522
33 OPR 599 3.43749
26 OPR 2583 3.43391
31 OPR 1729 3.39535
27 OPR 3481 3.38129
17 OPR 1243 3.37743
18 OPR 302 3.36519
32 OPR 1512 3.36242
40 OPR 2874 3.3329
34 OPR 2599 3.29634
41 OPR 1448 3.22393
28 OPR 4332 3.21996
19 OPR 3537 3.16299
29 OPR 4063 3.15461
42 OPR 1847 3.15327
33 OPR 1824 3.1522
35 OPR 1572 3.13967
30 OPR 3325 3.10001
20 OPR 4408 3.08841
24 OPR 1168 3.04883
31 OPR 2833 2.92705
20 OPR 3534 2.88559
21 OPR 4398 2.85018
25 OPR 224 2.83951
36 OPR 3470 2.83926
43 OPR 938 2.82786
44 OPR 931 2.80833
21 OPR 1711 2.75234
22 OPR 4294 2.73222
26 OPR 2973 2.70523
26 OPR 3167 2.6859
27 OPR 3861 2.67374
22 OPR 3509 2.61858
28 OPR 1319 2.61674
45 OPR 1782 2.61639
46 OPR 2335 2.58183
27 OPR 2539 2.56513
37 OPR 3486 2.5247
28 OPR 869 2.50808
23 OPR 3601 2.46826
32 OPR 2985 2.42244
29 OPR 272 2.41714
30 OPR 1791 2.35183
38 OPR 3491 2.34163
23 OPR 1254 2.33288
39 OPR 2493 2.30368
33 OPR 3240 2.2469
31 OPR 293 2.18618
34 OPR 2789 2.13613
24 OPR 3536 2.08899
29 OPR 3856 2.0842
35 OPR 457 2.06238
34 OPR 1922 2.03924
47 OPR 3931 2.03851
36 OPR 3080 2.00541
48 OPR 1763 1.9889
35 OPR 1517 1.97575
36 OPR 4403 1.91872
24 OPR 2771 1.91226
40 OPR 4117 1.87589
30 OPR 2200 1.8717
25 OPR 4004 1.85159
41 OPR 2658 1.77461
49 OPR 2353 1.73731
37 OPR 1721 1.72587
37 OPR 3497 1.69755
26 OPR 3875 1.67222
38 OPR 3614 1.64624
25 OPR 1502 1.61057
26 OPR 894 1.60018
32 OPR 3123 1.58136
31 OPR 3116 1.5811
27 OPR 1528 1.57364
32 OPR 3824 1.56656
39 OPR 3834 1.56235
40 OPR 2461 1.54809
41 OPR 3999 1.44144
33 OPR 4020 1.42279
38 OPR 1307 1.39332
34 OPR 3227 1.38727
50 OPR 2004 1.32357
27 OPR 326 1.24579
28 OPR 3769 1.22155
39 OPR 3451 1.13336
29 OPR 322 1.09004
28 OPR 4377 1.01903
30 OPR 2604 0.98915
42 OPR 3021 0.982355
40 OPR 1289 0.909371
42 OPR 922 0.883356
35 OPR 2817 0.874394
43 OPR 2080 0.827922
36 OPR 3259 0.82676
44 OPR 653 0.808071
41 OPR 20 0.774002
43 OPR 2193 0.685041
44 OPR 3480 0.672862
45 OPR 691 0.649904
37 OPR 4025 0.647571
38 OPR 462 0.620802
29 OPR 4368 0.603022
51 OPR 3485 0.496661
39 OPR 4396 0.480684
31 OPR 703 0.472759
46 OPR 2839 0.417431
33 OPR 2600 0.411199
45 OPR 2969 0.390075
46 OPR 3353 0.375291
40 OPR 442 0.370534
47 OPR 4114 0.26188
48 OPR 1836 0.254138
41 OPR 4264 0.226234
42 OPR 3783 0.213931
52 OPR 937 0.208111
49 OPR 812 0.206054
47 OPR 3345 0.1956
42 OPR 1277 0.19379
48 OPR 2982 0.157963
34 OPR 4361 0.132835
30 OPR 4325 0.11449
43 OPR 3972 0.104074
53 OPR 1994 0.0929351
43 OPR 3585 0.070779
49 OPR 3700 -0.0139002
44 OPR 1466 -0.028104
31 OPR 4381 -0.0290566
50 OPR 3561 -0.0478725
54 OPR 1652 -0.0664144
50 OPR 2339 -0.076633
55 OPR 1810 -0.102099
32 OPR 3421 -0.118807
51 OPR 2787 -0.139598
33 OPR 468 -0.188401
34 OPR 1701 -0.189623
45 OPR 4245 -0.26317
35 OPR 1495 -0.424958
52 OPR 2966 -0.492256
35 OPR 4382 -0.495867
53 OPR 3943 -0.504787
54 OPR 2158 -0.552328
51 OPR 3967 -0.560277
55 OPR 4162 -0.576627
46 OPR 3966 -0.578922
56 OPR 1939 -0.59877
56 OPR 3029 -0.653681
36 OPR 2627 -0.670392
52 OPR 3849 -0.678526
53 OPR 3128 -0.784786
44 OPR 172 -1.13535
45 OPR 151 -1.15067
37 OPR 2611 -1.16379
47 OPR 4306 -1.25258
46 OPR 509 -1.26891
48 OPR 3821 -1.30548
49 OPR 2783 -1.3294
32 OPR 2405 -1.35365
54 OPR 3749 -1.39238
38 OPR 3535 -1.42261
47 OPR 1547 -1.59178
33 OPR 4389 -1.63187
57 OPR 3764 -1.70863
34 OPR 3767 -1.8307
50 OPR 3961 -2.01502
36 OPR 3607 -2.18351
51 OPR 415 -2.2332
58 OPR 1827 -2.29193
55 OPR 3704 -2.32525
57 OPR 2745 -2.36626
37 OPR 2234 -2.40579
58 OPR 499 -2.49012
59 OPR 3366 -2.56216
59 OPR 2410 -2.63983
60 OPR 2164 -2.70082
52 OPR 3797 -3.00048
61 OPR 2972 -3.18454
48 OPR 4034 -3.22404
60 OPR 3417 -3.33697
62 OPR 2560 -3.74052
61 OPR 4000 -3.89845
63 OPR 1785 -3.93474
35 OPR 3658 -4.84805
53 OPR 2483 -4.91803
62 OPR 4282 -4.98026
49 OPR 1153 -5.04162
Chris Hibner
05-03-2012, 07:53
It would undervalue them for sure. Unfortunately, I don't actually have a way to determine which alliance earned coopertition points, since it's not in the full results and I don't have the time to implement a twitter parser.
We went for the coopertition bridge every match, usually with at least 45 seconds left in the match. I'm sure that hurts our OPR, but anyway...
You also don't have a way to determine which robots scored the points in each match, which is why we use OPR. You can use the OPR algorithm on coopertition points to get a "coopertition OPR" that should in theory determine which robots are doing the coopertition bridge balancing.
You also don't have a way to determine which robots scored the points in each match, which is why we use OPR. You can use the OPR algorithm on coopertition points to get a "coopertition OPR" that should in theory determine which robots are doing the coopertition bridge balancing.
The problem is that for every match, I at least get a (foul + baskets + bridge) score for each alliance, which is then used to determine OPR. I don't, however, get a coopertition score for each alliance every match, so you can't apply the same regression math to try and tease out which teams actually earned the coopertition bridge points. With the data actually available in the FRC results, the best you can do is divide each team's CP total by their # of matches played, and hope that correlates with the teams that are actually cooperteting.
If I could parse the twitter feed or if it was available at a more convenient place than twitter (anyone know a link?), then I'd be able to break out fun things like Bridge Power Ratings, Hybrid Ratings, Basket Power Ratings, Foul Ratings, and Coopertition ratings, which would probably help a prospective picking team pick out complementary teams. Come to think of it, that would be useful enough to be worth trying to do.
Chris Hibner
05-03-2012, 08:23
The problem is that for every match, I at least get a (foul + baskets + bridge) score for each alliance, which is then used to determine OPR. I don't, however, get a coopertition score for each alliance, so you can't apply the same regression math to try and tease out which teams actually earned the coopertition bridge points. With the data actually available in the FRC results, the best you can do is divide each team's CP total by their # of matches played, and hope that correlates with the teams that are actually cooperteting.
If I could parse the twitter feed or if it was available at a more convenient place than twitter (anyone know a link?), then I'd be able to break out fun things like Bridge Power Ratings, Hybrid Ratings, Basket Power Ratings, Foul Ratings, and Coopertition ratings.
Ahhh, for some reason I thought they were giving the coopertition bonus in the results. I was competing this week so I haven't seen what the web results look like this year.
PerpetualMotion
05-03-2012, 08:51
I don't, however, get a coopertition score for each alliance every match, so you can't apply the same regression math to try and tease out which teams actually earned the coopertition bridge points.
If you're using an n x n+1 matrix where the n+1 column is the sum of points, can you not use the sum on the standings page under the CP column?
For example
http://www2.usfirst.org/2012comp/Events/sdc/rankings.html
By this theory, you could also do separate "OPR's" for Hybrid Points, Bridge Points, Teleop Points, and Coop Points. That would be interesting to see.
If you really want to, you can pull the standings, and take the CP points/possible CPs * Bridge Points. I think one could make a reasonable argument that each teams contribution towards teh Co-Op bridge should be worth 10 points if successful. Thus for Kettering, looking at the top 2 rankings, you could argue that 2337 deserves a 14CP/(2CP*12matches)*10 points or... 5.8 point bonus. 51 would get 10CP/(2CP*12matches)*10 or 4.17 bonus. You would need to do that in relation to all teams to get a full understanding, and even then it only tells a partial story.
OPR will be an interesting metric this year. While not as low a value as it was in 2009, I expect it will not be as strong a predictor as it was in 2008 or 2010. Smart teams will be looking at what is seeding high, and what is winning, and thus what are good predictors.
Further discussion should probably be in an outside thread so as not to thread-jack Bongle any further than I have.
Thank you Bongle for posting the OPRs.
If you're using an n x n+1 matrix where the n+1 column is the sum of points, can you not use the sum on the standings page under the CP column?
For example
http://www2.usfirst.org/2012comp/Events/sdc/rankings.html
By this theory, you could also do separate "OPR's" for Hybrid Points, Bridge Points, Teleop Points, and Coop Points. That would be interesting to see.
Yeah, I thought of that after I posted :). In fact, I was completely wrong in my previous post - all you need to do an OPR-style calc is the sum of the points scored and what alliance partners that team throughout the regional, so the standings page will in fact be able to give us all the things we want wrt bridge/basket/foul/coopertition points. The individual match scores are actually not necessary (except in past years, FIRST didn't break out the sum of a team's scoring types, which is why I thought the lack of CP/HP/BP/FP in the match scores was a deal-killer).
Alright, starting work on the bridge/basket/foul/coopertition analysis component now. I'm pretty excited. Hopefully done in a few hours (8pm EST).
Ok, here's v19. This includes, for 2012, the ability to rank teams on hybrid/bridge/teleop categories. I assumed that 2 coopertition points = 10 points of bridge scoring.
I may have skipped a version number.
billbo911
05-03-2012, 21:19
OK, I'm running Win 7 x64. When I run OPRNet from a command line, I get an error saying MSVCP100.dll is missing.
I re-installed it, but the error keeps popping up every time I try to run OPRNet.
Any clue what's happening and how to cure this?
OK, I'm running Win 7 x64. When I run OPRNet from a command line, I get an error saying MSVCP100.dll is missing.
I re-installed it, but the error keeps popping up every time I try to run OPRNet.
Any clue what's happening and how to cure this?
Try installing the Visual C++ 2008 runtimes: http://www.microsoft.com/download/en/details.aspx?id=29
billbo911
05-03-2012, 22:37
Try installing the Visual C++ 2008 runtimes: http://www.microsoft.com/download/en/details.aspx?id=29
Nope, same error after install.
I'm having the same issue as Mr. Bill, but on XP x32 (I know, antiquated, right?).
billbo911
06-03-2012, 00:38
I just tried installing the MS Visual C++ 2010 as well, and that didn't fix it either.
Now this is getting odd!
OK, it's a few minutes later now.
I just copied the MSVCP100.dll file from system32 into the folder with OPRNet.
I now get a different error. See the attached image.
I read a few message on the net saying something about linking the dll's statically. Does that make sense to you? This is way out of my league.
Ah, I must have messed up my project settings. I changed its directory on my computer so I could get it in source control, and I must have forgotten to move something else or change a setting.
Edit: Whoops, I'm so used to developing on VS2008 I forgot I've moved to 2010 at home. Ok, so you need these runtimes: http://www.microsoft.com/download/en/details.aspx?id=5555
Here's v20. I made it so the overall OPR is also given the coopertition adjustment (coopertition points * 5, assuming that CPs are points you could have gotten if your alliance assigned you to a different bridge), and did a clean-and-build to attempt to fix the 0xc000007b errors people are getting.
billbo911
06-03-2012, 10:05
Here's v20. I made it so the overall OPR is also given the coopertition adjustment (coopertition points * 5, assuming that CPs are points you could have gotten if your alliance assigned you to a different bridge), and did a clean-and-build to attempt to fix the 0xc000007b errors people are getting.
Yep, working like a champ now!
Bongle,
Can I ask you a favor? Can you please make a single post describing all the command line options? I've been using this awesome little tool for a few seasons now and really love it. The problem is, my PC took a dive last fall and I lost all my batch files I used as templates. So, I need to start from scratch and I am, well, a bit lazy and don't want to read through 16+ pages of posts to find all the tricks I used to generate the data I used to use. :(
Thanks!
It says i cant run because im missing the MSVCP100.dll and I cant find that .dll
Yep, working like a champ now!
Bongle,
Can I ask you a favor? Can you please make a single post describing all the command line options? I've been using this awesome little tool for a few seasons now and really love it. The problem is, my PC took a dive last fall and I lost all my batch files I used as templates. So, I need to start from scratch and I am, well, a bit lazy and don't want to read through 16+ pages of posts to find all the tricks I used to generate the data I used to use. :(
Thanks!
Here's the bat file I used for the week 1 regionals:
oprnet gg 2012 bridge r q > allopr-bridge.txt
oprnet stx 2012 bridge r q >> allopr-bridge.txt
oprnet sdc 2012 bridge r q >> allopr-bridge.txt
oprnet nh 2012 bridge r q >> allopr-bridge.txt
oprnet kc 2012 bridge r q >> allopr-bridge.txt
oprnet tn 2012 bridge r q >> allopr-bridge.txt
oprnet migl 2012 bridge r q >> allopr-bridge.txt
oprnet pah 2012 bridge r q >> allopr-bridge.txt
oprnet gg 2012 teleop r q > allopr-teleop.txt
oprnet stx 2012 teleop r q >> allopr-teleop.txt
oprnet sdc 2012 teleop r q >> allopr-teleop.txt
oprnet nh 2012 teleop r q >> allopr-teleop.txt
oprnet kc 2012 teleop r q >> allopr-teleop.txt
oprnet tn 2012 teleop r q >> allopr-teleop.txt
oprnet migl 2012 teleop r q >> allopr-teleop.txt
oprnet pah 2012 teleop r q >> allopr-teleop.txt
oprnet gg 2012 hybrid r q > allopr-hybrid.txt
oprnet stx 2012 hybrid r q >> allopr-hybrid.txt
oprnet sdc 2012 hybrid r q >> allopr-hybrid.txt
oprnet nh 2012 hybrid r q >> allopr-hybrid.txt
oprnet kc 2012 hybrid r q >> allopr-hybrid.txt
oprnet tn 2012 hybrid r q >> allopr-hybrid.txt
oprnet migl 2012 hybrid r q >> allopr-hybrid.txt
oprnet pah 2012 hybrid r q >> allopr-hybrid.txt
Let's take one line:
"oprnet nh 2012 hybrid r q >> allopr-hybrid.txt"
Broken down:
oprnet - you need this part to start the program :)
nh - indicates you care about the new hampshire regional
2012 - indicates you want results for 2012
hybrid - indicates the statistic you want to print (other options for 2012: opr, teleop, hybrid, bridge)
r - sort teams by ranking (as opposed to 't', which sorts them by team number)
q - quiet mode: makes it not print out status data. Also changes the output format so it's easier to copy/paste into excel. If you want loud mode from the command line for whatever reason, just omit the q.
>> - tells DOS to append all output from oprnet to a text file. The single greater-than ('>') tells it to clear out the file and start over.
allopr-hybrid.txt - which file you want to output to.
The q is optional, and the ">> blah.txt", being a DOS command, is also optional. If you don't have the ">> blah.txt", it'll just spit to your command-line window.
Note that because I'm lazy and because I doubt there's that much use nowadays of the more esoteric parameters like SAA, PM, or DPR, I don't really support them and if the app crashes when you try to use one, I am not that bothered. In 2013, I'm likely to not care very much if the bridge/teleop/hybrid feature gets broken as well.
billbo911
06-03-2012, 11:35
Ah, I must have messed up my project settings. I changed its directory on my computer so I could get it in source control, and I must have forgotten to move something else or change a setting.
Edit: Whoops, I'm so used to developing on VS2008 I forgot I've moved to 2010 at home. Ok, so you need these runtimes: http://www.microsoft.com/download/en/details.aspx?id=5555
It says i cant run because im missing the MSVCP100.dll and I cant find that .dll
Dodar,
First, follow the link in Bongle's message above and add the Visual 2010 runtimes. Then download and run his v.20 and you should find it works again.
Here's the bat file I used for the week 1 regionals:
oprnet gg 2012 bridge r q > allopr-bridge.txt
oprnet stx 2012 bridge r q >> allopr-bridge.txt
oprnet sdc 2012 bridge r q >> allopr-bridge.txt
oprnet nh 2012 bridge r q >> allopr-bridge.txt
oprnet kc 2012 bridge r q >> allopr-bridge.txt
oprnet tn 2012 bridge r q >> allopr-bridge.txt
oprnet migl 2012 bridge r q >> allopr-bridge.txt
oprnet pah 2012 bridge r q >> allopr-bridge.txt
oprnet gg 2012 teleop r q > allopr-teleop.txt
oprnet stx 2012 teleop r q >> allopr-teleop.txt
oprnet sdc 2012 teleop r q >> allopr-teleop.txt
oprnet nh 2012 teleop r q >> allopr-teleop.txt
oprnet kc 2012 teleop r q >> allopr-teleop.txt
oprnet tn 2012 teleop r q >> allopr-teleop.txt
oprnet migl 2012 teleop r q >> allopr-teleop.txt
oprnet pah 2012 teleop r q >> allopr-teleop.txt
oprnet gg 2012 hybrid r q > allopr-hybrid.txt
oprnet stx 2012 hybrid r q >> allopr-hybrid.txt
oprnet sdc 2012 hybrid r q >> allopr-hybrid.txt
oprnet nh 2012 hybrid r q >> allopr-hybrid.txt
oprnet kc 2012 hybrid r q >> allopr-hybrid.txt
oprnet tn 2012 hybrid r q >> allopr-hybrid.txt
oprnet migl 2012 hybrid r q >> allopr-hybrid.txt
oprnet pah 2012 hybrid r q >> allopr-hybrid.txt
Let's take one line:
"oprnet nh 2012 hybrid r q >> allopr-hybrid.txt"
Broken down:
oprnet - you need this part to start the program :)
nh - indicates you care about the new hampshire regional
2012 - indicates you want results for 2012
hybrid - indicates the statistic you want to print (other options for 2012: opr, teleop, hybrid, bridge)
r - sort teams by ranking (as opposed to 't', which sorts them by team number)
q - quiet mode: makes it not print out status data. Also changes the output format so it's easier to copy/paste into excel. If you want loud mode from the command line for whatever reason, just omit the q.
>> - tells DOS to append all output from oprnet to a text file. The single greater-than ('>') tells it to clear out the file and start over.
allopr-hybrid.txt - which file you want to output to.
The q is optional, and the ">> blah.txt", being a DOS command, is also optional. If you don't have the ">> blah.txt", it'll just spit to your command-line window.
Note that because I'm lazy and because I doubt there's that much use nowadays of the more esoteric parameters like SAA, PM, or DPR, I don't really support them and if the app crashes when you try to use one, I am not that bothered. In 2013, I'm likely to not care very much if the bridge/teleop/hybrid feature gets broken as well.
Bongle,
As always, you have exceeded my expectations. Thanks for getting exactly what I am looking for spelled out so quickly!!:D
The Lucas
06-03-2012, 12:45
Great work as always.
Where do get the data from? FMS Twitter Feed? FRCspy?
Great work as always.
Where do get the data from? FMS Twitter Feed? FRCspy?
USFirst, with TheBlueAlliance as a backup*. The bridge/hybrid/teleop stuff requires the USFirst team rankings page to be up.
*I haven't actually tested the TBA backup code in a while, I'm not sure it still works since it is at least 2 years old.
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