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OPR after Week Three Events
The OPR/CCWM numbers up to Week 3 events have been posted, please see
http://www.chiefdelphi.com/media/papers/2174 All events are now included. Enjoy the data! If you find any error or have any questions, please let me know. |
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Thanks for all the work you put into this!
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Thanks for putting this together. Always fun to use these numbers to compare teams between separate events.
Noticed that the WM results page was based on the Max CCWM for teams that have played in multiple tournaments, but the Query page posts and ranks based on the average. Is that an intentional difference? On the Query page 2056 has an OPR of 85.6 for 2nd best, while the OPR results page has them at 86.8, which would be 1st. Also curious about the difference here. |
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The Query page does not use the average. It shows the world OPR and CCWM ranking which is obtained by using all the match data from all the events so far and calculate OPR and CCWM. This way all interactions through teams that attend multiple events will be incorporated in the calculations. So there is no argument about strong or weak competitions. |
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Does anybody know the score of qualification match 72 at New York? It affects teams' OPR because I temporarily put in 0-0 to do the calculations.
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Has anyone calculated Autonomous/Tele/Hanging OPR separately?
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Thanks. Didn't realize that.
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(Hard to see everything when the video cuts away, but it looks like in match 72 we went 4/4 on 5 sets and still had time to hang for 20. :) Unfortunately an autonomous error kept us from beating our personal best performance from match 25.) Our autonomous OPR is quite a bit lower than our average contribution to the autonomous. I wonder if that is because many teams practice lining up for the center autonomous and are moved to the wing when they play with us. If they are not as accurate/practiced from that secondary location that might explain the difference. Moral to the Story... If you are not going to pick up the extra discs in auto please practice a wing location so that you are compatible with those that will. (We are developing an extra disc wing autonomous just in case we are paired with a 7 disc center partner too.) |
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I analyzed 4343's numbers from GTREast, and I would say that our Auto OPR is right where I guessed it would be (I guessed 80% x 3/3, 20% x 2/3 for 16.8 avg, and our OPR is 16.7). Our Climbing OPR is way low though, as is 2056's. Either we didn't hang in as many matches as I thought we did, or something is skewing that, because a hanging OPR of 4.5ish suggests we're hanging for 10 less than half the time. Our Teleop OPR is lower than I'd like, but thankfully there's lots of room for improvement. A slight change to our hopper design should prevent us from dropping our 4th disk out the top of our hopper (this happened about 60% of the time on the way back to the pyramid). Several times in the interest of time, the drivers elected to shoot for the 2pt goal when an alliance partner was using the pyramid. Hard to determine what effect that had on OPR though, since its still scoring points, but saving time. |
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Put a trim pot on your bot. Read it with an analog input. Use that value to trim your autonomous shooter speed. You can easily make tweaks between matches in the heat of competition. No software changes or uploads. |
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If you're worried about a trim pot getting bumped and screwing you up, you can put a very simple text file on the cRIO to adjust your speed. You can change the text file and FTP it to the cRIO in about 10 seconds. We call it our "fudge file" (as in the fudge factor to adjust or speed/angle/etc.). If anyone wants an example of how to do this in LabVIEW, let me know and I'll either post it here or e-mail it to you. |
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If you have 3 free buttons on the operator console, you can use them to adjust values in the fudge file. Use button1 to cycle through the available fudge values in the file to select the one you want to adjust. Use button2 to bump the selected value up. Button3 to bump the selected value down. No need to connect a development computer. |
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Ed,
First off, this is an impressive collection of VBA scripts! Second - when I try to run the refresh data script, I get an error, something about runtime error ' 13' Type mismatch. I opened v3.0, go to the Dallas page, as thats the one I'm interested in, and make sure that I enable macros and a data connection. When I hit ctrl-shift-P it starts doing a lot of stuff but then stops at that error. When I run the step into the command and do it line by line, it seems it's because it's going through the teams list (which is blank at the time) until it hits the word "match" in C353. Any tips? Am I missing a step? I don't see anything else suggested in the instructions page. Thanks! Andrew |
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Heh. OPR After week 4 events, *all of waterloo shoots to the top*
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Furthermore, Wisconsin's highest OPR is approximately 50% of waterloos top 2 oprs.
I see nothing terribly notable about Wisconsin. Waterloo is having possibly the deepest FRC event that's ever happened outside of MSC or IRI. |
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My buddy wasn't comparing waterloo to wisconsin. He was just asking about wisconsin's data.
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Also, with such a low number of teams, the top three teams inflate the average OPR data. |
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They're actually not artificially inflating the OPR of the other teams as they normally would be, thanks to the 277 point match.
Can any other event say that it has 14 teams, or nearly half the teams there with OPR > 20. Yes, the 3 strongest account for most of the biggest scores, but you would expect that. With 64 matches and 32 teams, 1 of the 3 will be in about 50% of the matches. Just because the deepest end of the pool is really deep, doesn't make the remainder any less deep. Any of Waterloo's top 10 would have been a top 3 at Montreal last week. |
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For future reference in case you encounter this issue again, you have the following 2 recourses: 1) Twitter data for that match (for example, see here). 2) If there's only one match score missing, pick a team from each alliance that was in that match. Using the Qual Match Results data, add up the scores for the alliances that team was on. Subtract that from the sum of Auto+Climb+TeleOp for that team in the Team Standings data. That should be the alliance score for the missing match. Example calculation, using Team 1660: Here are Team 1660's alliances and scores at New York, with Match #72 set to a score of "0": Code:
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What is notable about Waterloo is that the top 5 teams all have OPR > 50, and the top 10 are all OPR > 37. Most events from this week I am checking have OPR < 37 by the time you are out of the top 5 showing a clear split of the top teams from everyone else. Of course Waterloo still has that, with the top 2 teams having an OPR > 90 :eek:
Wisconsin has a very strange OPR set. It has 29 teams of OPR > 20 and the top 10 all have OPR > 36, but no one has an OPR > 50. And I already noted in a different thread that OPR compared to average individual robot scores was wrong by at least 5 places for most of the teams I checked. |
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Ed,
What is the significance of the shading of the cells in columns O & R (OPR & CCWM) in the individual event pages? |
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I put in those conditional formatting back in 2008 and never took it out. Basically, when OPR is bigger than average score, or CCWM is bigger than average winning margin, it will turn green. Green is good. It means those teams contribute more than their partners to get the average score. Somebody with a lucky schedule can have very high average score but OPR/CCWM which are the calculated contribution will tell you the true story in most cases. If you only look at OPR/CCWM and ignore average score and average winning margin, the green color does not add any information. I am surprised nobody has ever asked this question. I can take it out in the future. |
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This was the highest quality FRC Regional i've ever seen, all of those teams listed would do well on a field at championship. The field of 32 teams at Waterloo was historically deep, we got a robot that could do 3+ cycles a match with the 23rd pick, 1114/2056 got a long range shooter with the 24th pick, I call that depth. At most regionals during qualifications the event can get a little monotonus with a couple poor matches in a row. At Waterloo there was rarely any slow matches during qualifications, everyone in the stands were engaged, I even saw arena staff and regular Waterloo students getting into the games during qualifications. |
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Ignoring the scores of 1114, 2056, and 4069 during elimination, the average elimination score at Waterloo was 101 (121 if you included them). Compare that to Boilermaker which had an average elimination of 97 (or 88 if you removed 359, 868, and 1747), I'd say that's similar, but I wouldn't say that BMR had that much depth. My guess is that you'd find similar results for other regional competitions. |
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Thank you, Ed, for what is looking like a truly wonderful tool. |
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