***Stats and OPRs based on Twitter Qual match data as of Fri 3-14-2014 22:30:53 ET.
The usual Twitter data caveats apply.**
NOTE: LOOK FOR UPDATED DATA TO BE POSTED LATER IN THIS THREAD
Stats based on 2654 Qual matches from Twitter data Fri 14 Mar 2014 223053 ET.txt (1.51 KB)
OPR based on Twitter data 3-14-2014 203053 ET revB.XLS (359 KB)
Stats based on 2654 Qual matches from Twitter data Fri 14 Mar 2014 223053 ET.txt (1.51 KB)
OPR based on Twitter data 3-14-2014 203053 ET revB.XLS (359 KB)
Excerpt from the above post:
win foul points awarded:
20 average (mean)
220 max
lose foul points awarded:
** 5 average (mean)**
110 max
The above is a very simple assessment of how the foul points affect this game. 4X as many foul points to the winning alliance…this means that fouls swing a large percentage of matches.
50 point foul is effectively a automatic loss most of the time.
Tragic.
Worst game design since 2003, yet no real action to correct…
Tragic.
20 foul points on average for the winning alliance. That is insane. What makes it worse, is that by the look at average scores, they are not a ton different then last year, but the fouls are worth a ton more. I think the game designers expected higher average match scores to make up for higher foul scores.
Agreed that the impact of foul points is tragic… and that foul points swinging the outcome of the match is likely a significant contributor to this statistic; however, I do think there is another possible/probable cause.
Fouls “take advantage” of less experienced, lower-performing teams. The teams that are more likely to get careless HP fouls, struggle to pickup a ball when inbounding, play hard defense that involves a manipulator flipping out and getting inside an offensive bot, or pin for too long are the teams that are less familiar with the rules, haven’t kept up with the Q&A, and haven’t designed as effective an offensive bot.
The fact that the teams most likely to suffer from the heavy fouls are also the teams that FIRST is having the hardest time retaining isn’t a good thing for FIRST growing at or above average next year.
Consider me more and more on the side of “bring foul values down to 10 and 30.” Keep in mind this is still 333% and 150% the value of fouls in 2013.
Big, Bad, Bobth Post! (319)
Agreed. Quite sad to see some really good strategies play out and then that one tech foul swings it the other way.
I think a 30 point value should be the max assigned to the tech foul. Hopefully, based on average win/loss margins it will have a smaller swing effect on match outcomes.
***Twitter Qual Match Stats
based on Twitter Qual match data as of Sat 15 Mar 2014 20:13:09 ET.
The usual Twitter data caveats apply.**
I’ve removed the Quartile data from the stats report. In their place I will be posting histograms later this evening. Also Twitter-based OPRs. So check back later.
Stats based on Qual matches from Twitter Sat 15Mar2014 201309 ET.txt (1.38 KB)
Stats based on Qual matches from Twitter Sat 15Mar2014 201309 ET.txt (1.38 KB)
***Unpenalized Winning Margin Histogram
based on Twitter Qual match data as of Sat 15 Mar 2014 20:13:09 ET.
The usual Twitter data caveats apply.**
***OPR for Final, Foul, Auto, & TeleOp
based on Twitter Qual match data as of Sat 15 Mar 2014 20:56:33 ET.
The usual Twitter data caveats apply.**
Data is shown for teams which have played at least 6 matches.
OPR (from Twitter data 3-15-2014 205633).xls (369 KB)
OPR (from Twitter data 3-15-2014 205633).xls (369 KB)
Very well presented, your picture is worth a thousand words! Would you mind if I combine your charts with my questionnaire results for submission to FIRST tomorrow?
The questionnaire can be found here.
[would it be possible to calculate the percentage of games finished within +/- 50 points? i.e. a tech foul call or non-call would have swung the results of that game?]
^^^ This says it all. Thank you Nathan. ^^^
You have my permission.
[would it be possible to calculate the percentage of games finished within +/- 50 points? i.e. a tech foul call or non-call would have swung the results of that game?]
See attached chart. Of the 3022 non-tied qual matches in the Twitter data dated 3/15/2014 20:13:09 ET, there were 1619 matches with final score (including awarded foul points) margin less than or equal to 50.
The usual Twitter data caveats apply.
***Alliance Score Residuals
based on Twitter Qual match data as of Sat 15 Mar 2014 20:56:33 ET.**
*Example graph interpretation:
81 - 18 = 62% of Alliance Unpenalized Scores were within +/- 20 points of the “OPR” predicted value.
66 - 32 = 35% of Alliance Unpenalized Scores were within +/- 10 points of the “OPR” predicted value.*
The usual Twitter data caveats apply.
This can be a double whammy for District teams on the cusp of making it to the District Championship. The points for winning qualifying matches can function as the tie-breaker for determining who makes the cut-off and who doesn’t. Your team can do everything right, but if a partner makes a mistake or doesn’t know the rule, there goes 2 points. (And vice versa, you can do everything wrong and still get 2 points!) We do not have the manpower or experience to pull a 51 and record every foul and coach other teams through their problem areas. At our next event we will make a point to bring it up before every match so everyone knows.
At the end of the season I would be curious to see how many teams make or do not make the DCMP by foul points.
I agree that would be an interesting metric, although the match data doesn’t show how deserving the fouls were or how consistently they were called.
As you are probably aware the twitter data (caveats apply) shows 1778 lost one match and won another at Mt Vernon due to fouls, so no net impact.
Yep, and that make me wonder if they are uniformly enough distributed so that it is a net zero effect. I think the safest thing to do is assume that they are deserved. At Mr. Vernon I thought the refs did a great job.
***Red wins 1935; Blue wins 1722; Ties 26
based on Twitter Qual and Elim match data as of Sun 16 Mar 2014 15:32:18 ET.**
The usual Twitter data caveats apply.*
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Does this include eliminations? If so, that would make sense.
The long term trends have been that Qual performance for red is 50% and elimination is ~65%.
Elims only: red wins 415 (66.8%); blue wins 206 (33.2%); ties 3
Quals only: red wins 1520 (50.1%); blue wins 1516 (49.9%); ties 23
Twitter data 3/16 15:32:18
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I thought I understood what these numbers meant, but I’m confused, so could someone explain somthing to me? I’m with team 1825 and the spreadsheet says we have an OPR of over 80 points (the blue alliance agrees.) but our CCWM is -40, could someone explain what those number mean? Thanks.
