This is some pretty awesome data Caleb! I have been working on my own script to pull down the match data, organize it, and run various calculations on it. This is not exactly simple stuff, but it's given me the chance to practice my (not-so-great) scripting skills, refresh on some linear algebra, and of course play with ROBOT DATA in JMP.
I think using the real match data (microbuns method) to add the +20 for a breach and +25 for a capture to Qual matches is the best way to calculate this new OPR (I call it "Modified OPR"). It's also a pretty simple modification to my OPR calculation script since I already have the data columns there for breach and capture. Obviously I only add this to the final score if the match is not an elims match. This is most accurate to how elims matches are truly scored. I prefer to let the calculated contribution to tower weakening and defense breaching speak for itself in the analysis of those columns by themselves.
Code:
(if breach=='true')score+=20;} if(capture=='true'){score+=25;}
microbuns, I get the same results as you for 2016_ONTO with my Perl OPR calculator if I use data from only the qualification matches. Always nice to double-check work
.
One thing I would like to hear opinions on is if eliminations match data should be use in OPR calculations. My results change significantly when I factor in elims data for my Modified OPR and Regular OPR. See below (sorted by 'Mod OPR Qual'). OPRs tend to drop for robots in elims, probably due to the "cap" for breach points, the alliance partnership with two other good teams, and the fact that defense is a bigger factor in elims.
Perhaps someone who attended this regional could comment which OPR more accurately reflects true robot performance (specifically looking at 2013, 610, 1241 and 1305 in this list since they change rank depending on which OPR I rank by).
Code:
Team Mod OPR ALL OPR ALL Mod OPR Qual OPR Qual
2056 87.76 69.46 99.25 77.16
1114 76.15 59.84 73.32 57.41
118 59.85 49.83 69.96 56.85
2013 54.16 41.92 66.19 48.66
610 48.24 36.67 60.95 43.7
1241 58.48 46.65 58.63 46.11
1305 52.56 38.84 47.19 36.43
4476 49.78 36.59 45.98 33.27
5807 46.69 35.65 43.8 34.76
296 43.15 31.33 42.91 30.38
4618 42.65 32.17 42.07 31.23
5596 28.24 25.83 40.99 32.78
4976 36.67 26.41 39.1 27.33
3117 38.74 33.71 39.04 32.88
5031 34.44 28.27 38.59 30.12
1547 37.79 30.53 37.5 30.39
4783 31.54 24.96 37.13 27.57
5036 39.98 32.47 34.46 29.24
1325 38.05 27.82 32.7 25.3
4732 34.1 27.2 31.4 25.61
1285 30.56 23.24 30.11 22.79
746 30.8 22.05 29.9 22.04
4704 31.71 23.86 28.82 22.14
2634 21.9 20.42 28.16 24.64
2228 27.65 22.06 27.98 22.33
2935 27.59 23.73 27.61 23.51
4308 24.77 22.28 25.2 22.8
6125 23.34 22.21 23.46 22.72
4248 23.54 18.12 23.21 18.17
2185 22.2 18.32 22.47 18.55
2340 22.77 23.04 22.18 22.82
4939 21.37 23.62 21.89 23.83
4343 16.26 15.33 21.06 17.75
4525 21.85 22.16 20.95 21.7
1075 22.49 18.58 20.06 17.18
4252 19.4 13.59 18.36 13.23
3710 23.6 21.57 15.24 16.59
5580 12.24 14.17 14.99 15.94
4015 13.23 11.04 13.24 11.12
5428 12.75 14.08 13.04 13.33
6141 18.76 18.79 12.72 15.38
2198 12.85 9.32 12.64 9.45
6070 12.56 10.67 10.16 9.52
6046 11.9 12.28 9.15 10.69
1246 11.73 11.87 8.54 9.98
3541 7.99 9.23 8.04 9.37
6140 6.63 11.06 6.14 11.04
5076 6.73 6.92 5.78 6.43
5094 -4.85 0.26 -5.58 -0.51