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#1
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Quantitatively Evaluating the Regionals
Now that all of the regional and district events are finished for 2011, does anybody have a favorite way of evaluating which ones were the toughest to win?
This is a fairly complicated question, despite an obvious answer (Michigan State Champs) and some conceptually simple possible methods (ex: total average points per match). I'm toying with this problem for fun, and initially I'm looking at ways to compare the OPR data from regional to regional. For example, one can reason that the high scoring teams have the biggest impact on regional difficulty, and thus calculate OPR minus some threshold for each team, sum that up for the whole event, and in this way determine how much big scoring is present at a given event. I am also interested in the impact of having different numbers of super strong and fairly strong teams present. For example, having just one super powerhouse doesn't make an event really hard to win, because then you can win by getting picked. Having two of those super teams makes it really hard for everyone else, but fairly easy, relatively speaking, for those two teams, even moreso than if there was only one super team. That's assuming they aren't opposed to being allied together. But there are other things going on as well. If it's a big regional with lots of teams, then it's slightly harder for the two super teams to win, because a third team might go undefeated (not facing either super team) and have a higher qualification score, then go onto prevent the super partnership. Also, a regional with exactly 2 super teams, 21 solid teams, and 30 really weak teams might be a bit harder for the super teams since they'd have a weaker 3rd robot than opposing alliances and would have to fight through 3 stacked alliances to win. Another angle to consider this from is that the percentage chance of winning a given event is going to depend on your team's robot ability, represented by OPR or some other measure. Obviously a higher OPR will give you a better chance to win any event... or would it? In the event with two super teams, you might be better off with a medium OPR than a higher OPR, because you'd have a better chance of landing on the top alliance with pick #16. Also, I can envision a pair of events where a higher OPR team would be more likely to win event A than event B, while a medium OPR team would be more likely to win event B than event A. For example, let's say two events already have 3 super strong teams registered, but one has a really deep pool of solid robots in its second tier, while the other only has a couple of solid tier 2 bots. I think the medium OPR team is better off with the deep pool in hopes of either being a 3rd pick or getting on a stacked alliance; in the other event, the medium team is more likely to end up as an alliance captain without any really strong teams to pick as partners. The super team, on the other hand, is probably more likely to win the event with 3 strong robots and a sharp dropoff after that. They can expect to end up on one of two strong alliances and get their chance to duke it out in the finals with the other strong alliance. Anyway, given that difficulty depends on your team's OPR, I think it would be cool to have an algorithm that could output the percentage chance of winning for a mystery team with a given OPR that joins at the last minute. I know that I'm missing a lot of important considerations here. I just think this is an interesting problem to examine. It must be because I'm a baseball stat nerd. |
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#2
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Re: Quantitatively Evaluating the Regionals
Ed Law calculates OPR across all events (all matches, one matrix) in his scouting database. It is on the WorldRank tab. Check it out, it does change the OPR significantly.
For instance here is the OPR data I was using going into Philly last week: Code:
Philly Teams by highest single event OPR 395 37.475 NY 365 33.9129 MD 341 26.0867 FL 486 23.7777 NJ 56 22.9167 DC 103 21.2299 FL 834 20.1278 NJ 1302 19.2485 NJ 3015 18.6522 ROC 1403 16.4453 MD 1143 16.1828 MD 2534 15.9369 DC 1647 14.8564 NJ 816 13.8934 NJ 272 13.8589 NY 303 10.9292 NJ 1980 10.724 MD 2234 10.2987 NJ 1640 9.86629 ROC 316 8.89519 MD 2729 8.60878 NJ 369 8.03446 NY 102 6.69432 NJ 3123 6.59455 DC 223 5.84058 NJ 2607 4.57833 NJ 1517 4.53616 NH 224 4.1761 NJ 2641 3.88772 PIT 225 3.00393 MD 1391 2.3401 NJ 484 1.85067 MD 2053 1.77439 ROC 433 0.239089 DC 423 -0.89371 NJ 1370 -2.85469 MD 204 -3.86119 MD 708 -4.59569 MD 2895 -6.02996 NY 3182 -6.6021 CT 87 -7.83013 MD 709 -7.85528 NJ 203 304 321 357 1495 1712 1791 2229 2539 2559 3151 3167 3553 3629 Code:
Philly teams by WorldRank OPR 365 34.49753988 395 28.12398837 56 27.60206962 341 24.29760008 103 23.33148775 1143 22.87816165 2534 22.51985178 1403 21.13740269 1302 19.92360914 486 19.10922384 834 18.74439376 1647 18.14687306 272 16.36615124 3015 14.28577685 816 13.25102034 303 12.45179496 2234 11.43519307 1980 9.801092345 369 8.987250719 1640 8.695600056 316 8.526063969 3123 6.615008499 223 6.016749535 2729 5.878076428 102 5.156151462 224 4.924877745 225 4.92132435 1517 4.867728693 2607 4.242186796 1391 2.211706164 2053 2.032134126 2641 -0.493929277 433 -0.894736634 423 -1.186731875 484 -1.247363326 1370 -3.46124594 204 -4.21698992 2895 -4.888207753 709 -5.031536874 708 -5.820604497 87 -6.332812955 203 304 321 357 1495 1712 1791 2229 2539 2559 3151 3167 3182 3553 3629 |
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#3
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Re: Quantitatively Evaluating the Regionals
Empirical evidence of 2 high-OPR teams against a handful of medium OPR teams and a bunch of low (or negative) OPR teams: GTR and Waterloo since 2007.
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