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Unread 12-04-2011, 19:05
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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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Unread 12-04-2011, 19:38
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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
Again this is old data, so go look at the new data in Team 2834's database.
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Unread 13-04-2011, 10:11
Racer26 Racer26 is offline
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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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