Offensive Power Rankings for 2008

[Joe Ross]

Originally Posted by IndySam

The penalties are such a huge factor this year, unless you find a way to account for them, this formula won't accurately reflect a teams offensive ability.

This is actually better then a team's offensive ability. It shows a teams point contribution. If a team is consistently penalized, they will have a lower OPR then a team that scores the same points per match but does so without penalties. You would obviously want the latter on your alliance.

Another interesting thing is that a team that constantly gets in the way of it's alliance parters would have a lower OPR then one that scores the same number of points but allows it's alliance partners to live to their full potential.

[cziggy343]

are thier going to be ones for every regional? or would that be an endeavour of the individual teams to do?

[Bongle]

Just finished the complete list. This includes every single 2nd-week and later regional. The first-week regionals have slightly different formatting for match results, and I couldn't include them easily. At least based on this analysis, we finally have an answer for the question: "Is anyone CLOSE to 1114?". The answer: no.

The top 50:

1114	79.0239
2056	52.583
987	51.736
40	50.8061
233	50.1563
330	48.7413
494	47.7625
525	47.3403
217	47.1941
1625	46.0802
1024	45.6433
25	45.2803
103	45.2493
33	45.1412
39	44.6339
175	44.0685
1731	42.2656
1124	42.2552
67	42.1626
368	39.0168
20	37.4932
1718	37.472
191	37.3548
1086	37.3254
16	36.6151
126	36.0601
1251	35.7449
968	35.0079
1574	34.6153
100	34.5714
141	34.3271
1218	34.3093
836	34.1721
381	34.1544
1126	34.0365
383	33.3622
69	33.1613
79	33.0133
469	33.0073
1717	32.3547
254	31.4165
501	31.3563
365	31.2399
111	30.847
1098	30.7075
997	30.6114
1507	30.6009
1156	30.5231
1153	30.4529
47	30.3471

See the attachment for the rest.

[MCahoon]

I don't see entries for any teams I remember from Microsoft-Seattle Regional (Week 4).

[Bongle]

Originally Posted by MCahoon

I don't see entries for any teams I remember from Microsoft-Seattle Regional (Week 4).

It had funny formatting, but upon thinking about it some more, I don't think it should badly affect my program's ability to read it. I'll put it in and re-do them.

In fact, I can think of a way I should be able to get the week 1 regionals working as well.

Check this thread again in 10 minutes, I should have an updated one up.

[Greg Marra]

If you let me know a precise format you want, I can give you a huge CSV dump into the formatting you want from The Blue Alliance's database.

[Gaurav27]

I would also like to see standings of all teams ranked based on their record at the attended official events (Win-Loss-Tie).

[Bongle]

Originally Posted by Greg Marra

If you let me know a precise format you want, I can give you a huge CSV dump into the formatting you want from The Blue Alliance's database.

"Red1 <tab> Red2 <tab> red3 <tab> blue1 <tab> blue2 <tab> blue3 <tab> redscore <tab> bluescore <line feed or carriage return or end of line or whatever>" is all I need. That'd be great. CSV is good too, I'm not particular about the delimiter.

So including week 1, the top 50 now looks like:

1114	68.5388
2056	53.7198
987	51.0249
233	50.3309
330	48.6782
39	44.2954
103	43.4295
1731	42.7127
1124	42.087
67	42.0777
525	41.482
175	40.3134
25	40.2684
217	40.0997
1024	39.8043
1718	38.6849
1086	37.4098
191	37.0664
20	36.9179
40	36.6407
1251	36.1213
368	35.623
121	35.5714
1625	35.182
968	35.1251
494	35.0843
1218	35.0123
1574	34.6153
383	34.1952
141	34.1791
1126	33.9523
79	33.8184
469	33.2445
1717	32.6876
69	32.3057
254	32.2835
126	32.1564
33	32.0724
365	31.1953
1507	30.8839
47	30.8582
1156	30.7724
16	30.6096
1065	30.3857
836	30.1605
381	30.1114
93	29.8324
195	29.8271
1512	29.78

[Greg Marra]

The CSV is too big to attach. Find it here: http://www.thebluealliance.net/cdvid...30_matches.csv

Let me know if that works for you

[Kyler]

Okay I somewhat understand how this is all calculated but I am guessing that somebody has already made an excel file to calculate all this? I tried to download one from '06 but the link was broken so can somebody please upload a new one? Thanks.

[Kyler]

Well, just something interesting I have found. Its to be expected and nothing major but it dies go to show being very percise (adding 4 decimal points) Can change things quite a bit in ranking the teams. To test my own Power Ranking program I ran the GTR results and found my results were different that bongles by up to a point (might not seem like much but once you get to the lower power rankings it is 10 % +) and it changes orders a lot. Here's what i found.



Nevermind, I entered one score wrong. My results are the exact same but with 4 excta decimal points.



I only included a few differences because the teams start to change then and I was too lazy to sort that all out. Also, a big THANKYOU! to everyone that helped me understand this stuff.

[Jacob Plicque]

Kyler,
Will you post your program code for review? I think that your are on to something by adding precision to your calculation.

[Guy Davidson]

Wee, I managed to break java

My inversion algorithm for the 1465x1465 or so matrix runs out of heap space. I'm currently working on an alternative way to get p. Right now, I'm going from Mp = s to p = Minverses. I might try to create an augmented matrix and rref it to get the solution. Any other ideas?

EDIT: Nevermind, I just solved the equation Mp = s.

Greg, I now have the OPR's generated from the entire csv dump you generated. Is there any way you could generate other csv dumps to analyze? By regional, by week, over the last three weeks, etc., all sounds like interesting sets of data to analyze.

[Guy Davidson]

I have the rankings generated from Greg Marra's csv dump of the TBA database.

Top 50:

1114	66.10642467
2056	54.11894734
233	50.73081127
330	48.61296306
987	48.40552663
39	48.06177403
525	45.48888639
67	44.23000818
1731	42.99226989
1124	42.40054838
217	42.10281885
103	41.29156933
40	40.86592771
175	39.4420245
191	39.06592804
469	37.90116922
20	37.75470786
79	37.65042852
1717	37.34613148
141	37.32830996
1024	37.2668216
968	35.93916079
1086	35.8662985
1126	35.81116812
368	35.65581359
494	35.0189302
2171	33.98399753
25	33.89508807
1625	33.79257371
365	33.63738509
254	32.91821392
1718	32.54432471
47	32.49881588
93	32.23816608
1477	32.14182287
1251	31.57996364
1806	31.33327422
16	31.18613493
69	31.04681657
1629	31.01151072
33	30.94122998
1418	30.31278837
195	30.2915486
27	29.90208154
383	29.89513167
71	29.87541039
287	29.76950247
171	29.71637571
148	29.4612061
877	29.34477514

The entire spreadsheet is attached. I'm working with Greg Marra on getting some more specific data sets and analyzing them, and after I do that, I'll post the results. Any specific requests?

[IndySam]

Originally Posted by Joe Ross

This is actually better then a team's offensive ability. It shows a teams point contribution. If a team is consistently penalized, they will have a lower OPR then a team that scores the same points per match but does so without penalties. You would obviously want the latter on your alliance.

Another interesting thing is that a team that constantly gets in the way of it's alliance parters would have a lower OPR then one that scores the same number of points but allows it's alliance partners to live to their full potential.

A team can have a great scoring record and have few penalties but can still have their rating ruined by being on alliances that have scored penalties.

If you can't factor out alliance penalties then there is way too much "luck of the draw" possible in this chart.