(12) #34 Oklahoma Christian (13-4)

1565.79 (37)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
89 Central Florida Win 11-7 7.31 23 5.34% Counts Mar 19th Mens College Centex
100 Iowa State Win 13-6 12.92 38 5.48% Counts (Why) Mar 19th Mens College Centex
65 California-Santa Barbara Loss 11-12 -17.62 10 5.48% Counts Mar 19th Mens College Centex
16 Texas Loss 6-13 -21.08 29 5.48% Counts (Why) Mar 19th Mens College Centex
21 McGill Loss 10-15 -17.54 39 5.48% Counts Mar 20th Mens College Centex
86 Iowa Win 12-11 -11.26 34 5.48% Counts Mar 20th Mens College Centex
65 California-Santa Barbara Win 11-5 22.33 10 5.03% Counts (Why) Mar 20th Mens College Centex
59 Missouri S&T Win 10-6 23.08 25 5.98% Counts (Why) Apr 9th Ozarks D III College Mens CC 2022
107 John Brown Win 12-6 10.68 9 6.35% Counts (Why) Apr 9th Ozarks D III College Mens CC 2022
173 Truman State Win 13-6 -4.76 40 6.52% Counts (Why) Apr 9th Ozarks D III College Mens CC 2022
173 Truman State Win 11-5 -4.34 40 5.98% Counts (Why) Apr 10th Ozarks D III College Mens CC 2022
107 John Brown Win 12-6 10.68 9 6.35% Counts (Why) Apr 10th Ozarks D III College Mens CC 2022
59 Missouri S&T Loss 9-15 -54.57 25 7.76% Counts Apr 30th South Central D III College Mens Regionals 2022
179 Colorado School of Mines** Win 15-6 0 53 0% Ignored (Why) Apr 30th South Central D III College Mens Regionals 2022
107 John Brown Win 15-5 14.99 9 7.76% Counts (Why) Apr 30th South Central D III College Mens Regionals 2022
59 Missouri S&T Win 15-12 14.04 25 7.76% Counts May 1st South Central D III College Mens Regionals 2022
107 John Brown Win 15-6 14.99 9 7.76% Counts (Why) May 1st South Central D III College Mens Regionals 2022
**Blowout Eligible. Learn more about how this works here.

FAQ

The results on this page ("USAU") are the results of an implementation of the USA Ultimate Top 20 algorithm, which is used to allocate post season bids to both colleg and club ultimate teams. The data was obtained by scraping USAU's score reporting website. Learn more about the algorithm here. TL;DR, here is the rating function. Every game a team plays gets a rating equal to the opponents rating +/- the score value. With all these data points, we iterate team ratings until convergence. There is also a rule for discounting blowout games (see next FAQ)
For reference, here is handy table with frequent game scrores and the resulting game value:
"...if a team is rated more than 600 points higher than its opponent, and wins with a score that is more than twice the losing score plus one, the game is ignored for ratings purposes. However, this is only done if the winning team has at least N other results that are not being ignored, where N=5."

Translation: if a team plays a game where even earning the max point win would hurt them, they can have the game ignored provided they win by enough and have suffficient unignored results.