(4) #89 Rice (12-6)

1131.84 (214)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
177 Tulane Win 8-6 -13.77 407 5.07% Counts Feb 8th Rice Antifreeze 2025
136 Trinity Win 9-7 -2.62 229 5.42% Counts Feb 8th Rice Antifreeze 2025
255 Texas-B** Win 12-0 0 215 0% Ignored (Why) Feb 8th Rice Antifreeze 2025
205 Texas A&M Win 11-5 -10.4 244 5.42% Counts (Why) Feb 9th Rice Antifreeze 2025
136 Trinity Win 8-5 6.6 229 4.88% Counts (Why) Feb 9th Rice Antifreeze 2025
73 Colorado College Win 14-10 48.78 287 8.35% Counts Mar 22nd Womens Centex 2025
189 LSU Win 10-5 -5.35 165 7.42% Counts (Why) Mar 22nd Womens Centex 2025
27 Texas** Loss 3-13 0 358 0% Ignored (Why) Mar 22nd Womens Centex 2025
45 Texas-Dallas Loss 3-12 -14.82 261 8.01% Counts (Why) Mar 22nd Womens Centex 2025
67 Illinois Loss 10-13 -13.69 129 8.35% Counts Mar 23rd Womens Centex 2025
12 Utah** Loss 4-15 0 385 0% Ignored (Why) Mar 23rd Womens Centex 2025
44 Washington University Loss 9-14 -3.88 175 8.35% Counts Mar 23rd Womens Centex 2025
251 Colorado College-B** Win 11-4 0 0% Ignored (Why) Apr 12th South Central D III Womens Conferences 2025
200 Truman State** Win 11-3 0 303 0% Ignored (Why) Apr 12th South Central D III Womens Conferences 2025
136 Trinity Win 10-7 6.7 229 9.39% Counts Apr 12th South Central D III Womens Conferences 2025
73 Colorado College Loss 5-12 -48.74 287 9.52% Counts (Why) Apr 13th South Central D III Womens Conferences 2025
73 Colorado College Win 15-12 48.2 287 9.92% Counts Apr 13th South Central D III Womens Conferences 2025
136 Trinity Win 11-8 4.47 229 9.92% Counts Apr 13th South Central D III Womens Conferences 2025
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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.