(2) #126 Sam Houston State (6-11)

709.17 (43)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
123 Tulane Win 8-4 23.88 57 3.94% Counts (Why) Feb 12th Antifreeze 2022
98 Rice Loss 5-7 -4.43 95 3.94% Counts Feb 12th Antifreeze 2022
165 North Texas Win 4-2 7.08 48 2.79% Counts (Why) Feb 12th Antifreeze 2022
134 Arizona State Win 12-4 26.86 35 4.76% Counts (Why) Feb 13th Antifreeze 2022
132 Trinity Win 9-7 10.92 51 4.55% Counts Feb 13th Antifreeze 2022
169 Houston Loss 4-6 -42.06 48 6.05% Counts Apr 16th Texas D I College Womens CC 2022
82 Texas A&M Loss 8-11 -5.99 40 8.34% Counts Apr 16th Texas D I College Womens CC 2022
85 Texas-Dallas Loss 6-10 -16.81 47 7.65% Counts Apr 16th Texas D I College Womens CC 2022
19 Texas** Loss 2-15 0 30 0% Ignored (Why) Apr 16th Texas D I College Womens CC 2022
169 Houston Win 8-5 12.28 48 6.89% Counts (Why) Apr 17th Texas D I College Womens CC 2022
165 North Texas Win 9-5 21.57 48 7.15% Counts (Why) Apr 17th Texas D I College Womens CC 2022
77 Texas State Loss 5-9 -14.31 46 7.15% Counts Apr 17th Texas D I College Womens CC 2022
66 Arkansas Loss 5-12 -16.91 34 8.98% Counts (Why) Apr 30th South Central D I College Womens Regionals 2022
68 Kansas Loss 8-12 -2.92 30 9.36% Counts Apr 30th South Central D I College Womens Regionals 2022
35 Colorado State** Loss 1-13 0 47 0% Ignored (Why) Apr 30th South Central D I College Womens Regionals 2022
82 Texas A&M Loss 9-10 18.03 40 9.36% Counts May 1st South Central D I College Womens Regionals 2022
114 Missouri Loss 8-10 -19.27 25 9.11% Counts May 1st South Central D I College Womens Regionals 2022
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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.