(7) #78 Grand Canyon (13-5)

1219.9 (211)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
180 Arizona Win 10-5 -4.46 317 3.95% Counts (Why) Jan 25th New Year Fest 2025
114 Arizona State Win 8-7 -5.72 240 3.95% Counts Jan 25th New Year Fest 2025
242 Arizona-B** Win 13-1 0 302 0% Ignored (Why) Jan 25th New Year Fest 2025
187 Colorado-B Win 11-6 -7.7 282 4.21% Counts (Why) Jan 25th New Year Fest 2025
107 Denver Win 10-8 3.35 293 4.33% Counts Jan 26th New Year Fest 2025
106 San Diego State Loss 6-9 -24.65 356 3.95% Counts Jan 26th New Year Fest 2025
114 Arizona State Win 8-4 19.02 240 5.95% Counts (Why) Mar 29th Canyon Classic
114 Arizona State Win 9-3 22.17 240 6.19% Counts (Why) Mar 29th Canyon Classic
134 Northern Arizona Loss 6-7 -34.86 273 6.19% Counts Mar 29th Canyon Classic
134 Northern Arizona Win 8-5 3.31 273 6.19% Counts (Why) Mar 29th Canyon Classic
180 Arizona** Win 11-3 0 317 0% Ignored (Why) Apr 12th Desert D I Womens Conferences 2025
114 Arizona State Win 11-6 24.4 240 7.94% Counts (Why) Apr 12th Desert D I Womens Conferences 2025
10 California-San Diego** Loss 1-15 0 382 0% Ignored (Why) Apr 26th Southwest D I College Womens Regionals 2025
123 California-San Diego-B Win 13-9 11.91 351 9.43% Counts Apr 26th Southwest D I College Womens Regionals 2025
106 San Diego State Win 13-8 32.89 356 9.43% Counts Apr 26th Southwest D I College Womens Regionals 2025
41 Southern California Loss 10-15 -10.4 269 9.43% Counts Apr 26th Southwest D I College Womens Regionals 2025
114 Arizona State Win 11-9 -1.54 240 9.43% Counts Apr 27th Southwest D I College Womens Regionals 2025
68 Santa Clara Loss 10-13 -25.81 287 9.43% Counts Apr 27th Southwest D I College Womens Regionals 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.