(18) #180 Arizona (6-14)

537.6 (317)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
114 Arizona State Loss 8-13 -4.81 240 5.82% Counts Jan 25th New Year Fest 2025
187 Colorado-B Win 8-6 13.72 282 5% Counts Jan 25th New Year Fest 2025
78 Grand Canyon Loss 5-10 5.91 211 5.17% Counts Jan 25th New Year Fest 2025
107 Denver Loss 8-11 7.91 293 5.82% Counts Jan 25th New Year Fest 2025
242 Arizona-B Win 11-5 6.02 302 5.34% Counts (Why) Jan 26th New Year Fest 2025
114 Arizona State Loss 5-8 -1.79 240 4.81% Counts Jan 26th New Year Fest 2025
220 Cal State-Long Beach Win 8-4 12.88 373 4.9% Counts (Why) Feb 1st Presidents Day Qualifiers 2025
123 California-San Diego-B Loss 7-8 14.67 351 5.48% Counts Feb 1st Presidents Day Qualifiers 2025
196 UCLA-B Win 7-4 21 369 4.69% Counts (Why) Feb 1st Presidents Day Qualifiers 2025
30 UCLA** Loss 2-12 0 415 0% Ignored (Why) Feb 1st Presidents Day Qualifiers 2025
40 California** Loss 3-11 0 285 0% Ignored (Why) Feb 2nd Presidents Day Qualifiers 2025
123 California-San Diego-B Loss 4-9 -11.93 351 5.1% Counts (Why) Feb 2nd Presidents Day Qualifiers 2025
251 Colorado College-B Win 15-6 2.02 7.77% Counts (Why) Mar 1st Snow Melt 2025
73 Colorado College** Loss 5-15 0 287 0% Ignored (Why) Mar 1st Snow Melt 2025
107 Denver Loss 3-15 -8.96 293 7.77% Counts (Why) Mar 1st Snow Melt 2025
193 Colorado Mines Loss 11-13 -24.64 288 7.77% Counts Mar 2nd Snow Melt 2025
187 Colorado-B Win 9-8 6.77 282 7.35% Counts Mar 2nd Snow Melt 2025
114 Arizona State Loss 3-15 -15.31 240 7.77% Counts (Why) Mar 2nd Snow Melt 2025
78 Grand Canyon** Loss 3-11 0 211 0% Ignored (Why) Apr 12th Desert D I Womens Conferences 2025
134 Northern Arizona Loss 5-9 -26.05 273 9.43% Counts Apr 12th Desert D I Womens Conferences 2025
**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.