(12) #166 UCLA-B (7-10)

837.04 (2)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
162 Arizona Loss 4-7 -26.76 10 5.3% Counts Feb 1st Presidents Day Qualifiers 2025
194 Cal State-Long Beach Win 7-5 5.08 13 5.53% Counts Feb 1st Presidents Day Qualifiers 2025
104 California-San Diego-B Loss 3-8 -9.74 1 5.41% Counts (Why) Feb 1st Presidents Day Qualifiers 2025
25 UCLA** Loss 2-13 0 10 0% Ignored (Why) Feb 1st Presidents Day Qualifiers 2025
115 Arizona State Loss 5-12 -17.25 33 6.68% Counts (Why) Feb 2nd Presidents Day Qualifiers 2025
194 Cal State-Long Beach Win 7-3 19.07 13 5.05% Counts (Why) Feb 2nd Presidents Day Qualifiers 2025
220 California-San Diego-C Win 10-2 9.55 11 6.08% Counts (Why) Feb 2nd Presidents Day Qualifiers 2025
194 Cal State-Long Beach Loss 2-3 -17.26 13 4.5% Counts Mar 2nd Claremont Classic 2025
104 California-San Diego-B Loss 4-13 -16.36 1 8.77% Counts (Why) Mar 2nd Claremont Classic 2025
220 California-San Diego-C Win 5-2 8.29 11 5.32% Counts (Why) Mar 2nd Claremont Classic 2025
126 Claremont-B Loss 3-8 -23.65 10 6.82% Counts (Why) Mar 2nd Claremont Classic 2025
194 Cal State-Long Beach Win 5-4 -7.95 13 6.39% Counts Mar 8th Gnomageddon
104 California-San Diego-B Win 3-2 27.77 1 4.77% Counts (Why) Mar 8th Gnomageddon
199 California-Santa Barbara-B Win 9-4 27.91 26 7.69% Counts (Why) Mar 8th Gnomageddon
89 San Diego State Loss 4-9 -3.46 31 7.69% Counts (Why) Mar 8th Gnomageddon
63 California-Irvine Loss 5-9 23.98 30 7.98% Counts Mar 9th Gnomageddon
104 California-San Diego-B Loss 3-5 0.72 1 6.03% Counts Mar 9th Gnomageddon
**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.