(30) #124 California-San Diego-B (9-8)

908.98 (116)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
171 California-Irvine Win 10-3 12.83 36 5.59% Counts (Why) Feb 1st Presidents’ Day Qualifier Women
125 Chico State Loss 7-8 -7.53 129 5.68% Counts Feb 1st Presidents’ Day Qualifier Women
58 California-Santa Cruz Loss 4-10 -8.43 91 5.59% Counts (Why) Feb 1st Presidents’ Day Qualifier Women
142 Colorado-B Win 7-6 0.62 47 5.29% Counts Feb 1st Presidents’ Day Qualifier Women
148 Arizona State Win 10-3 25.13 44 5.59% Counts (Why) Feb 2nd Presidents’ Day Qualifier Women
96 Occidental Loss 7-8 3.29 32 5.68% Counts Feb 2nd Presidents’ Day Qualifier Women
58 California-Santa Cruz Loss 4-8 -5.74 91 5.08% Counts Feb 2nd Presidents’ Day Qualifier Women
145 UCLA-B Win 9-4 32.05 90 6.55% Counts (Why) Feb 29th 2nd Annual Claremont Ultimate Classic
96 Occidental Loss 5-7 -9.98 32 6.29% Counts Feb 29th 2nd Annual Claremont Ultimate Classic
161 Claremont Win 8-7 -14.69 114 7.04% Counts Feb 29th 2nd Annual Claremont Ultimate Classic
140 Santa Clara Win 9-4 36.59 232 6.91% Counts (Why) Mar 7th Santa Clara Rage Home Tournament 2020
196 California-B** Win 9-3 0 122 0% Ignored (Why) Mar 7th Santa Clara Rage Home Tournament 2020
144 Nevada-Reno Win 7-6 -0.56 203 6.91% Counts Mar 7th Santa Clara Rage Home Tournament 2020
86 San Diego State University Loss 5-8 -13.99 18 6.91% Counts Mar 7th Santa Clara Rage Home Tournament 2020
163 Sonoma State Win 8-6 -3.55 12 7.17% Counts Mar 8th Santa Clara Rage Home Tournament 2020
96 Occidental Loss 2-7 -27.12 32 6.06% Counts (Why) Mar 8th Santa Clara Rage Home Tournament 2020
86 San Diego State University Loss 6-10 -19.18 18 7.66% Counts Mar 8th Santa Clara Rage Home Tournament 2020
**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.