(1) #50 California-Santa Cruz (15-7)

1437.65 (142)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
31 California Loss 8-13 -19.51 142 6.6% Counts Jan 28th Santa Barbara Invitational 2023
7 Carleton College** Loss 2-14 0 141 0% Ignored (Why) Jan 28th Santa Barbara Invitational 2023
70 Northwestern Win 11-6 23.18 145 6.25% Counts (Why) Jan 28th Santa Barbara Invitational 2023
25 California-Davis Loss 6-11 -17.62 141 6.25% Counts Jan 28th Santa Barbara Invitational 2023
70 Northwestern Win 11-10 -5.22 145 6.6% Counts Jan 29th Santa Barbara Invitational 2023
29 UCLA Win 9-5 45.44 141 5.67% Counts (Why) Jan 29th Santa Barbara Invitational 2023
39 Santa Clara Loss 5-11 -34.19 141 6.42% Counts (Why) Feb 4th Stanford Open
158 Stanford-B** Win 9-2 0 144 0% Ignored (Why) Feb 4th Stanford Open
34 Portland Loss 5-10 -25.13 142 6.22% Counts Feb 4th Stanford Open
90 Claremont Win 9-3 13.91 140 5.79% Counts (Why) Feb 4th Stanford Open
119 San Diego State Win 12-1 0.48 142 6.72% Counts (Why) Feb 5th Stanford Open
87 Southern California Win 9-3 15.26 142 5.79% Counts (Why) Feb 5th Stanford Open
87 Southern California Win 7-2 13.29 142 5.08% Counts (Why) Feb 5th Stanford Open
108 California-San Diego-B Win 8-5 -2.08 141 5.79% Counts (Why) Feb 5th Stanford Open
79 Nevada-Reno Win 9-6 11.75 142 6.98% Counts Feb 18th Santa Clara Rage Tournament
150 Arizona State** Win 13-0 0 143 0% Ignored (Why) Feb 18th Santa Clara Rage Tournament
108 California-San Diego-B Win 10-4 8.29 141 6.86% Counts (Why) Feb 18th Santa Clara Rage Tournament
178 Chico State** Win 13-1 0 146 0% Ignored (Why) Feb 18th Santa Clara Rage Tournament
196 California-Davis-B** Win 13-0 0 178 0% Ignored (Why) Feb 18th Santa Clara Rage Tournament
39 Santa Clara Loss 6-7 -1.62 141 6.5% Counts Feb 19th Santa Clara Rage Tournament
79 Nevada-Reno Loss 6-7 -26.88 142 6.5% Counts Feb 19th Santa Clara Rage Tournament
197 California-B** Win 13-2 0 153 0% Ignored (Why) Feb 19th Santa Clara Rage Tournament
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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.