(14) #35 California-Santa Cruz (11-6)

1328.21 (723)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
30 Brigham Young Loss 10-11 -3.85 701 6.86% Counts Jan 25th Santa Barbara Invite 2020
6 California-Santa Barbara Loss 8-13 9.76 700 6.86% Counts Jan 25th Santa Barbara Invite 2020
17 Northwestern Loss 7-13 -16.99 701 6.86% Counts Jan 25th Santa Barbara Invite 2020
4 Vermont Loss 8-9 37.07 698 6.49% Counts Jan 25th Santa Barbara Invite 2020
37 Cal Poly-SLO Loss 5-10 -40.18 685 6.1% Counts Jan 26th Santa Barbara Invite 2020
38 Washington University Win 9-8 3.28 697 6.49% Counts Jan 26th Santa Barbara Invite 2020
76 Colorado-B** Win 12-4 0 0% Ignored (Why) Feb 1st Presidents’ Day Qualifier Women
67 California-San Diego-B Win 10-4 10.49 6.32% Counts (Why) Feb 1st Presidents’ Day Qualifier Women
62 Chico State Win 10-6 7.75 6.64% Counts (Why) Feb 1st Presidents’ Day Qualifier Women
65 Occidental Win 11-9 -12.56 7.24% Counts Feb 2nd Presidents’ Day Qualifier Women
52 Cal State-Long Beach Loss 9-10 -32.91 7.24% Counts Feb 2nd Presidents’ Day Qualifier Women
67 California-San Diego-B Win 8-4 7.34 5.75% Counts (Why) Feb 2nd Presidents’ Day Qualifier Women
77 Humboldt State** Win 13-1 0 0% Ignored (Why) Feb 8th Stanford Open 2020
82 Lewis & Clark Win 13-6 -19.06 7.63% Counts (Why) Feb 8th Stanford Open 2020
50 San Diego State Win 13-4 29.85 130 7.63% Counts (Why) Feb 8th Stanford Open 2020
19 California-Davis Win 6-5 23.61 645 5.81% Counts Feb 9th Stanford Open 2020
63 Santa Clara Win 7-5 -3.91 6.07% Counts Feb 9th Stanford Open 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.