() #39 California-Davis (13-9)

1593.28 (7)

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# Opponent Result Effect % of Ranking Status Date Event
90 Colorado State Win 11-7 4.84 5.06% Jan 26th Santa Barbara Invite 2019
4 California-Santa Barbara Loss 7-13 7.11 5.2% Jan 26th Santa Barbara Invite 2019
37 Washington University Loss 7-8 -2.31 4.62% Jan 26th Santa Barbara Invite 2019
13 Stanford Loss 8-13 -1.85 5.2% Jan 26th Santa Barbara Invite 2019
37 Washington University Win 10-8 18.12 5.06% Jan 27th Santa Barbara Invite 2019
48 California-Santa Cruz Win 10-9 2.88 5.2% Jan 27th Santa Barbara Invite 2019
275 Cal Poly SLO-B** Win 13-0 0 0% Ignored Feb 2nd Presidents Day Qualifiers Women
246 California-B** Win 13-1 0 0% Ignored Feb 2nd Presidents Day Qualifiers Women
187 California-San Diego-B** Win 10-4 0 0% Ignored Feb 2nd Presidents Day Qualifiers Women
107 Chico State Win 13-8 -1.21 5.51% Feb 2nd Presidents Day Qualifiers Women
23 California Loss 8-9 10.97 5.21% Feb 3rd Presidents Day Qualifiers Women
119 UCLA-B Win 12-6 1.29 5.36% Feb 3rd Presidents Day Qualifiers Women
119 UCLA-B Win 10-1 2.19 4.81% Feb 3rd Presidents Day Qualifiers Women
- Humboldt State** Win 13-2 0 0% Ignored Feb 9th Stanford Open 2019
48 California-Santa Cruz Loss 9-10 -12.24 5.84% Feb 9th Stanford Open 2019
107 Chico State Win 9-8 -22.9 5.52% Feb 9th Stanford Open 2019
129 Pacific Lutheran Win 6-5 -21.78 4.44% Feb 10th Stanford Open 2019
14 Colorado Loss 10-12 16.07 6.94% Mar 2nd Stanford Invite 2019
4 California-Santa Barbara Loss 5-10 7.45 6.17% Mar 2nd Stanford Invite 2019
24 Washington Loss 7-11 -13.59 6.76% Mar 2nd Stanford Invite 2019
38 Florida Loss 7-8 -7.04 6.17% Mar 3rd Stanford Invite 2019
50 Whitman Win 11-9 12.29 6.94% Mar 3rd Stanford Invite 2019
**Blowout Eligible

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.