(1) #31 California (11-19)

1657.96 (142)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
50 California-Santa Cruz Win 13-8 8.34 142 2.94% Counts Jan 28th Santa Barbara Invitational 2023
7 Carleton College** Loss 6-15 0 141 0% Ignored (Why) Jan 28th Santa Barbara Invitational 2023
70 Northwestern Win 7-5 -2.18 145 2.33% Counts Jan 28th Santa Barbara Invitational 2023
42 Wisconsin Win 13-9 8.08 142 2.94% Counts Jan 28th Santa Barbara Invitational 2023
12 California-Santa Barbara Loss 7-12 -3.63 141 2.94% Counts Jan 29th Santa Barbara Invitational 2023
25 California-Davis Loss 8-9 -1.8 141 2.78% Counts Jan 29th Santa Barbara Invitational 2023
74 Utah Win 9-8 -8.81 141 2.78% Counts Jan 29th Santa Barbara Invitational 2023
3 Colorado Loss 7-13 9.13 141 3.49% Counts Feb 18th President’s Day Invite
53 Cal Poly-SLO Loss 7-9 -18.45 142 3.2% Counts Feb 18th President’s Day Invite
74 Utah Win 13-3 6.02 141 3.49% Counts (Why) Feb 18th President’s Day Invite
25 California-Davis Loss 5-12 -18.65 141 3.35% Counts (Why) Feb 18th President’s Day Invite
17 California-San Diego Loss 6-10 -10.91 141 3.2% Counts Feb 19th President’s Day Invite
11 Oregon Loss 5-14 -5.83 141 3.49% Counts (Why) Feb 19th President’s Day Invite
29 UCLA Loss 6-10 -16.2 141 3.2% Counts Feb 19th President’s Day Invite
87 Southern California Win 10-7 -6.22 142 3.3% Counts Feb 20th President’s Day Invite
53 Cal Poly-SLO Win 9-7 0.05 142 3.2% Counts Feb 20th President’s Day Invite
8 Stanford Loss 5-10 0.06 141 3.69% Counts Mar 11th Stanford Invite Womens
6 Brigham Young Loss 5-11 0.94 141 3.81% Counts (Why) Mar 11th Stanford Invite Womens
20 Western Washington Loss 7-8 -0.1 141 3.69% Counts Mar 11th Stanford Invite Womens
12 California-Santa Barbara Win 7-5 24.86 141 3.3% Counts Mar 11th Stanford Invite Womens
8 Stanford Loss 7-10 7.59 141 3.93% Counts Mar 12th Stanford Invite Womens
3 Colorado** Loss 4-11 0 141 0% Ignored (Why) Mar 12th Stanford Invite Womens
11 Oregon Loss 8-11 3.17 141 4.15% Counts Mar 12th Stanford Invite Womens
10 Northeastern Loss 8-13 -0.91 146 4.4% Counts Mar 18th Womens Centex1
18 Colorado State Loss 7-13 -18.59 143 4.4% Counts Mar 18th Womens Centex1
44 Pennsylvania Win 13-7 17.66 147 4.4% Counts (Why) Mar 18th Womens Centex1
33 Ohio State Win 12-10 9.85 145 4.4% Counts Mar 19th Womens Centex1
42 Wisconsin Win 13-8 15.86 142 4.4% Counts Mar 19th Womens Centex1
10 Northeastern Loss 6-15 -5.69 146 4.4% Counts (Why) Mar 19th Womens Centex1
14 Virginia Loss 13-14 6.8 139 4.4% Counts Mar 19th Womens Centex1
**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.