() #48 Texas (6-14)

1459.95 (139)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
87 Southern California Win 9-3 9.12 142 3.87% Counts (Why) Feb 18th President’s Day Invite
17 California-San Diego Loss 7-11 -4.89 141 4.56% Counts Feb 18th President’s Day Invite
12 California-Santa Barbara Loss 7-10 9.68 141 4.43% Counts Feb 18th President’s Day Invite
28 Duke Win 9-7 22.52 139 4.3% Counts Feb 18th President’s Day Invite
24 Carleton College-Eclipse Loss 7-13 -13.99 141 4.68% Counts Feb 19th President’s Day Invite
3 Colorado Loss 5-10 18.85 141 4.16% Counts Feb 19th President’s Day Invite
18 Colorado State Win 9-8 22.09 143 4.43% Counts Feb 20th President’s Day Invite
29 UCLA Win 10-9 16.2 141 4.68% Counts Feb 20th President’s Day Invite
36 Brown Loss 10-11 -0.31 143 5.9% Counts Mar 18th Womens Centex1
35 Michigan Loss 10-13 -10.57 145 5.9% Counts Mar 18th Womens Centex1
14 Virginia Loss 4-13 -8.11 139 5.9% Counts (Why) Mar 18th Womens Centex1
42 Wisconsin Loss 5-12 -33.23 142 5.66% Counts (Why) Mar 18th Womens Centex1
54 Georgia Tech Loss 8-13 -37.84 140 5.9% Counts Mar 19th Womens Centex1
75 Boston University Win 15-7 22.68 105 5.9% Counts (Why) Mar 19th Womens Centex1
45 Washington University Loss 5-7 -15.2 140 4.69% Counts Mar 19th Womens Centex1
6 Brigham Young Loss 7-13 17.62 141 6.25% Counts Mar 25th Northwest Challenge1
2 British Columbia** Loss 3-13 0 141 0% Ignored (Why) Mar 25th Northwest Challenge1
9 Washington Loss 8-13 15.17 141 6.25% Counts Mar 25th Northwest Challenge1
29 UCLA Loss 7-13 -23.54 141 6.25% Counts Mar 26th Northwest Challenge1
74 Utah Win 11-10 -7.37 141 6.25% Counts Mar 26th Northwest Challenge1
**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.