(1) #102 Utah (7-14)

922.86 (46)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
62 Cal Poly-SLO Loss 7-9 -0.61 41 4.49% Counts Feb 19th Presidents Day Invite 2022
4 California-Santa Barbara** Loss 2-13 0 48 0% Ignored (Why) Feb 19th Presidents Day Invite 2022
115 California-San Diego-B Win 8-5 14.92 82 4.05% Counts (Why) Feb 20th Presidents Day Invite 2022
3 Colorado** Loss 1-14 0 27 0% Ignored (Why) Feb 20th Presidents Day Invite 2022
43 Colorado College Loss 5-15 -8.57 3 4.89% Counts (Why) Feb 20th Presidents Day Invite 2022
85 Southern California Win 8-7 11.99 66 4.35% Counts Feb 21st Presidents Day Invite 2022
9 Stanford** Loss 2-10 0 132 0% Ignored (Why) Feb 21st Presidents Day Invite 2022
103 Denver Loss 4-6 -16.16 41 4.22% Counts Mar 12th Big Sky Brawl
105 Montana Loss 8-9 -7.53 2 5.5% Counts Mar 12th Big Sky Brawl
107 Montana State Loss 4-10 -34.82 48 5.08% Counts (Why) Mar 12th Big Sky Brawl
75 Portland Loss 6-7 3.11 18 4.81% Counts Mar 12th Big Sky Brawl
188 Boise State Win 10-2 2.11 10 5.08% Counts (Why) Mar 13th Big Sky Brawl
46 Whitman Loss 4-15 -14.83 6 7.76% Counts (Why) Apr 16th Big Sky D I College Womens CC 2022
107 Montana State Win 10-9 6.27 48 7.76% Counts Apr 16th Big Sky D I College Womens CC 2022
- Utah State Loss 11-12 -18.91 17 7.76% Counts Apr 16th Big Sky D I College Womens CC 2022
105 Montana Win 10-8 21.11 2 7.56% Counts Apr 17th Big Sky D I College Womens CC 2022
6 Washington** Loss 4-13 0 72 0% Ignored (Why) May 7th Northwest D I College Womens Regionals 2022
16 Western Washington** Loss 2-13 0 5 0% Ignored (Why) May 7th Northwest D I College Womens Regionals 2022
46 Whitman Loss 8-9 28.59 6 8.73% Counts May 7th Northwest D I College Womens Regionals 2022
107 Montana State Win 9-8 7.12 48 8.73% Counts May 7th Northwest D I College Womens Regionals 2022
107 Montana State Win 13-12 7.57 48 9.23% Counts May 8th Northwest D I College Womens Regionals 2022
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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.