() #11 Brigham Young (13-7) NW 4

2256.04 (63)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
9 California-Santa Barbara Loss 12-15 -11.4 95 4.72% Counts Jan 26th Santa Barbara Invite 2024
30 Cal Poly-SLO Win 13-12 -14.32 129 4.72% Counts Jan 26th Santa Barbara Invite 2024
5 Stanford Win 11-9 25.42 39 4.72% Counts Jan 27th Santa Barbara Invite 2024
13 Victoria Win 11-8 13.03 32 4.72% Counts Jan 27th Santa Barbara Invite 2024
17 California-Santa Cruz Loss 11-13 -20.13 102 4.72% Counts Jan 27th Santa Barbara Invite 2024
17 California-Santa Cruz Win 10-9 -3.54 102 6.3% Counts Mar 2nd Stanford Invite 2024
28 California Win 8-6 -5.66 28 5.41% Counts Mar 2nd Stanford Invite 2024
7 Colorado Loss 9-10 3.04 32 6.3% Counts Mar 2nd Stanford Invite 2024
10 Washington Loss 12-13 -9.36 91 7.07% Counts Mar 15th NW Challenge 2024
4 Oregon Loss 10-13 -1.15 37 7.07% Counts Mar 16th NW Challenge 2024
26 Wisconsin Win 13-10 -3.86 36 7.07% Counts Mar 16th NW Challenge 2024
13 Victoria Win 13-6 37.85 32 7.07% Counts (Why) Mar 16th NW Challenge 2024
60 Utah State** Win 13-3 0 8 0% Ignored (Why) Apr 13th Big Sky D I Womens Conferences 2024
171 Montana State** Win 13-0 0 3 0% Ignored (Why) Apr 13th Big Sky D I Womens Conferences 2024
116 Montana** Win 13-2 0 72 0% Ignored (Why) Apr 13th Big Sky D I Womens Conferences 2024
25 Utah Win 13-7 18.34 36 8.91% Counts (Why) Apr 13th Big Sky D I Womens Conferences 2024
116 Montana** Win 13-5 0 72 0% Ignored (Why) May 4th Northwest D I College Womens Regionals 2024
4 Oregon Loss 10-13 -1.79 37 10.6% Counts May 4th Northwest D I College Womens Regionals 2024
10 Washington Loss 11-13 -26.88 91 10.6% Counts May 4th Northwest D I College Womens Regionals 2024
154 Oregon State** Win 13-3 0 35 0% Ignored (Why) May 4th Northwest D I College Womens Regionals 2024
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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.