() #2 Carleton College (17-2) NC 1

2219.55 (28)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
11 California-Davis Win 12-4 25.3 62 7.84% Counts (Why) Mar 5th Stanford Invite 2022
17 Oregon Win 13-3 3.44 7 8.17% Counts (Why) Mar 5th Stanford Invite 2022
46 Whitman** Win 13-1 0 6 0% Ignored (Why) Mar 5th Stanford Invite 2022
10 California-San Diego Win 12-10 -1.8 10 8.17% Counts Mar 6th Stanford Invite 2022
4 California-Santa Barbara Win 12-8 33.06 48 8.17% Counts Mar 6th Stanford Invite 2022
7 Tufts Win 13-7 35.62 38 8.17% Counts (Why) Mar 6th Stanford Invite 2022
5 British Columbia Win 14-12 14.77 5 9.72% Counts Mar 26th Northwest Challenge
10 California-San Diego Win 15-10 21.01 10 9.72% Counts Mar 26th Northwest Challenge
9 Stanford Win 14-12 0.24 132 9.72% Counts Mar 26th Northwest Challenge
5 British Columbia Loss 13-15 -32.05 5 9.72% Counts Mar 27th Northwest Challenge
3 Colorado Loss 4-15 -70.46 27 9.72% Counts (Why) Mar 27th Northwest Challenge
81 Iowa State** Win 15-2 0 7 0% Ignored (Why) Apr 9th Western North Central D I College Womens CC 2022
134 Nebraska** Win 13-3 0 12 0% Ignored (Why) Apr 9th Western North Central D I College Womens CC 2022
35 Minnesota Win 15-9 -31.28 11 10.91% Counts Apr 9th Western North Central D I College Womens CC 2022
66 Iowa** Win 12-0 0 13 0% Ignored (Why) Apr 30th North Central D I College Womens Regionals 2022
92 Marquette** Win 13-1 0 20 0% Ignored (Why) Apr 30th North Central D I College Womens Regionals 2022
164 Wisconsin-Oshkosh** Win 12-2 0 13 0% Ignored (Why) Apr 30th North Central D I College Womens Regionals 2022
120 Wisconsin-Eau Claire** Win 11-2 0 23 0% Ignored (Why) May 1st North Central D I College Womens Regionals 2022
92 Marquette** Win 12-0 0 20 0% Ignored (Why) May 1st North Central 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.