(3) #21 Northeastern (11-11)

1548.06 (23)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
78 Southern California Win 12-8 -2.8 22 4% Counts Mar 19th Womens Centex
14 Florida State Loss 6-12 -16.96 49 3.89% Counts Mar 19th Womens Centex
30 Georgia Tech Win 9-8 1.41 52 3.78% Counts Mar 19th Womens Centex
62 Washington University Win 13-7 7.53 29 4% Counts (Why) Mar 19th Womens Centex
41 Colorado College Win 10-5 13.21 23 3.55% Counts (Why) Mar 20th Womens Centex
13 Pittsburgh Loss 7-9 -4.11 58 3.67% Counts Mar 20th Womens Centex
34 Michigan Win 9-5 13.8 37 3.43% Counts (Why) Mar 20th Womens Centex
39 Boston University Loss 9-11 -24.81 50 5.34% Counts Apr 23rd Metro Boston D I College Womens CC 2022
154 Harvard** Win 13-2 0 64 0% Ignored (Why) Apr 23rd Metro Boston D I College Womens CC 2022
79 MIT Win 12-4 4.59 54 5.12% Counts (Why) Apr 23rd Metro Boston D I College Womens CC 2022
7 Tufts Loss 4-12 -7.49 53 5.12% Counts (Why) Apr 24th Metro Boston D I College Womens CC 2022
79 MIT Win 11-3 4.38 54 4.9% Counts (Why) Apr 24th Metro Boston D I College Womens CC 2022
26 Brown Loss 7-8 -9.63 63 5.32% Counts May 7th New England D I College Womens Regionals 2022
43 Dartmouth Win 11-8 9.25 50 5.99% Counts May 7th New England D I College Womens Regionals 2022
10 Vermont Loss 5-8 -3.65 72 4.95% Counts May 7th New England D I College Womens Regionals 2022
26 Brown Win 5-4 3.38 63 4.12% Counts May 8th New England D I College Womens Regionals 2022
10 Vermont Loss 2-7 -9.83 72 4.34% Counts (Why) May 8th New England D I College Womens Regionals 2022
15 Georgia Loss 12-13 2.63 58 7.12% Counts May 27th 2022 D I College Championships
1 North Carolina** Loss 1-15 0 27 0% Ignored (Why) May 27th 2022 D I College Championships
8 Stanford Loss 3-15 -12.44 15 7.12% Counts (Why) May 28th 2022 D I College Championships
14 Florida State Loss 9-11 -6.82 49 7.12% Counts May 28th 2022 D I College Championships
31 SUNY-Binghamton Win 14-3 38.63 137 7.12% Counts (Why) May 29th 2022 D I College Championships
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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.