(11) #94 Rhode Island (14-7)

1101.95 (163)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
176 Bentley Win 6-4 -6.84 98 4.12% Counts (Why) Mar 23rd Get Down to Business
233 Northeastern-B** Win 10-1 0 118 0% Ignored (Why) Mar 23rd Get Down to Business
218 Rensselaer Polytech Win 6-4 -20.79 368 4.12% Counts (Why) Mar 23rd Get Down to Business
201 Stonehill Win 7-4 -8.98 54 4.32% Counts (Why) Mar 23rd Get Down to Business
158 Bates Win 8-4 6.76 83 4.78% Counts (Why) Mar 29th New England Open 2025
148 Boston University Win 12-2 13.59 256 5.78% Counts (Why) Mar 29th New England Open 2025
233 Northeastern-B** Win 13-0 0 118 0% Ignored (Why) Mar 29th New England Open 2025
48 McGill Loss 11-13 11.38 228 6.02% Counts Mar 30th New England Open 2025
174 New Hampshire Win 15-4 5.12 177 6.02% Counts (Why) Mar 30th New England Open 2025
174 New Hampshire Win 14-4 5.12 177 6.02% Counts (Why) Mar 30th New England Open 2025
91 SUNY-Buffalo Loss 7-9 -15.5 200 5.53% Counts Mar 30th New England Open 2025
61 Brown Win 8-7 23.9 316 6% Counts Apr 12th Greater New England D I Womens Conferences 2025
61 Brown Loss 2-10 -22.01 316 5.9% Counts (Why) Apr 12th Greater New England D I Womens Conferences 2025
174 New Hampshire Win 7-4 -1.3 177 5.14% Counts (Why) Apr 12th Greater New England D I Womens Conferences 2025
5 Vermont** Loss 0-15 0 385 0% Ignored (Why) Apr 12th Greater New England D I Womens Conferences 2025
151 Boston College Win 15-7 15.71 294 7.59% Counts (Why) Apr 26th New England D I College Womens Regionals 2025
131 Harvard Win 12-10 -2.51 243 7.59% Counts Apr 26th New England D I College Womens Regionals 2025
5 Vermont** Loss 5-15 0 385 0% Ignored (Why) Apr 26th New England D I College Womens Regionals 2025
61 Brown Loss 6-10 -18.48 316 6.96% Counts Apr 27th New England D I College Womens Regionals 2025
38 MIT Loss 7-14 -7.98 312 7.59% Counts Apr 27th New England D I College Womens Regionals 2025
87 Vermont-B Win 8-6 23.56 291 6.51% Counts Apr 27th New England D I College Womens Regionals 2025
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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.