(6) #86 Williams (15-5)

1333.84 (10)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
71 Columbia Win 7-6 7.42 33 3.59% Counts Mar 2nd No Sleep till Brooklyn 2024
111 NYU Win 9-5 13.03 230 3.73% Counts (Why) Mar 2nd No Sleep till Brooklyn 2024
164 SUNY-Stony Brook Win 10-4 2.88 302 3.79% Counts (Why) Mar 2nd No Sleep till Brooklyn 2024
58 Cornell Loss 7-10 -8.45 1 4.11% Counts Mar 3rd No Sleep till Brooklyn 2024
73 Wellesley Win 9-8 7.84 78 4.11% Counts Mar 3rd No Sleep till Brooklyn 2024
81 Wesleyan Win 9-8 6.19 81 4.11% Counts Mar 3rd No Sleep till Brooklyn 2024
145 Dartmouth Win 11-4 8.57 42 4.74% Counts (Why) Mar 23rd Rodeo 2024
62 Duke Loss 4-7 -14.15 216 3.93% Counts Mar 23rd Rodeo 2024
138 Liberty Win 10-3 10.06 32 4.51% Counts (Why) Mar 23rd Rodeo 2024
151 North Carolina-B Win 10-3 6.34 75 4.51% Counts (Why) Mar 23rd Rodeo 2024
62 Duke Loss 7-8 1.21 216 4.59% Counts Mar 24th Rodeo 2024
138 Liberty Win 9-6 1.51 32 4.59% Counts Mar 24th Rodeo 2024
166 Smith Win 11-4 3.16 5.64% Counts (Why) Apr 13th South New England D III Womens Conferences 2024
175 Amherst Win 9-5 -6.08 339 5.27% Counts (Why) Apr 13th South New England D III Womens Conferences 2024
105 Mount Holyoke Win 10-5 24.75 221 5.46% Counts (Why) Apr 13th South New England D III Womens Conferences 2024
166 Smith Win 10-5 1.86 6.49% Counts (Why) May 4th New England D III College Womens Regionals 2024
175 Amherst Win 10-7 -18.46 339 6.91% Counts May 4th New England D III College Womens Regionals 2024
92 Middlebury Loss 9-10 -12.13 159 7.31% Counts May 4th New England D III College Womens Regionals 2024
105 Mount Holyoke Loss 8-11 -40.26 221 7.31% Counts May 4th New England D III College Womens Regionals 2024
166 Smith Win 7-3 2.96 5.3% Counts (Why) May 5th New England D III 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.