(11) #87 Bates (14-6)

1332.33 (40)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
81 Wesleyan Loss 6-9 -18.78 81 4.51% Counts Mar 2nd No Sleep till Brooklyn 2024
73 Wellesley Loss 2-12 -27.68 78 4.87% Counts (Why) Mar 2nd No Sleep till Brooklyn 2024
201 Columbia-B Win 6-3 -12.43 143 3.49% Counts (Why) Mar 2nd No Sleep till Brooklyn 2024
201 Columbia-B** Win 14-2 0 143 0% Ignored (Why) Mar 3rd No Sleep till Brooklyn 2024
164 SUNY-Stony Brook Win 9-2 3.27 302 4.2% Counts (Why) Mar 3rd No Sleep till Brooklyn 2024
130 Boston University Win 8-6 -0.63 6 5.49% Counts Mar 30th Northeast Classic 2024
111 NYU Win 10-4 24.19 230 5.59% Counts (Why) Mar 30th Northeast Classic 2024
52 Haverford/Bryn Mawr Win 7-5 30.29 8 5.08% Counts Mar 30th Northeast Classic 2024
150 RIT Win 11-3 8.46 24 5.87% Counts (Why) Mar 31st Northeast Classic 2024
73 Wellesley Win 10-6 34.64 78 5.87% Counts (Why) Mar 31st Northeast Classic 2024
81 Wesleyan Win 8-4 31.37 81 5.08% Counts (Why) Mar 31st Northeast Classic 2024
52 Haverford/Bryn Mawr Loss 8-11 -8.75 8 6.4% Counts Mar 31st Northeast Classic 2024
145 Dartmouth Loss 6-7 -34.8 42 5.94% Counts Apr 13th North New England D III Womens Conferences 2024
- Colby** Win 11-2 0 0% Ignored (Why) Apr 13th North New England D III Womens Conferences 2024
185 Bowdoin** Win 14-0 0 67 0% Ignored (Why) Apr 13th North New England D III Womens Conferences 2024
92 Middlebury Loss 5-6 -8.8 159 5.46% Counts Apr 13th North New England D III Womens Conferences 2024
166 Smith Win 12-2 4.85 8.19% Counts (Why) May 4th New England D III College Womens Regionals 2024
73 Wellesley Win 10-9 17.21 78 8.54% Counts May 4th New England D III College Womens Regionals 2024
109 Brandeis Win 9-6 20.7 48 7.59% Counts May 4th New England D III College Womens Regionals 2024
105 Mount Holyoke Loss 3-11 -63.22 221 7.83% 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.