(1) #109 Brandeis (12-8)

1165.91 (48)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
175 Amherst Win 10-2 5.48 339 4.06% Counts (Why) Mar 3rd Grand Northeast Kickoff
146 New Hampshire Win 14-7 15.05 131 4.65% Counts (Why) Mar 3rd Grand Northeast Kickoff
73 Wellesley Loss 11-13 -0.15 78 4.92% Counts Mar 9th Live Free or Sky 2024
146 New Hampshire Win 14-4 16.88 131 4.92% Counts (Why) Mar 9th Live Free or Sky 2024
173 Bentley Win 7-3 6.82 151 4.01% Counts (Why) Mar 23rd New England Open 2024
216 Northeastern-B** Win 13-2 0 587 0% Ignored (Why) Mar 23rd New England Open 2024
92 Middlebury Loss 6-7 0.67 159 4.57% Counts Mar 23rd New England Open 2024
57 Connecticut Loss 0-13 -13.85 127 5.53% Counts (Why) Mar 23rd New England Open 2024
78 Harvard Loss 3-9 -19.21 18 4.57% Counts (Why) Mar 24th New England Open 2024
230 Clark** Win 11-1 0 1037 0% Ignored (Why) Mar 24th New England Open 2024
216 Northeastern-B** Win 15-2 0 587 0% Ignored (Why) Mar 24th New England Open 2024
172 Stonehill Win 15-6 13.81 6.96% Counts (Why) Apr 20th Metro Boston D III Womens Conferences 2024
173 Bentley Win 15-3 12.21 151 6.96% Counts (Why) Apr 20th Metro Boston D III Womens Conferences 2024
73 Wellesley Loss 10-13 -7.66 78 6.96% Counts Apr 20th Metro Boston D III Womens Conferences 2024
172 Stonehill Win 15-0 15.64 7.82% Counts (Why) May 4th New England D III College Womens Regionals 2024
175 Amherst Win 11-6 6.09 339 7.39% Counts (Why) May 4th New England D III College Womens Regionals 2024
87 Bates Loss 6-9 -18.82 40 6.94% Counts May 4th New England D III College Womens Regionals 2024
105 Mount Holyoke Win 9-7 23.34 221 7.17% Counts May 4th New England D III College Womens Regionals 2024
73 Wellesley Loss 3-8 -24.23 78 6.08% Counts (Why) May 5th New England D III College Womens Regionals 2024
92 Middlebury Loss 3-9 -31.86 159 6.47% 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.