(42) #144 Bates (11-9)

1059.56 (225)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
207 Northeastern-B Win 8-5 8.2 151 4.86% Counts (Why) Mar 8th Grand Northeast Kickoff 2025
223 Colby Loss 5-6 -22.37 103 4.47% Counts Mar 8th Grand Northeast Kickoff 2025
381 New Hampshire** Win 9-0 0 102 0% Ignored (Why) Mar 8th Grand Northeast Kickoff 2025
393 Middlebury-B** Win 13-0 0 102 0% Ignored (Why) Mar 8th Grand Northeast Kickoff 2025
307 Amherst Win 9-7 -25.08 114 5.39% Counts Mar 9th Grand Northeast Kickoff 2025
279 Brown-B Win 8-5 -7.14 101 4.86% Counts (Why) Mar 9th Grand Northeast Kickoff 2025
207 Northeastern-B Win 15-10 10.02 151 5.87% Counts Mar 9th Grand Northeast Kickoff 2025
218 MIT Loss 10-11 -31.43 84 6.59% Counts Mar 22nd PBR State Open
112 Bowdoin Loss 9-10 1.41 174 6.59% Counts Mar 22nd PBR State Open
334 Bentley** Win 15-5 0 115 0% Ignored (Why) Mar 22nd PBR State Open
166 Brandeis Loss 8-10 -24.01 68 6.42% Counts Mar 23rd PBR State Open
122 Boston University Win 9-7 24.96 100 6.05% Counts Mar 23rd PBR State Open
290 Worcester Polytechnic** Win 13-4 0 88 0% Ignored (Why) Mar 23rd PBR State Open
68 Wesleyan Loss 8-13 -9.34 232 6.99% Counts Mar 29th Easterns 2025
45 Elon Loss 5-13 -4.09 22 6.99% Counts (Why) Mar 29th Easterns 2025
78 Richmond Loss 8-13 -15.6 68 6.99% Counts Mar 29th Easterns 2025
89 North Carolina-Asheville Win 13-12 27.6 44 6.99% Counts Mar 29th Easterns 2025
73 Williams Loss 12-13 15.06 91 6.99% Counts Mar 30th Easterns 2025
70 Franciscan Win 13-10 51.01 180 6.99% Counts Mar 30th Easterns 2025
46 Middlebury Loss 9-15 1.71 7 6.99% Counts Mar 30th Easterns 2025
**Blowout Eligible. Learn more about how this works here.

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.