(18) #148 Bates College (10-8)

958.83 (91)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
138 Bowdoin Loss 10-11 -5.47 76 5.3% Counts Mar 26th Layout Pigout 2022
284 Bentley Win 14-9 -4.46 104 5.3% Counts Mar 26th Layout Pigout 2022
295 Haverford Win 12-6 -0.67 39 5.16% Counts (Why) Mar 26th Layout Pigout 2022
123 Williams Loss 14-15 -0.55 127 5.3% Counts Mar 27th Layout Pigout 2022
317 Stonehill** Win 12-4 0 186 0% Ignored (Why) Apr 2nd New England Open
372 Northeastern-C** Win 13-2 0 358 0% Ignored (Why) Apr 2nd New England Open
248 Worcester Polytechnic Institute Win 13-1 15 90 5.61% Counts (Why) Apr 2nd New England Open
187 Bryant Loss 7-9 -23.63 97 5.15% Counts Apr 2nd New England Open
35 Middlebury Loss 12-15 18.23 60 6.3% Counts Apr 17th North New England D III College Mens CC 2022
267 Colby Win 13-11 -15.2 58 6.3% Counts Apr 17th North New England D III College Mens CC 2022
138 Bowdoin Win 10-9 10.23 76 6.3% Counts Apr 17th North New England D III College Mens CC 2022
187 Bryant Win 10-8 7.89 97 6.88% Counts Apr 30th New England D III College Mens Regionals 2022
146 Brandeis Loss 12-13 -9.29 153 7.07% Counts Apr 30th New England D III College Mens Regionals 2022
138 Bowdoin Loss 9-10 -7.44 76 7.07% Counts Apr 30th New England D III College Mens Regionals 2022
284 Bentley Win 12-9 -15.85 104 7.07% Counts Apr 30th New England D III College Mens Regionals 2022
35 Middlebury Loss 9-15 4.28 60 7.07% Counts May 1st New England D III College Mens Regionals 2022
138 Bowdoin Win 15-10 36.58 76 7.07% Counts May 1st New England D III College Mens Regionals 2022
146 Brandeis Loss 13-14 -9.29 153 7.07% Counts May 1st New England D III College Mens Regionals 2022
**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.