(10) #119 Yale (16-4)

1110.48 (53)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
247 Dartmouth-B Win 10-9 -17.12 138 4.66% Counts Mar 19th Jersey Devil
311 Edinboro Win 15-8 -12.41 63 4.66% Counts (Why) Mar 19th Jersey Devil
220 Swarthmore Win 10-9 -13.46 85 4.66% Counts Mar 19th Jersey Devil
247 Dartmouth-B Loss 10-11 -29.35 138 4.66% Counts Mar 20th Jersey Devil
94 RIT Loss 9-10 -1.16 37 5.24% Counts Apr 2nd Northeast Classic
245 New Hampshire Win 10-6 1.69 40 4.8% Counts (Why) Apr 2nd Northeast Classic
216 Amherst Win 13-7 8.97 36 5.24% Counts (Why) Apr 2nd Northeast Classic
120 Connecticut Win 10-7 20.28 40 4.95% Counts Apr 2nd Northeast Classic
175 Massachusetts-C Win 12-6 19.31 28 5.1% Counts (Why) Apr 3rd Northeast Classic
127 Bowdoin Win 13-12 4.24 30 5.24% Counts Apr 3rd Northeast Classic
204 SUNY-Geneseo Win 12-3 12.95 38 5.02% Counts (Why) Apr 3rd Northeast Classic
372 Sacred Heart** Win 15-4 0 44 0% Ignored (Why) Apr 9th Hudson Valley D I College Mens CC 2022
241 SUNY-Albany Win 13-6 8.52 42 5.55% Counts (Why) Apr 9th Hudson Valley D I College Mens CC 2022
248 Central Connecticut State Win 12-6 5.93 47 5.4% Counts (Why) Apr 9th Hudson Valley D I College Mens CC 2022
241 SUNY-Albany Win 8-5 -0.06 42 4.59% Counts (Why) Apr 10th Hudson Valley D I College Mens CC 2022
248 Central Connecticut State Win 12-9 -9.18 47 6.6% Counts Apr 30th Metro East D I College Mens Regionals 2022
143 SUNY-Binghamton Win 8-7 0.59 47 5.86% Counts Apr 30th Metro East D I College Mens Regionals 2022
91 Princeton Loss 7-9 -10.57 46 6.05% Counts May 1st Metro East D I College Mens Regionals 2022
94 RIT Win 8-6 24.28 37 5.66% Counts May 1st Metro East D I College Mens Regionals 2022
101 Rutgers Loss 7-9 -13.33 42 6.05% Counts May 1st Metro East D I College Mens Regionals 2022
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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.