(7) #209 SUNY-Stony Brook (8-11)

715.85 (48)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
119 Connecticut Loss 7-9 3.97 29 4.45% Counts Mar 5th No Sleep Till Brooklyn 2022
154 NYU Loss 8-13 -13.32 45 4.85% Counts Mar 5th No Sleep Till Brooklyn 2022
309 SUNY-Binghamton-B Win 10-7 -2.14 52 4.59% Counts Mar 5th No Sleep Till Brooklyn 2022
123 Williams Loss 8-11 -0.38 127 4.85% Counts Mar 5th No Sleep Till Brooklyn 2022
267 Colby Win 12-10 1.34 58 4.85% Counts Mar 6th No Sleep Till Brooklyn 2022
165 MIT Loss 9-10 2.92 44 4.85% Counts Mar 6th No Sleep Till Brooklyn 2022
175 SUNY Cortland Loss 7-9 -8.66 55 5.61% Counts Apr 2nd Strong Island
279 Hofstra Win 13-3 21.46 47 6.11% Counts (Why) Apr 2nd Strong Island
367 SUNY-Fredonia** Win 13-0 0 51 0% Ignored (Why) Apr 2nd Strong Island
342 SUNY-Stony Brook-B** Win 13-1 0 47 0% Ignored (Why) Apr 2nd Strong Island
175 SUNY Cortland Loss 6-13 -30.35 55 6.11% Counts (Why) Apr 3rd Strong Island
279 Hofstra Win 15-6 21.46 47 6.11% Counts (Why) Apr 3rd Strong Island
192 Rowan Win 11-8 32.23 45 6.86% Counts Apr 16th Metro NY D I College Mens CC 2022
105 Rutgers Loss 7-13 -9.66 41 6.86% Counts Apr 16th Metro NY D I College Mens CC 2022
76 Columbia Loss 5-13 -3.8 43 6.86% Counts (Why) Apr 16th Metro NY D I College Mens CC 2022
119 Connecticut Loss 7-13 -14.2 29 6.86% Counts Apr 16th Metro NY D I College Mens CC 2022
94 Princeton Loss 6-11 -5.09 37 6.49% Counts Apr 17th Metro NY D I College Mens CC 2022
105 Rutgers Loss 8-12 -1.1 41 6.86% Counts Apr 17th Metro NY D I College Mens CC 2022
279 Hofstra Win 12-9 5.53 47 6.86% Counts Apr 17th Metro NY D I College Mens CC 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.