(1) #111 SUNY-Binghamton (7-12)

1191.72 (14)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
70 Case Western Reserve Win 10-6 27.48 4 3.93% Counts (Why) Jan 27th Mid Atlantic Warm Up
96 Connecticut Win 11-9 13.74 26 4.29% Counts Jan 27th Mid Atlantic Warm Up
98 Dartmouth Loss 7-9 -9.23 16 3.93% Counts Jan 27th Mid Atlantic Warm Up
208 Virginia Commonwealth Win 12-8 1.56 52 4.29% Counts Jan 27th Mid Atlantic Warm Up
142 Boston University Loss 8-11 -21.88 17 4.29% Counts Jan 28th Mid Atlantic Warm Up
85 Carnegie Mellon Loss 9-13 -13.07 20 4.29% Counts Jan 28th Mid Atlantic Warm Up
158 Kennesaw State Win 12-6 22.1 9 5.26% Counts (Why) Feb 24th Easterns Qualifier 2024
29 South Carolina Loss 9-13 4.2 52 5.4% Counts Feb 24th Easterns Qualifier 2024
61 William & Mary Loss 6-13 -20.53 50 5.4% Counts (Why) Feb 24th Easterns Qualifier 2024
60 Temple Loss 11-12 6.75 34 5.4% Counts Feb 24th Easterns Qualifier 2024
158 Kennesaw State Loss 6-7 -14.31 9 4.47% Counts Feb 25th Easterns Qualifier 2024
34 Ohio State Loss 5-12 -8.19 140 5.18% Counts (Why) Feb 25th Easterns Qualifier 2024
169 Rutgers Win 8-5 9.98 29 4.47% Counts (Why) Feb 25th Easterns Qualifier 2024
58 Maryland Loss 12-15 -2.81 25 5.4% Counts Feb 25th Easterns Qualifier 2024
236 MIT Win 11-8 -10.62 17 6.8% Counts Mar 23rd Carousel City Classic 2024
32 Ottawa Loss 10-12 16.34 23 6.8% Counts Mar 23rd Carousel City Classic 2024
46 Williams Loss 8-13 -11.89 34 6.8% Counts Mar 23rd Carousel City Classic 2024
32 Ottawa Loss 8-12 1.52 23 6.8% Counts Mar 24th Carousel City Classic 2024
113 Syracuse Win 11-10 8.91 30 6.8% Counts Mar 24th Carousel City Classic 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.