(16) #102 Syracuse (12-12)

1260.39 (140)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
120 Connecticut Loss 10-11 -7.02 57 3.29% Counts Feb 8th NJ Warmup 2025
236 NYU Loss 9-11 -29.26 339 3.29% Counts Feb 8th NJ Warmup 2025
179 Pennsylvania Win 12-11 -7.6 1 3.29% Counts Feb 8th NJ Warmup 2025
192 Princeton Loss 10-12 -21.91 216 3.29% Counts Feb 8th NJ Warmup 2025
44 Emory Loss 8-12 -3.58 42 3.69% Counts Feb 22nd Easterns Qualifier 2025
88 Georgetown Loss 4-11 -19.35 78 3.39% Counts (Why) Feb 22nd Easterns Qualifier 2025
37 North Carolina-Wilmington Loss 8-9 9.04 84 3.49% Counts Feb 22nd Easterns Qualifier 2025
87 Temple Win 10-9 6.73 179 3.69% Counts Feb 22nd Easterns Qualifier 2025
96 Appalachian State Loss 12-13 -4.26 68 3.69% Counts Feb 23rd Easterns Qualifier 2025
183 Kennesaw State Win 14-6 8.83 74 3.69% Counts (Why) Feb 23rd Easterns Qualifier 2025
128 SUNY-Binghamton Win 13-12 -0.28 178 3.69% Counts Feb 23rd Easterns Qualifier 2025
153 Carleton University Win 13-1 18.8 172 4.65% Counts (Why) Mar 22nd Salt City Classic
24 Ottawa Loss 5-13 -1.3 147 4.65% Counts (Why) Mar 22nd Salt City Classic
151 Rhode Island Win 12-7 15.19 140 4.65% Counts (Why) Mar 22nd Salt City Classic
83 SUNY-Buffalo Loss 9-11 -9.21 278 4.65% Counts Mar 22nd Salt City Classic
151 Rhode Island Loss 8-9 -15.39 140 4.4% Counts Mar 23rd Salt City Classic
128 SUNY-Binghamton Win 13-8 17.76 178 4.65% Counts Mar 23rd Salt City Classic
120 Connecticut Win 12-8 18.66 57 4.93% Counts Mar 29th East Coast Invite 2025
132 Rutgers Win 15-5 23.65 135 4.93% Counts (Why) Mar 29th East Coast Invite 2025
177 Towson Win 14-9 7.21 47 4.93% Counts Mar 29th East Coast Invite 2025
116 West Chester Win 15-10 19.98 101 4.93% Counts Mar 29th East Coast Invite 2025
56 Cornell Loss 5-10 -14.22 82 4.38% Counts Mar 30th East Coast Invite 2025
83 SUNY-Buffalo Loss 6-12 -26.15 278 4.8% Counts Mar 30th East Coast Invite 2025
87 Temple Win 12-10 14.97 179 4.93% Counts Mar 30th East Coast Invite 2025
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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.