(10) #67 Indiana (12-8)

1443.25 (51)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
127 Clemson Win 13-7 10.71 60 4.13% Counts (Why) Feb 8th Bulldog Brawl
72 Southern Illinois-Edwardsville Win 13-11 7.86 146 4.13% Counts Feb 8th Bulldog Brawl
185 Union (Tennessee) Win 12-9 -9.44 31 4.13% Counts Feb 8th Bulldog Brawl
183 Kennesaw State Win 15-10 -4.26 74 4.13% Counts Feb 9th Bulldog Brawl
133 Lipscomb Win 15-8 10.19 49 4.13% Counts (Why) Feb 9th Bulldog Brawl
72 Southern Illinois-Edwardsville Win 15-7 23.86 146 4.13% Counts (Why) Feb 9th Bulldog Brawl
96 Appalachian State Win 13-10 7.75 68 4.64% Counts Feb 22nd Easterns Qualifier 2025
66 Dartmouth Win 12-11 6.52 18 4.64% Counts Feb 22nd Easterns Qualifier 2025
52 William & Mary Win 10-8 17.54 101 4.52% Counts Feb 22nd Easterns Qualifier 2025
49 North Carolina State Win 11-9 18.04 21 4.64% Counts Feb 22nd Easterns Qualifier 2025
44 Emory Loss 10-14 -11.37 42 4.64% Counts Feb 23rd Easterns Qualifier 2025
64 James Madison Loss 12-13 -5.39 70 4.64% Counts Feb 23rd Easterns Qualifier 2025
47 McGill Loss 7-15 -21.98 43 4.64% Counts (Why) Feb 23rd Easterns Qualifier 2025
35 Chicago Loss 6-15 -25.68 97 6.19% Counts (Why) Mar 29th Huck Finn 2025
39 Cincinnati Loss 9-10 4.08 228 6.19% Counts Mar 29th Huck Finn 2025
11 Davenport Loss 7-14 -2.98 377 6.19% Counts Mar 29th Huck Finn 2025
42 Stanford Loss 11-14 -9.19 27 6.19% Counts Mar 29th Huck Finn 2025
44 Emory Loss 4-11 -26.22 42 5.68% Counts (Why) Mar 30th Huck Finn 2025
77 Iowa State Win 13-11 8.95 79 6.19% Counts Mar 30th Huck Finn 2025
84 Ohio State Win 11-10 0.09 51 6.19% Counts Mar 30th Huck Finn 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.