(37) #250 Illinois State (6-13)

612.58 (59)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
110 Berry Loss 7-13 1.99 26 5.05% Counts Jan 25th T Town Throwdown XX
268 Harding Win 13-6 27.82 68 5.05% Counts (Why) Jan 25th T Town Throwdown XX
373 Tennessee-Chattanooga -B** Win 13-1 0 45 0% Ignored (Why) Jan 25th T Town Throwdown XX
160 LSU Loss 5-13 -11.72 36 5.05% Counts (Why) Jan 25th T Town Throwdown XX
104 Alabama** Loss 4-13 0 10 0% Ignored (Why) Jan 26th T Town Throwdown XX
172 Alabama-Birmingham Loss 5-11 -12.74 16 4.63% Counts (Why) Jan 26th T Town Throwdown XX
135 Mississippi State Loss 5-15 -5.39 23 5.05% Counts (Why) Jan 26th T Town Throwdown XX
72 Southern Illinois-Edwardsville Loss 5-9 15.65 146 5.78% Counts Mar 1st Midwest Throwdown 2025
385 Wisconsin-Eau Claire-B** Win 10-3 0 126 0% Ignored (Why) Mar 1st Midwest Throwdown 2025
107 Iowa** Loss 4-13 0 59 0% Ignored (Why) Mar 1st Midwest Throwdown 2025
86 Marquette** Loss 5-13 7.22 22 6.74% Counts (Why) Mar 2nd Midwest Throwdown 2025
265 St John's (Minnesota) Loss 10-12 -21.51 290 6.74% Counts Mar 2nd Midwest Throwdown 2025
309 Washington University-B Win 12-8 10.59 0 6.74% Counts Mar 2nd Midwest Throwdown 2025
256 Illinois-B Win 12-7 35.29 41 6.74% Counts (Why) Mar 2nd Midwest Throwdown 2025
117 Colorado Mines Loss 9-13 14.67 28 8.49% Counts Mar 29th Old Capitol Open 2025
178 Minnesota-B Loss 7-13 -23.13 5 8.49% Counts Mar 29th Old Capitol Open 2025
161 Wisconsin-Eau Claire Loss 7-13 -17.25 47 8.49% Counts Mar 29th Old Capitol Open 2025
203 Nebraska Loss 6-13 -39.53 189 8.49% Counts (Why) Mar 30th Old Capitol Open 2025
281 Wisconsin-Platteville Win 12-9 17.04 256 8.49% Counts Mar 30th Old Capitol Open 2025
**Blowout Eligible. Learn more about how this works here.

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.