(3) #158 Grinnell (10-7)

1233.99 (214)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
284 Harding Win 9-5 2.3 225 3.91% Counts (Why) Feb 22nd Dust Bowl 2025
275 Texas Tech Win 11-2 6.73 245 4.18% Counts (Why) Feb 22nd Dust Bowl 2025
159 Kansas Win 10-8 12.11 272 4.44% Counts Feb 22nd Dust Bowl 2025
176 Northern Iowa Win 9-8 2.79 360 4.31% Counts Feb 23rd Dust Bowl 2025
87 Missouri S&T Loss 4-9 -12.79 212 3.77% Counts (Why) Feb 23rd Dust Bowl 2025
130 North Texas Loss 8-9 -1.3 220 4.31% Counts Feb 23rd Dust Bowl 2025
274 St John's (Minnesota) Win 13-9 -1.72 236 6.08% Counts Mar 29th Old Capitol Open 2025
143 Wisconsin-Milwaukee Loss 8-13 -28.61 142 6.08% Counts Mar 29th Old Capitol Open 2025
174 Minnesota-Duluth Win 13-7 32.66 439 6.08% Counts (Why) Mar 29th Old Capitol Open 2025
118 Colorado Mines Loss 8-12 -19.6 183 6.08% Counts Mar 30th Old Capitol Open 2025
176 Northern Iowa Win 11-3 31.74 360 5.58% Counts (Why) Mar 30th Old Capitol Open 2025
301 Luther Win 12-10 -23.11 248 6.83% Counts Apr 12th West Plains D III Mens Conferences 2025
60 Carleton College-CHOP Loss 7-15 -14.29 124 7.67% Counts (Why) Apr 26th North Central D III College Mens Regionals 2025
150 Macalester Loss 10-11 -6.78 234 7.67% Counts Apr 26th North Central D III College Mens Regionals 2025
301 Luther Win 14-9 -6.6 248 7.67% Counts Apr 26th North Central D III College Mens Regionals 2025
60 Carleton College-CHOP Loss 6-13 -14.29 124 7.67% Counts (Why) Apr 27th North Central D III College Mens Regionals 2025
169 Michigan Tech Win 15-9 40.3 141 7.67% Counts Apr 27th North Central D III College Mens Regionals 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.