(76) #208 Wisconsin-Whitewater (7-11)

1034.01 (598)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
176 Northern Iowa Loss 5-13 -27.38 360 5.58% Counts (Why) Mar 22nd Meltdown 2025
338 Rose-Hulman Win 12-4 6.15 490 5.36% Counts (Why) Mar 22nd Meltdown 2025
253 St Thomas Win 9-8 -2.56 557 5.28% Counts Mar 22nd Meltdown 2025
204 Winona State Loss 5-9 -26.02 332 4.79% Counts Mar 22nd Meltdown 2025
242 Grace Win 7-4 16.49 389 4.25% Counts (Why) Mar 23rd Meltdown 2025
176 Northern Iowa Loss 4-11 -25 360 5.12% Counts (Why) Mar 23rd Meltdown 2025
423 Northern Michigan** Win 15-5 0 0% Ignored (Why) Apr 12th Lake Superior D I Mens Conferences 2025
44 Wisconsin Loss 9-13 23.08 149 6.64% Counts Apr 12th Lake Superior D I Mens Conferences 2025
155 Wisconsin-La Crosse Loss 9-13 -14.2 235 6.64% Counts Apr 12th Lake Superior D I Mens Conferences 2025
143 Wisconsin-Milwaukee Loss 4-15 -24.56 142 6.64% Counts (Why) Apr 12th Lake Superior D I Mens Conferences 2025
155 Wisconsin-La Crosse Loss 12-15 -5.8 235 6.64% Counts Apr 13th Lake Superior D I Mens Conferences 2025
143 Wisconsin-Milwaukee Loss 9-14 -15.59 142 6.64% Counts Apr 13th Lake Superior D I Mens Conferences 2025
300 Wisconsin-Stevens Point Win 15-5 17.6 389 6.64% Counts (Why) Apr 13th Lake Superior D I Mens Conferences 2025
103 Marquette Loss 11-13 15.33 141 7.45% Counts Apr 26th North Central D I College Mens Regionals 2025
44 Wisconsin** Loss 3-15 0 149 0% Ignored (Why) Apr 26th North Central D I College Mens Regionals 2025
222 Wisconsin-B Win 15-8 41.92 279 7.45% Counts (Why) Apr 26th North Central D I College Mens Regionals 2025
135 Wisconsin-Eau Claire Loss 7-15 -25.17 337 7.45% Counts (Why) Apr 26th North Central D I College Mens Regionals 2025
195 Minnesota-B Win 14-8 47.16 163 7.45% Counts (Why) Apr 27th North Central D I 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.