(6) #172 Wisconsin-Whitewater (6-15)

876.37 (7)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
301 Houston Win 12-8 -4.58 17 3.71% Counts Feb 19th Mardi Gras XXXIV
102 Emory Loss 4-13 -12.59 25 3.71% Counts (Why) Feb 19th Mardi Gras XXXIV
114 Florida State Loss 5-9 -10.14 24 3.19% Counts Feb 19th Mardi Gras XXXIV
294 Tulane-B Win 13-11 -10.81 23 3.71% Counts Feb 19th Mardi Gras XXXIV
106 LSU Loss 2-13 -12.91 23 3.71% Counts (Why) Feb 20th Mardi Gras XXXIV
202 Spring Hill College Win 12-9 8.32 23 3.71% Counts Feb 20th Mardi Gras XXXIV
294 Tulane-B Loss 8-10 -28.95 23 3.62% Counts Feb 20th Mardi Gras XXXIV
70 Chicago Loss 5-7 5.36 19 4.17% Counts Apr 2nd Huck Finn 2022
46 Cincinnati Loss 7-13 2.69 39 5.25% Counts Apr 2nd Huck Finn 2022
91 Kentucky Loss 8-9 10.27 21 4.97% Counts Apr 2nd Huck Finn 2022
64 Northwestern Loss 2-15 -5.96 23 5.25% Counts (Why) Apr 2nd Huck Finn 2022
78 Missouri Loss 10-11 13.95 14 5.25% Counts Apr 3rd Huck Finn 2022
190 Illinois State Win 15-12 12.22 13 5.25% Counts Apr 3rd Huck Finn 2022
21 Wisconsin Loss 10-15 23.3 94 6.25% Counts Apr 23rd Lake Superior D I College Mens CC 2022
189 Wisconsin-Eau Claire Loss 12-13 -13.53 5 6.25% Counts Apr 23rd Lake Superior D I College Mens CC 2022
97 Marquette Loss 11-14 -1.29 5 6.25% Counts Apr 24th Lake Superior D I College Mens CC 2022
225 Wisconsin- La Crosse Win 15-6 27.03 3 6.25% Counts (Why) Apr 24th Lake Superior D I College Mens CC 2022
326 Wisconsin-Stevens Point Win 15-7 -6.47 5 6.25% Counts (Why) Apr 24th Lake Superior D I College Mens CC 2022
95 Iowa State Loss 9-11 4.08 5 6.62% Counts Apr 30th North Central D I College Mens Regionals 2022
21 Wisconsin** Loss 1-13 0 94 0% Ignored (Why) Apr 30th North Central D I College Mens Regionals 2022
133 Wisconsin-Milwaukee Loss 10-11 1.56 5 6.62% Counts Apr 30th North Central D I College Mens Regionals 2022
**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.