(1) #224 Minnesota-B (12-6)

695.71 (26)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
108 Vanderbilt Loss 7-9 10.84 22 6.15% Counts Mar 19th Missouri Loves Company MLC
63 Northwestern** Loss 5-13 0 8 0% Ignored (Why) Mar 19th Missouri Loves Company MLC
173 Truman State Loss 4-12 -27.38 40 6.43% Counts (Why) Mar 19th Missouri Loves Company MLC
147 Michigan-B Win 15-10 53.22 27 6.7% Counts Mar 20th Missouri Loves Company MLC
271 Oklahoma State University Win 15-8 27.07 22 6.7% Counts (Why) Mar 20th Missouri Loves Company MLC
347 Iowa State-B Win 9-8 -38.52 32 6.72% Counts Mar 26th Old Capital Open 2022
349 Southeast Missouri State Win 7-6 -34.66 33 5.88% Counts Mar 26th Old Capital Open 2022
262 Minnesota-Duluth Win 9-8 -2.24 30 6.72% Counts Mar 26th Old Capital Open 2022
267 Wisconsin-B Win 12-8 20.41 28 7.1% Counts Mar 27th Old Capital Open 2022
86 Iowa Loss 4-13 -3.74 34 7.1% Counts (Why) Mar 27th Old Capital Open 2022
148 Nebraska Loss 7-10 -7.43 40 6.72% Counts Mar 27th Old Capital Open 2022
262 Minnesota-Duluth Win 11-7 23.09 30 6.91% Counts Mar 27th Old Capital Open 2022
374 Wisconsin-Eau Claire-B** Win 13-0 0 27 0% Ignored (Why) Apr 23rd North Central Dev College Mens CC 2022
299 Minnesota-C Win 13-6 27.69 33 8.95% Counts (Why) Apr 23rd North Central Dev College Mens CC 2022
267 Wisconsin-B Loss 9-11 -41.62 28 8.95% Counts Apr 23rd North Central Dev College Mens CC 2022
310 Carleton College-Karls Win 13-10 -6.79 19 8.95% Counts Apr 23rd North Central Dev College Mens CC 2022
375 Wisconsin-Milwaukee-B** Win 13-2 0 27 0% Ignored (Why) Apr 24th North Central Dev College Mens CC 2022
347 Iowa State-B** Win 13-2 0 32 0% Ignored (Why) Apr 24th North Central Dev College Mens CC 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.