(3) #134 Nebraska (10-11)

702.45 (12)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
74 St. Olaf Loss 2-7 -7.28 19 3.8% Counts (Why) Mar 5th Midwest Throwdown 2022
158 Minnesota-Duluth Win 8-7 -1.1 10 4.65% Counts Mar 5th Midwest Throwdown 2022
164 Wisconsin-Oshkosh Win 8-4 16.2 13 4.16% Counts (Why) Mar 5th Midwest Throwdown 2022
145 Illinois Loss 5-8 -22.84 1 4.33% Counts Mar 6th Midwest Throwdown 2022
213 Washington University-B Win 7-4 -3.88 12 3.98% Counts (Why) Mar 6th Midwest Throwdown 2022
158 Minnesota-Duluth Win 8-7 -1.1 10 4.65% Counts Mar 6th Midwest Throwdown 2022
35 Minnesota Win 5-4 38.98 11 4.28% Counts Mar 26th Old Capital Open 2022
150 Truman State Loss 5-6 -10.74 20 4.74% Counts Mar 26th Old Capital Open 2022
66 Iowa Loss 3-10 -7.61 13 5.44% Counts (Why) Mar 27th Old Capital Open 2022
68 Kansas Win 7-6 31.19 38 5.15% Counts Mar 27th Old Capital Open 2022
34 Colorado State** Loss 1-13 0 12 0% Ignored (Why) Mar 27th Old Capital Open 2022
180 Minnesota-B Win 8-3 15.5 10 4.84% Counts (Why) Mar 27th Old Capital Open 2022
81 Iowa State Loss 10-13 3.45 7 6.99% Counts Apr 9th Western North Central D I College Womens CC 2022
2 Carleton College** Loss 3-13 0 28 0% Ignored (Why) Apr 9th Western North Central D I College Womens CC 2022
66 Iowa Loss 6-13 -9.94 13 6.99% Counts (Why) Apr 10th Western North Central D I College Womens CC 2022
180 Minnesota-B Win 11-10 -12.8 10 6.99% Counts Apr 10th Western North Central D I College Womens CC 2022
158 Minnesota-Duluth Win 9-7 9.03 10 6.41% Counts Apr 10th Western North Central D I College Womens CC 2022
66 Iowa Loss 3-12 -11.47 13 7.97% Counts (Why) Apr 30th North Central D I College Womens Regionals 2022
92 Marquette Loss 4-10 -21.68 20 7.26% Counts (Why) Apr 30th North Central D I College Womens Regionals 2022
164 Wisconsin-Oshkosh Win 8-7 -5.31 13 7.38% Counts Apr 30th North Central D I College Womens Regionals 2022
35 Minnesota** Loss 2-12 0 11 0% Ignored (Why) May 1st North Central D I College Womens 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.