(1) #37 Washington University (13-7)

1768.65 (10)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
97 Appalachian State Win 15-3 3.25 1 5.92% Counts (Why) Feb 10th Queen City Tune Up 2024
3 Carleton College** Loss 0-15 0 17 0% Ignored (Why) Feb 10th Queen City Tune Up 2024
22 Notre Dame Loss 12-13 10.16 6 5.92% Counts Feb 10th Queen City Tune Up 2024
25 Pittsburgh Loss 8-10 -4.18 9 5.76% Counts Feb 10th Queen City Tune Up 2024
17 Pennsylvania Win 11-10 30.26 5 5.92% Counts Feb 11th Queen City Tune Up 2024
57 William & Mary Win 9-5 16.31 8 5.08% Counts (Why) Feb 11th Queen City Tune Up 2024
92 Saint Louis Win 8-5 -2.63 18 5.82% Counts (Why) Mar 2nd Midwest Throwdown 2024
216 Northwestern-B** Win 13-0 0 478 0% Ignored (Why) Mar 2nd Midwest Throwdown 2024
187 Washington University-B** Win 10-4 0 415 0% Ignored (Why) Mar 2nd Midwest Throwdown 2024
109 Truman State** Win 11-2 0 30 0% Ignored (Why) Mar 2nd Midwest Throwdown 2024
92 Saint Louis Win 9-4 6.42 18 5.82% Counts (Why) Mar 3rd Midwest Throwdown 2024
84 Iowa State Win 7-6 -19.77 76 5.82% Counts Mar 3rd Midwest Throwdown 2024
109 Truman State** Win 9-2 0 30 0% Ignored (Why) Mar 3rd Midwest Throwdown 2024
55 Southern California Win 13-9 17.67 12 7.9% Counts Mar 16th Womens Centex 2024
21 Ohio State Loss 8-13 -15.67 3 7.9% Counts Mar 16th Womens Centex 2024
36 Texas-Dallas Win 12-10 22.56 2 7.9% Counts Mar 16th Womens Centex 2024
27 Utah Loss 5-8 -21 10 6.53% Counts Mar 17th Womens Centex 2024
27 Utah Loss 10-11 2.43 10 7.9% Counts Mar 17th Womens Centex 2024
36 Texas-Dallas Win 11-10 12.85 2 7.9% Counts Mar 17th Womens Centex 2024
46 Texas Loss 6-15 -59.33 2 7.9% Counts (Why) Mar 17th Womens Centex 2024
**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.