(14) #142 Saint Louis (7-11)

738.41 (372)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
132 Iowa Loss 5-7 -11.51 138 4.58% Counts Mar 1st Midwest Throwdown 2025
92 Iowa State Loss 4-11 -12.65 217 5.29% Counts (Why) Mar 1st Midwest Throwdown 2025
216 Washington University-B Win 13-1 7.7 230 5.77% Counts (Why) Mar 1st Midwest Throwdown 2025
147 Wisconsin-La Crosse Win 10-9 6.82 253 5.77% Counts Mar 1st Midwest Throwdown 2025
129 Winona State Loss 7-8 -0.95 253 5.12% Counts Mar 2nd Midwest Throwdown 2025
147 Wisconsin-La Crosse Win 7-6 5.58 253 4.77% Counts Mar 2nd Midwest Throwdown 2025
132 Iowa Win 10-4 46.65 138 6.35% Counts (Why) Mar 29th Old Capitol Open 2025
102 Macalester Loss 8-9 14.15 378 6.87% Counts Mar 29th Old Capitol Open 2025
215 Minnesota-Duluth Win 13-3 10.21 97 7.27% Counts (Why) Mar 29th Old Capitol Open 2025
74 Purdue Loss 1-11 -5.55 397 6.67% Counts (Why) Mar 29th Old Capitol Open 2025
102 Macalester Loss 5-7 -0.7 378 5.77% Counts Mar 30th Old Capitol Open 2025
110 Michigan State Loss 5-10 -21.14 402 6.46% Counts Mar 30th Old Capitol Open 2025
118 Northwestern Win 7-4 40.8 203 5.53% Counts (Why) Mar 30th Old Capitol Open 2025
111 Kansas Loss 6-13 -29.95 172 8.15% Counts (Why) Apr 12th Ozarks D I Womens Conferences 2025
97 Arkansas Loss 5-11 -19.84 145 7.48% Counts (Why) Apr 13th Ozarks D I Womens Conferences 2025
216 Washington University-B Win 10-9 -31 230 8.15% Counts Apr 13th Ozarks D I Womens Conferences 2025
4 Colorado** Loss 1-15 0 422 0% Ignored (Why) Apr 26th South Central D I College Womens Regionals 2025
28 Missouri** Loss 5-12 0 94 0% Ignored (Why) Apr 27th South Central D I College Womens Regionals 2025
**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.