(32) #100 Missouri (12-9)

1265.35 (133)

#60#62#65#68#100
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Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
178 Minnesota-B Win 12-7 9.14 5 4.94% Counts (Why) Mar 1st Midwest Throwdown 2025
265 St John's (Minnesota)** Win 13-3 0 290 0% Ignored (Why) Mar 1st Midwest Throwdown 2025
337 Purdue-B** Win 13-1 0 273 0% Ignored (Why) Mar 1st Midwest Throwdown 2025
256 Illinois-B** Win 13-1 0 41 0% Ignored (Why) Mar 2nd Midwest Throwdown 2025
107 Iowa Win 12-6 27.09 59 4.81% Counts (Why) Mar 2nd Midwest Throwdown 2025
156 Wisconsin-La Crosse Win 12-8 10.08 5 4.94% Counts Mar 2nd Midwest Throwdown 2025
72 Southern Illinois-Edwardsville Win 11-8 25.82 146 4.94% Counts Mar 2nd Midwest Throwdown 2025
107 Iowa Win 11-10 4.81 59 5.54% Counts Mar 15th Mens Centex 2025
74 Oklahoma Christian Loss 10-12 -7.36 26 5.54% Counts Mar 15th Mens Centex 2025
103 Texas A&M Win 11-5 30.84 133 5.09% Counts (Why) Mar 15th Mens Centex 2025
29 Utah Valley Loss 2-13 -6.64 30 5.54% Counts (Why) Mar 15th Mens Centex 2025
46 Middlebury Loss 3-13 -15.71 7 5.54% Counts (Why) Mar 16th Mens Centex 2025
136 North Texas Win 15-10 17.53 38 5.54% Counts Mar 16th Mens Centex 2025
62 Tulane Loss 13-14 4.23 4 5.54% Counts Mar 16th Mens Centex 2025
150 Kentucky Loss 9-10 -22.44 91 6.22% Counts Mar 29th Huck Finn 2025
103 Texas A&M Loss 10-12 -17.44 133 6.22% Counts Mar 29th Huck Finn 2025
154 Macalester Loss 10-12 -30.56 6 6.22% Counts Mar 29th Huck Finn 2025
84 Ohio State Win 10-8 20.44 51 6.06% Counts Mar 29th Huck Finn 2025
90 Missouri S&T Loss 6-15 -37.83 72 6.22% Counts (Why) Mar 30th Huck Finn 2025
154 Macalester Loss 10-11 -23.06 6 6.22% Counts Mar 30th Huck Finn 2025
194 Saint Louis Win 8-2 9.5 10 4.84% Counts (Why) Mar 30th Huck Finn 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.