(18) #231 Air Force (4-14)

942.02 (195)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
43 Whitman Loss 6-13 11.05 235 4.37% Counts (Why) Feb 8th DIII Grand Prix 2025
315 Pacific Lutheran Win 13-8 7.93 133 4.37% Counts Feb 8th DIII Grand Prix 2025
291 Reed Win 13-7 15.86 91 4.37% Counts (Why) Feb 8th DIII Grand Prix 2025
199 Occidental Loss 9-13 -13.06 199 4.37% Counts Feb 9th DIII Grand Prix 2025
40 Lewis & Clark Loss 8-13 16.9 148 4.37% Counts Feb 9th DIII Grand Prix 2025
107 Claremont Loss 6-13 -4.45 169 4.37% Counts (Why) Feb 9th DIII Grand Prix 2025
60 Carleton College-CHOP** Loss 2-13 0 124 0% Ignored (Why) Mar 1st D III River City Showdown 2025
145 Oberlin Loss 9-13 -4.16 19 5.2% Counts Mar 1st D III River City Showdown 2025
282 Navy Win 11-10 -2.91 375 5.2% Counts Mar 1st D III River City Showdown 2025
139 Puget Sound Loss 4-13 -12.99 165 5.2% Counts (Why) Mar 1st D III River City Showdown 2025
241 Xavier Loss 9-11 -15.25 269 5.2% Counts Mar 2nd D III River City Showdown 2025
169 Michigan Tech Loss 9-13 -8.59 141 5.2% Counts Mar 2nd D III River City Showdown 2025
118 Colorado Mines Loss 9-15 -6.74 183 7.36% Counts Apr 12th Rocky Mountain D III Mens Conferences 2025
89 Colorado College Loss 5-15 -3.58 127 7.36% Counts (Why) Apr 12th Rocky Mountain D III Mens Conferences 2025
118 Colorado Mines Loss 5-13 -15.24 183 8.26% Counts (Why) Apr 26th South Central D III College Mens Regionals 2025
89 Colorado College Loss 6-14 -4.06 127 8.26% Counts (Why) Apr 26th South Central D III College Mens Regionals 2025
194 John Brown Loss 12-13 1.67 386 8.26% Counts Apr 27th South Central D III College Mens Regionals 2025
284 Harding Win 13-6 37.75 225 8.26% Counts (Why) Apr 27th South Central D III College Mens 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.