(3) #153 Kentucky (12-11)

1265.58 (213)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
217 Akron Win 13-4 14.47 201 3.99% Counts (Why) Mar 15th Spring Spook
321 Cincinnati -B Win 8-6 -12.87 225 3.42% Counts Mar 15th Spring Spook
217 Akron Win 15-6 14.47 201 3.99% Counts (Why) Mar 16th Spring Spook
346 Wright State** Win 15-3 0 179 0% Ignored (Why) Mar 16th Spring Spook
145 Oberlin Loss 7-14 -23.41 19 3.99% Counts Mar 16th Spring Spook
39 Cincinnati Loss 8-15 -0.88 182 4.48% Counts Mar 29th Huck Finn 2025
93 Southern Illinois-Edwardsville Loss 7-12 -13.98 91 4.48% Counts Mar 29th Huck Finn 2025
87 Missouri S&T Loss 8-12 -9.33 212 4.48% Counts Mar 29th Huck Finn 2025
96 Missouri Win 10-9 15.79 212 4.48% Counts Mar 29th Huck Finn 2025
117 Mississippi State Loss 10-12 -6.02 264 4.48% Counts Mar 30th Huck Finn 2025
201 Saint Louis Win 10-9 -3.77 208 4.48% Counts Mar 30th Huck Finn 2025
150 Macalester Win 8-6 12.47 234 3.84% Counts Mar 30th Huck Finn 2025
292 Ball State Win 13-11 -16.2 366 5.02% Counts Apr 12th East Plains D I Mens Conferences 2025
56 Indiana Loss 6-13 -9.87 236 5.02% Counts (Why) Apr 12th East Plains D I Mens Conferences 2025
79 Notre Dame Loss 10-12 3.6 112 5.02% Counts Apr 12th East Plains D I Mens Conferences 2025
52 Purdue Loss 3-13 -8.01 158 5.02% Counts (Why) Apr 12th East Plains D I Mens Conferences 2025
26 Michigan** Loss 2-13 0 274 0% Ignored (Why) Apr 26th Great Lakes D I Mens Regionals 2025
61 Michigan State Loss 10-12 9.26 172 5.64% Counts Apr 26th Great Lakes D I Mens Regionals 2025
296 Loyola-Chicago Win 13-7 0.54 319 5.64% Counts (Why) Apr 26th Great Lakes D I Mens Regionals 2025
52 Purdue Loss 8-15 -6.95 158 5.64% Counts Apr 26th Great Lakes D I Mens Regionals 2025
148 Grand Valley Win 11-9 15.74 213 5.64% Counts Apr 27th Great Lakes D I Mens Regionals 2025
93 Southern Illinois-Edwardsville Win 15-14 20.74 91 5.64% Counts Apr 27th Great Lakes D I Mens Regionals 2025
227 Michigan-B Win 15-11 4.63 320 5.64% Counts Apr 27th Great Lakes D I Mens Regionals 2025
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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.