() #153 Kentucky (12-11)

1248.49 (17)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
215 Akron Win 13-4 14.51 16 3.99% Counts (Why) Mar 15th Spring Spook
323 Cincinnati -B Win 8-6 -12.66 11 3.42% Counts Mar 15th Spring Spook
215 Akron Win 15-6 14.51 16 3.99% Counts (Why) Mar 16th Spring Spook
348 Wright State** Win 15-3 0 15 0% Ignored (Why) Mar 16th Spring Spook
144 Oberlin Loss 7-14 -23.3 15 3.99% Counts Mar 16th Spring Spook
37 Cincinnati Loss 8-15 -0.8 15 4.48% Counts Mar 29th Huck Finn 2025
95 Southern Illinois-Edwardsville Loss 7-12 -13.96 17 4.48% Counts Mar 29th Huck Finn 2025
87 Missouri S&T Loss 8-12 -9.3 16 4.48% Counts Mar 29th Huck Finn 2025
97 Missouri Win 10-9 15.76 18 4.48% Counts Mar 29th Huck Finn 2025
118 Mississippi State Loss 10-12 -6.06 18 4.48% Counts Mar 30th Huck Finn 2025
204 Saint Louis Win 10-9 -3.8 18 4.48% Counts Mar 30th Huck Finn 2025
151 Macalester Win 8-6 12.52 16 3.84% Counts Mar 30th Huck Finn 2025
294 Ball State Win 13-11 -16.13 16 5.02% Counts Apr 12th East Plains D I Mens Conferences 2025
56 Indiana Loss 6-13 -10 20 5.02% Counts (Why) Apr 12th East Plains D I Mens Conferences 2025
78 Notre Dame Loss 10-12 3.59 17 5.02% Counts Apr 12th East Plains D I Mens Conferences 2025
53 Purdue Loss 3-13 -8.23 21 5.02% Counts (Why) Apr 12th East Plains D I Mens Conferences 2025
26 Michigan** Loss 2-13 0 24 0% Ignored (Why) Apr 26th Great Lakes D I Mens Regionals 2025
61 Michigan State Loss 10-12 8.93 23 5.64% Counts Apr 26th Great Lakes D I Mens Regionals 2025
297 Loyola-Chicago Win 13-7 0.61 16 5.64% Counts (Why) Apr 26th Great Lakes D I Mens Regionals 2025
53 Purdue Loss 8-15 -7.19 21 5.64% Counts Apr 26th Great Lakes D I Mens Regionals 2025
157 Grand Valley Win 11-9 13.94 47 5.64% Counts Apr 27th Great Lakes D I Mens Regionals 2025
95 Southern Illinois-Edwardsville Win 15-14 20.76 17 5.64% Counts Apr 27th Great Lakes D I Mens Regionals 2025
221 Michigan-B Win 15-11 6.7 17 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.