(2) #93 Kentucky (9-11)

1218.93 (35)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
59 Missouri S&T Loss 10-11 4.37 25 4.71% Counts Apr 2nd Huck Finn 2022
70 Chicago Loss 8-11 -11.79 18 4.71% Counts Apr 2nd Huck Finn 2022
44 Cincinnati Loss 5-13 -14.73 6 4.71% Counts (Why) Apr 2nd Huck Finn 2022
178 Wisconsin-Whitewater Win 9-8 -9.8 12 4.46% Counts Apr 2nd Huck Finn 2022
82 Missouri Win 11-9 14.68 23 4.71% Counts Apr 3rd Huck Finn 2022
221 DePaul Win 15-4 4.41 56 4.71% Counts (Why) Apr 3rd Huck Finn 2022
100 Iowa State Win 11-9 10.81 38 4.71% Counts Apr 3rd Huck Finn 2022
29 Purdue Loss 8-11 1.72 29 4.99% Counts Apr 9th East Plains D I College Mens CC 2022
251 IUPUI Win 15-6 0.12 47 4.99% Counts (Why) Apr 9th East Plains D I College Mens CC 2022
- Ball State** Win 15-3 0 10 0% Ignored (Why) Apr 9th East Plains D I College Mens CC 2022
51 Indiana Loss 9-12 -4.84 9 4.99% Counts Apr 10th East Plains D I College Mens CC 2022
60 Notre Dame Loss 12-13 4.43 25 4.99% Counts Apr 10th East Plains D I College Mens CC 2022
12 Michigan Loss 9-15 9.17 21 5.93% Counts Apr 30th Great Lakes D I College Mens Regionals 2022
198 Western Michigan Win 15-5 10.56 72 5.93% Counts (Why) Apr 30th Great Lakes D I College Mens Regionals 2022
63 Northwestern Loss 9-15 -21.63 8 5.93% Counts Apr 30th Great Lakes D I College Mens Regionals 2022
106 Michigan State Loss 7-11 -32.84 23 5.78% Counts May 1st Great Lakes D I College Mens Regionals 2022
29 Purdue Loss 10-13 4.43 29 5.93% Counts May 1st Great Lakes D I College Mens Regionals 2022
198 Western Michigan Win 14-7 9.48 72 5.93% Counts (Why) May 1st Great Lakes D I College Mens Regionals 2022
122 Grand Valley State Win 14-3 30.48 59 5.93% Counts (Why) May 1st Great Lakes D I College Mens Regionals 2022
50 Illinois Loss 10-14 -8.96 14 5.93% Counts May 1st Great Lakes D I College Mens Regionals 2022
**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.