() #162 Oklahoma (8-11)

480.27 (34)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
209 Illinois-B Win 7-2 10.23 16 4.23% Counts (Why) Mar 5th Midwest Throwdown 2022
141 Grinnell Win 4-3 10.43 9 3.54% Counts (Why) Mar 5th Midwest Throwdown 2022
142 Luther Loss 4-5 1.42 17 4.01% Counts Mar 5th Midwest Throwdown 2022
150 Truman State Loss 4-8 -23.19 44 4.63% Counts Mar 5th Midwest Throwdown 2022
145 Macalester Loss 5-7 -10 0 4.63% Counts Mar 6th Midwest Throwdown 2022
153 Minnesota-Duluth Win 8-5 25.9 17 4.82% Counts (Why) Mar 6th Midwest Throwdown 2022
200 Wisconsin-B Win 8-4 14.67 16 4.63% Counts (Why) Mar 6th Midwest Throwdown 2022
166 LSU Win 11-8 24.05 55 6.54% Counts Mar 19th Womens Centex
85 Texas-Dallas Loss 2-11 -4.97 47 6% Counts (Why) Mar 19th Womens Centex
77 Texas State Loss 3-11 -1.77 46 6% Counts (Why) Mar 19th Womens Centex
98 Rice Loss 3-11 -9.64 95 6% Counts (Why) Mar 19th Womens Centex
79 MIT Loss 1-11 -3.01 54 6% Counts (Why) Mar 20th Womens Centex
219 Texas-San Antonio Win 9-4 9.28 44 5.41% Counts (Why) Mar 20th Womens Centex
85 Texas-Dallas Loss 1-8 -4.18 47 5.09% Counts (Why) Mar 20th Womens Centex
62 Washington University** Loss 0-13 0 29 0% Ignored (Why) Apr 16th Ozarks D I College Womens CC 2022
114 Missouri Loss 2-13 -27.01 25 8.24% Counts (Why) Apr 16th Ozarks D I College Womens CC 2022
186 Missouri State Win 6-5 -2.06 23 6.27% Counts Apr 16th Ozarks D I College Womens CC 2022
121 Saint Louis Loss 0-11 -26.96 23 7.56% Counts (Why) Apr 17th Ozarks D I College Womens CC 2022
211 Washington University-B Win 8-0 15.33 9 6.41% Counts (Why) Apr 17th Ozarks D I College Womens CC 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.