(24) #133 Truman State (8-11)

981.98 (143)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
113 Saint Louis Win 7-6 18.33 141 6.26% Counts Feb 17th Dust Bowl 2024
124 Arkansas Loss 3-6 -25.12 324 5.21% Counts Feb 17th Dust Bowl 2024
77 Missouri Loss 5-15 -17.45 115 7.57% Counts (Why) Feb 17th Dust Bowl 2024
177 Missouri State Loss 5-6 -25.92 143 5.76% Counts Feb 17th Dust Bowl 2024
42 Texas-Dallas** Loss 0-11 0 114 0% Ignored (Why) Feb 17th Dust Bowl 2024
96 Iowa State Loss 7-10 -9.11 70 7.16% Counts Feb 18th Dust Bowl 2024
113 Saint Louis Loss 7-9 -11 141 7.8% Counts Mar 2nd Midwest Throwdown 2024
237 Northwestern-B** Win 13-0 0 48 0% Ignored (Why) Mar 2nd Midwest Throwdown 2024
34 Washington University** Loss 2-11 0 16 0% Ignored (Why) Mar 2nd Midwest Throwdown 2024
195 Washington University-B Win 6-5 -23.89 109 6.47% Counts Mar 2nd Midwest Throwdown 2024
35 St Olaf Win 5-4 57.25 143 5.85% Counts Mar 3rd Midwest Throwdown 2024
70 Northwestern Win 7-6 42.52 87 7.03% Counts Mar 3rd Midwest Throwdown 2024
34 Washington University** Loss 2-9 0 16 0% Ignored (Why) Mar 3rd Midwest Throwdown 2024
127 Wisconsin-Eau Claire Win 7-4 38.39 27 6.47% Counts (Why) Mar 3rd Midwest Throwdown 2024
48 Colorado College** Loss 3-10 0 95 0% Ignored (Why) Apr 13th South Central D III Womens Conferences 2024
223 Colorado College-B** Win 13-5 0 19 0% Ignored (Why) Apr 13th South Central D III Womens Conferences 2024
143 John Brown Win 9-8 8.01 87 11.37% Counts Apr 13th South Central D III Womens Conferences 2024
93 Rice Loss 3-11 -37.28 133 11.03% Counts (Why) Apr 13th South Central D III Womens Conferences 2024
66 Trinity Loss 3-13 -17.2 161 12.02% Counts (Why) Apr 14th South Central D III Womens Conferences 2024
**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.