(8) #165 North Texas (6-17)

507.97 (35)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
128 Sam Houston State Loss 2-4 -6.7 30 2.59% Counts Feb 12th Antifreeze 2022
93 Rice Win 11-3 49.28 29 4.23% Counts (Why) Feb 12th Antifreeze 2022
124 Tulane Win 7-3 30.28 53 3.34% Counts (Why) Feb 12th Antifreeze 2022
141 Arizona State Loss 8-10 -4.15 120 4.49% Counts Feb 13th Antifreeze 2022
133 Trinity Loss 6-9 -9.25 32 4.09% Counts Feb 13th Antifreeze 2022
68 Kansas** Loss 4-13 0 38 0% Ignored (Why) Feb 19th Big D Lil D
89 Texas-Dallas Loss 5-10 -1.49 27 4.34% Counts Feb 19th Big D Lil D
77 Texas State Win 7-5 37.08 24 3.88% Counts Feb 19th Big D Lil D
88 Texas A&M Loss 3-8 -2.31 17 3.8% Counts (Why) Feb 20th Big D Lil D
133 Trinity Loss 7-9 -3.64 32 4.48% Counts Feb 20th Big D Lil D
89 Texas-Dallas Loss 2-7 -2.17 27 3.54% Counts (Why) Feb 20th Big D Lil D
66 Iowa** Loss 2-11 0 13 0% Ignored (Why) Mar 19th Womens Centex
219 Texas-San Antonio Loss 4-9 -54.74 35 5.09% Counts (Why) Mar 19th Womens Centex
133 Trinity Loss 3-11 -23.82 32 5.64% Counts (Why) Mar 19th Womens Centex
208 Texas-B Win 8-5 6.33 40 5.09% Counts (Why) Mar 19th Womens Centex
88 Texas A&M Loss 5-10 -1.88 17 5.47% Counts Mar 20th Womens Centex
163 LSU Loss 2-7 -27.78 55 4.46% Counts (Why) Mar 20th Womens Centex
18 Texas** Loss 3-13 0 4 0% Ignored (Why) Apr 16th Texas D I College Womens CC 2022
77 Texas State Loss 1-13 -0.8 24 7.75% Counts (Why) Apr 16th Texas D I College Womens CC 2022
208 Texas-B Win 9-4 18.11 40 6.41% Counts (Why) Apr 16th Texas D I College Womens CC 2022
88 Texas A&M Loss 6-12 -3.09 17 7.54% Counts Apr 16th Texas D I College Womens CC 2022
128 Sam Houston State Loss 5-9 -20.3 30 6.65% Counts Apr 17th Texas D I College Womens CC 2022
208 Texas-B Win 11-5 20.24 40 7.11% Counts (Why) Apr 17th Texas 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.