(2) #269 Harding (10-10)

649.53 (9)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
284 Memphis Win 13-3 25.94 12 4.86% Counts (Why) Jan 21st Tupelo Tuneup
89 Mississippi State** Loss 1-13 0 7 0% Ignored (Why) Jan 21st Tupelo Tuneup
266 Southern Mississippi Loss 6-10 -22.96 9 4.46% Counts Jan 21st Tupelo Tuneup
209 Alabama-Birmingham Win 9-8 18.08 9 4.59% Counts Jan 22nd Tupelo Tuneup
347 Mississippi College Win 7-1 1.35 17 3.52% Counts (Why) Jan 22nd Tupelo Tuneup
251 Alabama-B Loss 8-12 -18.27 8 4.86% Counts Jan 23rd Tupelo Tuneup
251 Alabama-B Win 8-6 21.27 8 5.25% Counts Feb 18th ‘Ole Muddy Classic
209 Alabama-Birmingham Loss 6-11 -18.19 9 5.79% Counts Feb 18th ‘Ole Muddy Classic
347 Mississippi College Win 11-7 -6.08 17 5.96% Counts Feb 18th ‘Ole Muddy Classic
304 Mississippi State-B Win 11-7 15.79 14 5.96% Counts Feb 18th ‘Ole Muddy Classic
251 Alabama-B Loss 9-13 -21.86 8 6.12% Counts Feb 19th ‘Ole Muddy Classic
347 Mississippi College Win 13-4 2.42 17 6.12% Counts (Why) Feb 19th ‘Ole Muddy Classic
304 Mississippi State-B Win 11-3 22.76 14 5.62% Counts (Why) Feb 19th ‘Ole Muddy Classic
278 Baylor Loss 8-13 -38.5 35 6.48% Counts Feb 25th Dust Bowl 2023
96 Arkansas** Loss 5-13 0 8 0% Ignored (Why) Feb 25th Dust Bowl 2023
193 North Texas Loss 6-9 -5.7 13 5.76% Counts Feb 25th Dust Bowl 2023
156 Wichita State Loss 6-13 -8.46 4 6.48% Counts (Why) Feb 25th Dust Bowl 2023
271 Texas A&M-B Win 12-7 34.92 17 6.48% Counts (Why) Feb 26th Dust Bowl 2023
252 Texas-B Loss 6-8 -12.97 15 5.56% Counts Feb 26th Dust Bowl 2023
264 Oklahoma State Win 9-8 10.24 16 6.13% Counts Feb 26th Dust Bowl 2023
**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.