(28) #248 Florida-B (12-6)

963.86 (463)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
388 Ave Maria-B** Win 13-3 0 788 0% Ignored (Why) Feb 24th Florida Warm Up 2024 Weekend 2
412 Central Florida-B** Win 13-3 0 726 0% Ignored (Why) Feb 24th Florida Warm Up 2024 Weekend 2
287 Florida Tech Win 12-6 26.73 398 6.22% Counts (Why) Feb 24th Florida Warm Up 2024 Weekend 2
186 Miami (Florida) Loss 5-10 -21.74 260 5.68% Counts Feb 24th Florida Warm Up 2024 Weekend 2
206 Embry-Riddle Loss 9-10 0.68 369 6.39% Counts Feb 25th Florida Warm Up 2024 Weekend 2
383 Florida State-B Win 13-6 -5.79 356 6.39% Counts (Why) Feb 25th Florida Warm Up 2024 Weekend 2
196 Charleston Win 9-8 22.81 357 7.19% Counts Mar 16th Southerns 2024
265 Georgia College Loss 7-12 -48.89 242 7.6% Counts Mar 16th Southerns 2024
246 Georgia Southern Win 11-9 21.02 320 7.6% Counts Mar 16th Southerns 2024
196 Charleston Loss 3-15 -35.37 357 7.6% Counts (Why) Mar 17th Southerns 2024
418 Wisconsin-Eau Claire-B** Win 15-5 0 352 0% Ignored (Why) Mar 17th Southerns 2024
246 Georgia Southern Loss 5-15 -48.79 320 7.6% Counts (Why) Mar 17th Southerns 2024
412 Central Florida-B** Win 15-1 0 726 0% Ignored (Why) Apr 13th Southeast Dev Mens Conferences 2024
406 South Florida-B** Win 15-6 0 430 0% Ignored (Why) Apr 13th Southeast Dev Mens Conferences 2024
224 Georgia-B Loss 8-12 -38.7 183 9.57% Counts Apr 13th Southeast Dev Mens Conferences 2024
303 Alabama-B Win 14-8 29.98 190 9.57% Counts (Why) Apr 14th Southeast Dev Mens Conferences 2024
261 Georgia Tech-B Win 10-7 32.86 276 9.05% Counts Apr 14th Southeast Dev Mens Conferences 2024
224 Georgia-B Win 13-7 66.99 183 9.57% Counts (Why) Apr 14th Southeast Dev Mens Conferences 2024
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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.