(4) #139 Florida State (9-14)

1083.69 (59)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
38 Utah State Loss 4-13 -2.2 44 4.13% Counts (Why) Jan 31st Florida Warm Up 2025
19 Georgia** Loss 5-13 0 91 0% Ignored (Why) Jan 31st Florida Warm Up 2025
15 Washington University** Loss 2-13 0 70 0% Ignored (Why) Jan 31st Florida Warm Up 2025
4 Carleton College** Loss 1-13 0 64 0% Ignored (Why) Feb 1st Florida Warm Up 2025
56 Cornell Loss 9-13 0.93 82 4.13% Counts Feb 1st Florida Warm Up 2025
47 McGill Loss 1-13 -3.97 43 4.13% Counts (Why) Feb 1st Florida Warm Up 2025
61 Alabama-Huntsville Loss 8-12 -2.6 41 4.13% Counts Feb 2nd Florida Warm Up 2025
134 South Florida Loss 9-12 -13.63 68 4.13% Counts Feb 2nd Florida Warm Up 2025
209 Arkansas Win 12-6 12.93 93 4.78% Counts (Why) Feb 22nd Mardi Gras XXXVII
79 Florida Loss 7-10 -6.11 41 4.64% Counts Feb 22nd Mardi Gras XXXVII
160 LSU Win 10-9 1.72 36 4.91% Counts Feb 22nd Mardi Gras XXXVII
103 Texas A&M Win 12-11 14.56 133 4.91% Counts Feb 22nd Mardi Gras XXXVII
69 Auburn Loss 9-14 -8.01 76 5.84% Counts Mar 15th Tally Classic XIX
222 Harvard Win 15-11 0.46 46 5.84% Counts Mar 15th Tally Classic XIX
198 Georgia State Loss 9-10 -23.15 64 5.84% Counts Mar 15th Tally Classic XIX
160 LSU Win 11-10 2.07 36 5.84% Counts Mar 15th Tally Classic XIX
388 American-B** Win 14-5 0 246 0% Ignored (Why) Mar 22nd Atlantic Coast Open 2025
96 Appalachian State Loss 12-14 -1.99 68 6.18% Counts Mar 22nd Atlantic Coast Open 2025
163 Messiah Win 15-11 18.4 150 6.18% Counts Mar 22nd Atlantic Coast Open 2025
115 Vermont-B Loss 8-9 -0.87 35 5.85% Counts Mar 22nd Atlantic Coast Open 2025
184 East Carolina Loss 13-14 -21.03 0 6.18% Counts Mar 23rd Atlantic Coast Open 2025
255 Wake Forest Win 15-4 6.78 9 6.18% Counts (Why) Mar 23rd Atlantic Coast Open 2025
163 Messiah Win 13-8 25.98 150 6.18% Counts Mar 23rd Atlantic Coast Open 2025
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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.