(26) #406 South Florida-B (3-14)

-50.84 (430)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
73 Ave Maria** Loss 0-13 0 255 0% Ignored (Why) Feb 24th Florida Warm Up 2024 Weekend 2
388 Ave Maria-B Win 7-3 60.55 788 6.46% Counts (Why) Feb 24th Florida Warm Up 2024 Weekend 2
309 Florida Gulf Coast** Loss 4-13 0 392 0% Ignored (Why) Feb 24th Florida Warm Up 2024 Weekend 2
372 North Florida Loss 3-12 -18.07 396 8.54% Counts (Why) Feb 24th Florida Warm Up 2024 Weekend 2
412 Central Florida-B Win 13-4 35.09 726 8.9% Counts (Why) Feb 25th Florida Warm Up 2024 Weekend 2
372 North Florida Loss 6-7 22.38 396 7.36% Counts Feb 25th Florida Warm Up 2024 Weekend 2
309 Florida Gulf Coast** Loss 0-13 0 392 0% Ignored (Why) Mar 16th Tally Classic XVIII
383 Florida State-B Loss 4-10 -27.53 356 9.25% Counts (Why) Mar 16th Tally Classic XVIII
383 Florida State-B Loss 4-13 -31.99 356 10.59% Counts (Why) Mar 17th Tally Classic XVIII
287 Florida Tech** Loss 2-11 0 398 0% Ignored (Why) Mar 17th Tally Classic XVIII
384 Notre Dame-B Loss 2-10 -29.61 244 9.25% Counts (Why) Mar 17th Tally Classic XVIII
412 Central Florida-B Loss 8-10 -75.11 726 12.98% Counts Apr 13th Southeast Dev Mens Conferences 2024
248 Florida-B** Loss 6-15 0 463 0% Ignored (Why) Apr 13th Southeast Dev Mens Conferences 2024
224 Georgia-B** Loss 3-15 0 183 0% Ignored (Why) Apr 13th Southeast Dev Mens Conferences 2024
303 Alabama-B Loss 8-15 30.34 190 13.34% Counts Apr 14th Southeast Dev Mens Conferences 2024
412 Central Florida-B Win 12-8 30.83 726 13.34% Counts Apr 14th Southeast Dev Mens Conferences 2024
261 Georgia Tech-B** Loss 1-15 0 276 0% Ignored (Why) Apr 14th Southeast Dev Mens 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.