(1) #131 Georgia State (7-14)

1242.58 (14)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
88 Central Florida Loss 7-13 -18.53 18 4.82% Counts Jan 28th T Town Throwdown1
141 LSU Loss 7-8 -8.22 7 4.28% Counts Jan 28th T Town Throwdown1
61 Emory Loss 4-12 -12.88 47 4.63% Counts (Why) Jan 28th T Town Throwdown1
108 Vanderbilt Loss 11-12 -2.02 54 4.82% Counts Jan 28th T Town Throwdown1
251 Alabama-B Win 13-5 4.56 8 4.82% Counts (Why) Jan 29th T Town Throwdown1
259 Jacksonville State Win 13-5 2.72 7 4.82% Counts (Why) Jan 29th T Town Throwdown1
368 North Florida** Win 13-0 0 0% Ignored (Why) Jan 29th T Town Throwdown1
37 McGill Loss 7-13 -1.73 22 6.07% Counts Feb 25th Easterns Qualifier 2023
77 Temple Win 11-7 44.27 62 5.91% Counts Feb 25th Easterns Qualifier 2023
56 James Madison Loss 10-13 1.87 21 6.07% Counts Feb 25th Easterns Qualifier 2023
27 South Carolina** Loss 4-13 0 73 0% Ignored (Why) Feb 25th Easterns Qualifier 2023
69 Maryland Loss 10-12 3.83 29 6.07% Counts Feb 26th Easterns Qualifier 2023
37 McGill Loss 6-13 -4.48 22 6.07% Counts (Why) Feb 26th Easterns Qualifier 2023
26 Georgia Tech** Loss 5-15 0 1 0% Ignored (Why) Feb 26th Easterns Qualifier 2023
351 Central Michigan** Win 13-0 0 0% Ignored (Why) Apr 1st Huck Finn1
118 Marquette Loss 7-9 -17.78 16 7.44% Counts Apr 1st Huck Finn1
207 Illinois State Win 7-2 16.77 10 5.88% Counts (Why) Apr 1st Huck Finn1
94 Saint Louis Loss 4-8 -26.35 8 6.44% Counts Apr 1st Huck Finn1
104 Florida State Loss 7-8 -1.75 17 7.2% Counts Apr 2nd Huck Finn1
112 Illinois Win 9-5 45.07 10 6.96% Counts (Why) Apr 2nd Huck Finn1
108 Vanderbilt Loss 7-10 -25.3 54 7.67% Counts Apr 2nd Huck Finn1
**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.