(1) #2 Georgia (20-2) SE 1

2272.81 (80)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
17 Brigham Young Win 12-10 -6.14 39 3.71% Counts Feb 2nd Florida Warm Up 2024
82 Central Florida Win 13-7 -14.58 52 3.71% Counts (Why) Feb 2nd Florida Warm Up 2024
20 Northeastern Win 13-10 -4.41 65 3.71% Counts Feb 2nd Florida Warm Up 2024
10 Carleton College Loss 10-11 -14.94 87 3.71% Counts Feb 3rd Florida Warm Up 2024
74 Cincinnati** Win 13-5 0 6 0% Ignored (Why) Feb 3rd Florida Warm Up 2024
14 Texas Win 15-9 6.91 30 3.71% Counts Feb 3rd Florida Warm Up 2024
9 Brown Win 15-10 7.94 49 3.71% Counts Feb 4th Florida Warm Up 2024
4 Massachusetts Win 12-9 11.86 47 3.71% Counts Feb 4th Florida Warm Up 2024
13 North Carolina State Win 13-12 -9.88 42 4.68% Counts Mar 2nd Smoky Mountain Invite 2024
11 Minnesota Win 13-9 7.26 102 4.68% Counts Mar 2nd Smoky Mountain Invite 2024
21 Tufts Win 13-7 5.57 79 4.68% Counts (Why) Mar 2nd Smoky Mountain Invite 2024
23 UCLA Win 15-8 4.93 49 4.68% Counts (Why) Mar 2nd Smoky Mountain Invite 2024
8 Vermont Win 15-12 3.25 36 4.68% Counts Mar 3rd Smoky Mountain Invite 2024
7 Pittsburgh Win 15-14 -2.68 86 4.68% Counts Mar 3rd Smoky Mountain Invite 2024
4 Massachusetts Loss 12-15 -16.61 47 4.68% Counts Mar 3rd Smoky Mountain Invite 2024
33 Wisconsin Win 13-11 -24.96 14 5.89% Counts Mar 30th Easterns 2024
28 North Carolina-Wilmington Win 13-9 -7.5 109 5.89% Counts Mar 30th Easterns 2024
21 Tufts Win 13-7 7.1 79 5.89% Counts (Why) Mar 30th Easterns 2024
7 Pittsburgh Win 13-10 9.3 86 5.89% Counts Mar 30th Easterns 2024
5 Cal Poly-SLO Win 15-13 7.27 12 5.89% Counts Mar 31st Easterns 2024
8 Vermont Win 15-11 9.2 36 5.89% Counts Mar 31st Easterns 2024
4 Massachusetts Win 15-11 21.5 47 5.89% Counts Mar 31st Easterns 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.