() #21 Georgia Tech (12-8)

1854.79 (27)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
45 Elon Win 13-9 6.78 22 3.86% Counts Feb 1st Carolina Kickoff mens 2025
88 Georgetown Win 12-7 -1.03 78 3.86% Counts (Why) Feb 1st Carolina Kickoff mens 2025
32 Virginia Loss 10-13 -20.21 9 3.86% Counts Feb 1st Carolina Kickoff mens 2025
3 North Carolina Win 15-14 19.14 5 3.86% Counts Feb 2nd Carolina Kickoff mens 2025
49 North Carolina State Win 15-13 -3.05 21 3.86% Counts Feb 2nd Carolina Kickoff mens 2025
27 South Carolina Win 15-11 12.29 50 3.86% Counts Feb 2nd Carolina Kickoff mens 2025
13 Texas Win 13-11 17.64 15 4.87% Counts Mar 1st Smoky Mountain Invite 2025
1 Massachusetts Loss 9-11 7.93 108 4.87% Counts Mar 1st Smoky Mountain Invite 2025
31 Minnesota Loss 12-13 -13.62 33 4.87% Counts Mar 1st Smoky Mountain Invite 2025
5 Oregon Loss 9-15 -9.04 4 4.87% Counts Mar 1st Smoky Mountain Invite 2025
19 Georgia Win 14-13 8.32 91 4.87% Counts Mar 2nd Smoky Mountain Invite 2025
25 Penn State Loss 10-14 -21.8 56 4.87% Counts Mar 2nd Smoky Mountain Invite 2025
31 Minnesota Win 15-13 3.73 33 4.87% Counts Mar 2nd Smoky Mountain Invite 2025
6 Cal Poly-SLO Loss 8-13 -14.59 18 6.13% Counts Mar 29th Easterns 2025
4 Carleton College Loss 9-13 -4.58 64 6.13% Counts Mar 29th Easterns 2025
28 Pittsburgh Win 13-11 9.07 11 6.13% Counts Mar 29th Easterns 2025
37 North Carolina-Wilmington Win 11-7 15.69 84 5.97% Counts Mar 29th Easterns 2025
19 Georgia Loss 11-15 -22.44 91 6.13% Counts Mar 30th Easterns 2025
31 Minnesota Win 15-11 15.67 33 6.13% Counts Mar 30th Easterns 2025
37 North Carolina-Wilmington Win 10-9 -6.19 84 6.13% Counts Mar 30th Easterns 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.