() #30 Georgia Tech (12-9)

1458.95 (52)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
100 Case Western Reserve Win 15-5 2.12 50 4.33% Counts (Why) Feb 26th Commonwealth Cup Weekend 2
58 Temple Loss 9-10 -17.9 52 4.33% Counts Feb 26th Commonwealth Cup Weekend 2
149 North Carolina-Wilmington Win 13-8 -16.93 57 4.33% Counts Feb 26th Commonwealth Cup Weekend 2
13 Pittsburgh Loss 6-15 -15.36 58 4.33% Counts (Why) Feb 26th Commonwealth Cup Weekend 2
29 Purdue Loss 10-13 -14.18 16 4.33% Counts Feb 27th Commonwealth Cup Weekend 2
24 Ohio Win 10-8 13.59 57 4.21% Counts Feb 27th Commonwealth Cup Weekend 2
61 Ohio State Win 11-5 13 48 3.97% Counts (Why) Feb 27th Commonwealth Cup Weekend 2
51 Chicago Loss 9-10 -18.53 34 5.14% Counts Mar 19th Womens Centex
7 Tufts Loss 4-15 -2.7 53 5.14% Counts (Why) Mar 19th Womens Centex
21 Northeastern Loss 8-9 -1.84 23 4.87% Counts Mar 19th Womens Centex
43 Dartmouth Win 13-3 25.42 50 5.14% Counts (Why) Mar 20th Womens Centex
61 Ohio State Win 8-5 7.48 48 4.26% Counts (Why) Mar 20th Womens Centex
237 Emory-B** Win 13-0 0 77 0% Ignored (Why) Apr 9th Southern Appalachian D I College Womens CC 2022
15 Georgia Loss 4-10 -19.85 58 5.34% Counts (Why) Apr 9th Southern Appalachian D I College Womens CC 2022
45 Tennessee Win 9-6 15.06 65 5.44% Counts Apr 9th Southern Appalachian D I College Womens CC 2022
15 Georgia Loss 8-11 -9.2 58 7.28% Counts Apr 30th Southeast D I College Womens Regionals 2022
198 Miami** Win 13-0 0 59 0% Ignored (Why) Apr 30th Southeast D I College Womens Regionals 2022
81 Emory Win 11-4 11.26 65 6.68% Counts (Why) Apr 30th Southeast D I College Womens Regionals 2022
53 Central Florida Win 10-3 25.16 57 6.36% Counts (Why) May 1st Southeast D I College Womens Regionals 2022
14 Florida State Loss 5-13 -27.51 49 7.28% Counts (Why) May 1st Southeast D I College Womens Regionals 2022
45 Tennessee Win 13-7 31.46 65 7.28% Counts (Why) May 1st Southeast D I College Womens Regionals 2022
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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.