(2) #111 Georgetown (8-10)

854.73 (13)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
54 Liberty Loss 4-8 -6.13 46 3.86% Counts Feb 19th Commonwealth Cup Weekend 1
63 Virginia Tech Loss 5-8 -5.56 47 4.02% Counts Feb 19th Commonwealth Cup Weekend 1
53 James Madison Loss 6-13 -9.39 80 4.86% Counts (Why) Feb 20th Commonwealth Cup Weekend 1
114 Cedarville Win 10-5 24.84 40 4.32% Counts (Why) Feb 20th Commonwealth Cup Weekend 1
97 Mary Washington Win 4-2 17.25 38 2.73% Counts (Why) Feb 20th Commonwealth Cup Weekend 1
79 MIT Loss 5-9 -12.91 30 4.17% Counts Feb 20th Commonwealth Cup Weekend 1
96 Vermont-B Loss 4-7 -19.41 6 4.93% Counts Mar 26th Rodeo
186 Virginia-B Win 9-3 7.56 38 5.36% Counts (Why) Mar 26th Rodeo
186 Virginia-B Win 9-5 3.68 38 5.57% Counts (Why) Mar 27th Rodeo
193 Wake Forest Loss 6-7 -36.2 39 5.36% Counts Mar 27th Rodeo
156 American Win 8-3 18.64 42 5.66% Counts (Why) Apr 9th Colonial D I College Womens CC 2022
168 Maryland Win 8-7 -17.22 26 6.47% Counts Apr 9th Colonial D I College Womens CC 2022
157 Towson Win 10-1 20.95 87 6.36% Counts (Why) Apr 9th Colonial D I College Womens CC 2022
126 George Washington Win 13-4 51.36 4 9.17% Counts (Why) May 7th Atlantic Coast D I College Womens Regionals 2022
41 North Carolina State Loss 6-13 -8.49 21 9.17% Counts (Why) May 7th Atlantic Coast D I College Womens Regionals 2022
20 Virginia** Loss 5-12 0 69 0% Ignored (Why) May 7th Atlantic Coast D I College Womens Regionals 2022
44 William & Mary Loss 5-12 -9.99 123 8.8% Counts (Why) May 7th Atlantic Coast D I College Womens Regionals 2022
53 James Madison Loss 7-15 -18.57 80 9.17% Counts (Why) May 8th Atlantic Coast D I College Womens Regionals 2022
**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.