(3) #25 Georgia (8-10)

1775.26 (5)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
74 South Florida Win 13-4 4.68 16 5.02% Counts (Why) Jan 18th Florida Winter Classic 2020
31 Florida State Win 10-9 0.72 14 5.02% Counts Jan 18th Florida Winter Classic 2020
11 Dartmouth Loss 4-9 -14.72 7 4.15% Counts (Why) Jan 18th Florida Winter Classic 2020
7 Ohio State Loss 7-11 -6.96 3 4.89% Counts Jan 18th Florida Winter Classic 2020
15 Florida Loss 7-11 -13.56 7 4.89% Counts Jan 19th Florida Winter Classic 2020
74 South Florida Win 15-7 4.68 16 5.02% Counts (Why) Jan 19th Florida Winter Classic 2020
11 Dartmouth Loss 10-13 -3.58 7 5.02% Counts Jan 19th Florida Winter Classic 2020
3 Tufts Loss 8-9 21.74 286 5.57% Counts Feb 8th Queen City Tune Up 2020 Women
84 Notre Dame Win 8-5 -6.83 45 4.87% Counts (Why) Feb 8th Queen City Tune Up 2020 Women
38 Duke Loss 8-9 -20.22 14 5.57% Counts Feb 8th Queen City Tune Up 2020 Women
83 Clemson Win 11-4 1.54 19 5.41% Counts (Why) Feb 8th Queen City Tune Up 2020 Women
28 Michigan Win 8-7 4.44 25 5.23% Counts Feb 9th Queen City Tune Up 2020 Women
21 Vermont Loss 10-11 1.77 13 6.55% Counts Feb 22nd Commonwealth Cup 2020 Weekend 2
7 Ohio State Loss 6-13 -18.83 3 6.55% Counts (Why) Feb 22nd Commonwealth Cup 2020 Weekend 2
13 Pittsburgh Win 13-8 50.2 53 6.55% Counts Feb 22nd Commonwealth Cup 2020 Weekend 2
12 Virginia Loss 12-13 9.47 10 6.55% Counts Feb 23rd Commonwealth Cup 2020 Weekend 2
82 Oberlin Win 14-7 1.8 141 6.55% Counts (Why) Feb 23rd Commonwealth Cup 2020 Weekend 2
22 Northwestern Loss 10-12 -15.69 20 6.55% Counts Feb 23rd Commonwealth Cup 2020 Weekend 2
**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.