() #17 South Carolina (15-4) AC 3

1773.87 (81)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
142 Carleton College-CHOP** Win 15-6 0 35 0% Ignored (Why) Jan 28th Carolina Kickoff
75 Richmond Win 15-5 7.6 36 5.22% Counts (Why) Jan 28th Carolina Kickoff
15 North Carolina State Loss 11-15 -19.25 69 5.22% Counts Jan 28th Carolina Kickoff
24 North Carolina-Charlotte Win 13-10 14.02 60 5.22% Counts Jan 28th Carolina Kickoff
40 Duke Win 15-12 3.15 72 5.22% Counts Jan 29th Carolina Kickoff
2 North Carolina Loss 6-15 -12.96 76 5.22% Counts (Why) Jan 29th Carolina Kickoff
24 North Carolina-Charlotte Win 13-12 2.84 60 5.22% Counts Jan 29th Carolina Kickoff
53 Appalachian State Win 15-9 10.87 76 5.85% Counts Feb 11th Queen City Tune Up1
122 Carnegie Mellon Win 15-8 -7.89 54 5.85% Counts (Why) Feb 11th Queen City Tune Up1
67 Maryland Win 14-10 -0.32 48 5.85% Counts Feb 11th Queen City Tune Up1
13 Tufts Loss 11-15 -18.46 70 5.85% Counts Feb 11th Queen City Tune Up1
25 North Carolina-Wilmington Loss 8-11 -27.7 69 5.85% Counts Feb 12th Queen City Tune Up1
34 McGill Win 13-11 5.46 248 6.57% Counts Feb 25th Easterns Qualifier 2023
99 Temple Win 13-7 -1.33 84 6.57% Counts (Why) Feb 25th Easterns Qualifier 2023
51 James Madison Win 13-9 5.76 76 6.57% Counts Feb 25th Easterns Qualifier 2023
117 Georgia State** Win 13-4 0 109 0% Ignored (Why) Feb 25th Easterns Qualifier 2023
48 Cornell Win 13-9 6.92 129 6.57% Counts Feb 26th Easterns Qualifier 2023
24 North Carolina-Charlotte Win 15-11 21.64 60 6.57% Counts Feb 26th Easterns Qualifier 2023
39 William & Mary Win 15-11 10.04 56 6.57% Counts Feb 26th Easterns Qualifier 2023
**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.