(1) #78 Charleston (13-5)

1280.81 (33)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
234 Radford** Win 13-3 0 128 0% Ignored (Why) Feb 26th Cutlass Classic 2022
161 Kennesaw State Win 11-9 -6.38 23 5.52% Counts Feb 26th Cutlass Classic 2022
307 Embry-Riddle** Win 13-2 0 24 0% Ignored (Why) Feb 26th Cutlass Classic 2022
193 George Washington Win 7-0 4.95 33 4% Counts (Why) Feb 26th Cutlass Classic 2022
116 Appalachian State Win 13-10 9.49 46 5.52% Counts Feb 27th Cutlass Classic 2022
302 North Florida** Win 13-1 0 17 0% Ignored (Why) Mar 19th College Southerns XX
192 Wisconsin-Eau Claire Win 12-6 6.92 30 6.39% Counts (Why) Mar 19th College Southerns XX
205 Georgia Tech-B Win 13-7 2.23 29 6.56% Counts (Why) Mar 19th College Southerns XX
32 Middlebury Loss 6-15 -20.38 28 6.56% Counts (Why) Mar 20th College Southerns XX
222 Luther Win 15-8 -0.68 69 6.56% Counts (Why) Mar 20th College Southerns XX
96 Carleton College-CHOP Win 14-11 16.85 136 6.56% Counts Mar 20th College Southerns XX
190 Wake Forest Win 12-7 5.35 35 8.76% Counts (Why) Apr 23rd Carolina D I College Mens CC 2022
2 North Carolina** Loss 4-13 0 26 0% Ignored (Why) Apr 23rd Carolina D I College Mens CC 2022
40 South Carolina Loss 3-13 -32.79 70 8.76% Counts (Why) Apr 23rd Carolina D I College Mens CC 2022
22 Duke Loss 6-13 -17.05 26 8.76% Counts (Why) Apr 23rd Carolina D I College Mens CC 2022
206 Clemson Win 12-8 -8.25 38 8.76% Counts Apr 24th Carolina D I College Mens CC 2022
190 Wake Forest Win 12-6 10.68 35 8.53% Counts (Why) Apr 24th Carolina D I College Mens CC 2022
22 Duke Loss 9-10 28.55 26 8.76% Counts Apr 24th Carolina D I College Mens CC 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.