(6) #90 Carleton College-CHOP (13-7)

1200.18 (7)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
78 Missouri Win 9-5 23.85 14 3.94% Counts (Why) Mar 5th Midwest Throwdown 2022
54 Missouri S&T Loss 7-13 -15.91 6 4.59% Counts Mar 5th Midwest Throwdown 2022
142 Nebraska Win 10-4 15.83 3 4.01% Counts (Why) Mar 5th Midwest Throwdown 2022
169 Kansas Win 7-3 9.97 4 3.33% Counts (Why) Mar 6th Midwest Throwdown 2022
95 Iowa State Loss 9-10 -6.83 5 4.59% Counts Mar 6th Midwest Throwdown 2022
64 Northwestern Win 12-9 24.71 23 4.59% Counts Mar 6th Midwest Throwdown 2022
32 Washington University Loss 8-13 -5.1 20 4.59% Counts Mar 6th Midwest Throwdown 2022
374 Wisconsin-Eau Claire-B** Win 13-0 0 5 0% Ignored (Why) Mar 19th College Southerns XX
332 Florida-B** Win 13-1 0 11 0% Ignored (Why) Mar 19th College Southerns XX
117 Appalachian State Win 11-8 13.52 32 5.15% Counts Mar 19th College Southerns XX
189 Wisconsin-Eau Claire Win 15-5 10.75 5 5.15% Counts (Why) Mar 20th College Southerns XX
79 Charleston Loss 11-14 -14.16 28 5.15% Counts Mar 20th College Southerns XX
117 Appalachian State Win 12-8 17.62 32 5.15% Counts Mar 20th College Southerns XX
227 Macalester College Win 11-6 1.72 10 6.14% Counts (Why) Apr 16th Northwoods D III College Mens CC 2022
34 St. Olaf Loss 6-13 -18.37 21 6.49% Counts (Why) Apr 16th Northwoods D III College Mens CC 2022
155 Grinnell Win 11-7 14.57 33 6.31% Counts Apr 16th Northwoods D III College Mens CC 2022
213 Luther Win 13-5 8.86 0 7.71% Counts (Why) May 7th North Central D III College Mens Regionals 2022
249 St John's Win 13-7 -2.66 7 7.71% Counts (Why) May 7th North Central D III College Mens Regionals 2022
34 St. Olaf Loss 3-13 -22.14 21 7.71% Counts (Why) May 7th North Central D III College Mens Regionals 2022
160 Carthage Loss 9-13 -58.96 10 7.71% Counts May 7th North Central D III College Mens 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.