() #6 Colorado (18-5) SC 2

2197.57 (13)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
57 Stanford Win 14-8 -3.22 8 3.9% Counts (Why) Feb 18th President’s Day Invite
58 California-San Diego Win 15-7 -0.66 2 3.9% Counts (Why) Feb 18th President’s Day Invite
32 Oregon State Win 12-11 -10.84 5 3.9% Counts Feb 18th President’s Day Invite
17 Washington Win 13-11 0.87 38 3.9% Counts Feb 19th President’s Day Invite
61 Emory Win 13-7 -2.56 47 3.9% Counts (Why) Feb 19th President’s Day Invite
46 Western Washington Win 15-11 -5.2 26 3.9% Counts Feb 19th President’s Day Invite
10 California-Santa Cruz Win 11-10 0.7 1 3.9% Counts Feb 19th President’s Day Invite
17 Washington Win 12-10 1.25 38 3.9% Counts Feb 20th President’s Day Invite
9 Oregon Loss 13-14 -7.54 10 3.9% Counts Feb 20th President’s Day Invite
11 Brown Win 13-12 0.1 50 4.38% Counts Mar 4th Smoky Mountain Invite
30 Ohio State Win 13-10 -1.53 6 4.38% Counts Mar 4th Smoky Mountain Invite
5 Vermont Loss 10-13 -14.47 7 4.38% Counts Mar 4th Smoky Mountain Invite
19 Georgia Win 13-10 3.73 81 4.38% Counts Mar 4th Smoky Mountain Invite
8 Pittsburgh Win 13-11 8.55 17 4.38% Counts Mar 5th Smoky Mountain Invite
1 North Carolina Loss 13-15 -0.88 30 4.38% Counts Mar 5th Smoky Mountain Invite
5 Vermont Loss 12-13 -5.16 7 4.38% Counts Mar 5th Smoky Mountain Invite
2 Brigham Young Loss 11-13 -5.59 3 4.92% Counts Mar 18th Centex 2023
14 Carleton College Win 12-11 -1.17 20 4.92% Counts Mar 18th Centex 2023
54 Northwestern Win 13-6 0.96 16 4.92% Counts (Why) Mar 18th Centex 2023
23 Wisconsin Win 11-6 11.89 11 4.65% Counts (Why) Mar 18th Centex 2023
4 Texas Win 14-13 7.36 1 4.92% Counts Mar 19th Centex 2023
26 Georgia Tech Win 14-8 10.7 1 4.92% Counts (Why) Mar 19th Centex 2023
13 Tufts Win 15-11 13.03 37 4.92% Counts Mar 19th Centex 2023
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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.