(9) #71 Cornell (9-10)

1503.6 (79)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
50 Case Western Reserve Loss 11-13 -4.31 15 4.46% Counts Feb 25th Easterns Qualifier 2023
51 Virginia Loss 7-12 -18.13 1 4.46% Counts Feb 25th Easterns Qualifier 2023
26 Georgia Tech Win 12-9 33.13 1 4.46% Counts Feb 25th Easterns Qualifier 2023
150 George Washington Win 12-10 -5.47 2 4.46% Counts Feb 25th Easterns Qualifier 2023
27 South Carolina Loss 9-13 -3.45 73 4.46% Counts Feb 26th Easterns Qualifier 2023
33 Duke Win 15-11 31.18 34 4.46% Counts Feb 26th Easterns Qualifier 2023
25 North Carolina-Wilmington Loss 5-11 -9.36 24 4.09% Counts (Why) Feb 26th Easterns Qualifier 2023
134 Carnegie Mellon Win 13-6 19.8 18 5.62% Counts (Why) Mar 25th Carousel City Classic
50 Case Western Reserve Win 14-11 26.76 15 5.62% Counts Mar 25th Carousel City Classic
153 Columbia Win 15-7 14.1 14 5.62% Counts (Why) Mar 25th Carousel City Classic
82 Binghamton Win 11-10 4.94 42 5.62% Counts Mar 26th Carousel City Classic
31 Ottawa Loss 10-12 5.23 52 5.62% Counts Mar 26th Carousel City Classic
63 Rutgers Loss 10-13 -15.65 39 5.62% Counts Mar 26th Carousel City Classic
106 Liberty Loss 10-11 -18.08 80 5.95% Counts Apr 1st Atlantic Coast Open 2023
172 East Carolina Win 12-5 9.68 64 5.71% Counts (Why) Apr 1st Atlantic Coast Open 2023
45 Georgetown Loss 7-14 -24.66 15 5.95% Counts Apr 1st Atlantic Coast Open 2023
77 Temple Loss 7-15 -39.43 62 5.95% Counts (Why) Apr 2nd Atlantic Coast Open 2023
101 Navy Loss 9-10 -15.95 2 5.95% Counts Apr 2nd Atlantic Coast Open 2023
167 Virginia Commonwealth Win 13-7 9.11 62 5.95% Counts (Why) Apr 2nd Atlantic Coast Open 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.