(5) #91 Princeton (13-5)

1225.79 (46)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
211 North Carolina-B Win 13-2 5.66 38 4.88% Counts (Why) Mar 26th Rodeo
36 St. Olaf Loss 10-13 0.14 10 4.88% Counts Mar 26th Rodeo
121 Tennessee-Chattanooga Win 10-6 17.79 17 4.48% Counts (Why) Mar 26th Rodeo
85 Richmond Loss 6-10 -22.24 27 4.48% Counts Mar 26th Rodeo
161 Kennesaw State Win 11-10 -9.15 23 4.88% Counts Mar 27th Rodeo
36 St. Olaf Loss 9-12 -0.74 10 4.88% Counts Mar 27th Rodeo
101 Rutgers Win 11-10 5.06 42 5.8% Counts Apr 16th Metro NY D I College Mens CC 2022
142 NYU Win 11-7 14.16 39 5.65% Counts Apr 16th Metro NY D I College Mens CC 2022
275 Hofstra Win 11-7 -15.94 40 5.65% Counts Apr 16th Metro NY D I College Mens CC 2022
187 Rowan Win 15-4 12.79 43 5.8% Counts (Why) Apr 16th Metro NY D I College Mens CC 2022
120 Connecticut Loss 8-15 -41.92 40 5.8% Counts Apr 17th Metro NY D I College Mens CC 2022
202 SUNY-Stony Brook Win 11-6 4.94 39 5.49% Counts (Why) Apr 17th Metro NY D I College Mens CC 2022
142 NYU Win 11-6 18.38 39 5.49% Counts (Why) Apr 17th Metro NY D I College Mens CC 2022
140 SUNY-Buffalo Win 11-10 -6.7 46 6.51% Counts Apr 30th Metro East D I College Mens Regionals 2022
120 Connecticut Win 15-14 0.64 40 6.51% Counts Apr 30th Metro East D I College Mens Regionals 2022
74 Columbia Loss 13-15 -9.23 43 6.51% Counts May 1st Metro East D I College Mens Regionals 2022
143 SUNY-Binghamton Win 11-7 15.98 47 6.34% Counts May 1st Metro East D I College Mens Regionals 2022
119 Yale Win 9-7 10.43 53 5.98% Counts May 1st Metro East D I 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.