(5) #60 Temple (15-6)

1435.02 (34)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
107 Princeton Win 12-8 8.48 61 3.8% Counts Feb 5th New Jersey Warmup
167 Columbia Win 11-7 -0.4 38 3.92% Counts Feb 10th New Jersey Warmup
196 NYU Win 13-5 0.26 36 4.02% Counts (Why) Feb 10th New Jersey Warmup
126 Lehigh Win 13-7 11.23 13 4.02% Counts (Why) Feb 10th New Jersey Warmup
167 Columbia Win 14-9 -0.12 38 4.02% Counts Feb 11th New Jersey Warmup
113 Syracuse Win 14-10 6.39 30 4.02% Counts Feb 11th New Jersey Warmup
126 Lehigh Win 15-12 0.46 13 4.02% Counts Feb 11th New Jersey Warmup
158 Kennesaw State Win 10-8 -7.43 9 4.4% Counts Feb 24th Easterns Qualifier 2024
34 Ohio State Loss 9-11 -2 140 4.52% Counts Feb 24th Easterns Qualifier 2024
111 SUNY-Binghamton Win 12-11 -5.59 14 4.52% Counts Feb 24th Easterns Qualifier 2024
61 William & Mary Win 11-10 5.77 50 4.52% Counts Feb 24th Easterns Qualifier 2024
50 Alabama Loss 9-14 -19.26 3 4.52% Counts Feb 25th Easterns Qualifier 2024
56 Emory Win 13-8 24.06 31 4.52% Counts Feb 25th Easterns Qualifier 2024
106 Notre Dame Win 12-11 -4.72 25 4.52% Counts Feb 25th Easterns Qualifier 2024
29 South Carolina Loss 10-13 -3.75 52 4.52% Counts Feb 25th Easterns Qualifier 2024
85 Carnegie Mellon Loss 12-13 -15.5 20 6.03% Counts Mar 30th Atlantic Coast Open 2024
62 Massachusetts -B Loss 10-12 -15.48 149 6.03% Counts Mar 30th Atlantic Coast Open 2024
90 SUNY-Buffalo Win 15-8 25.97 72 6.03% Counts (Why) Mar 30th Atlantic Coast Open 2024
52 Virginia Tech Loss 12-13 -5.42 43 6.03% Counts Mar 30th Atlantic Coast Open 2024
165 RIT Win 15-10 -1.03 24 6.03% Counts Mar 31st Atlantic Coast Open 2024
90 SUNY-Buffalo Win 13-12 -2.25 72 6.03% Counts Mar 31st Atlantic Coast Open 2024
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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.