(3) #37 American (13-8)

1896.84 (20)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
21 Ohio State Loss 8-13 -7.17 145 5.37% Counts Feb 22nd 2025 Commonwealth Cup Weekend 2
6 Vermont** Loss 4-15 0 33 0% Ignored (Why) Feb 22nd 2025 Commonwealth Cup Weekend 2
29 Georgia Tech Win 11-10 16.27 170 5.37% Counts Feb 22nd 2025 Commonwealth Cup Weekend 2
33 Cornell Win 10-8 18.43 14 5.22% Counts Feb 23rd 2025 Commonwealth Cup Weekend 2
23 Pennsylvania Loss 6-10 -7.62 99 4.93% Counts Feb 23rd 2025 Commonwealth Cup Weekend 2
19 Notre Dame Win 11-9 36.21 315 5.37% Counts Feb 23rd 2025 Commonwealth Cup Weekend 2
34 Ohio Win 12-10 17.01 23 5.37% Counts Feb 23rd 2025 Commonwealth Cup Weekend 2
227 Pennsylvania-B** Win 13-0 0 77 0% Ignored (Why) Mar 1st Cherry Blossom Classic 2025
113 George Washington Win 9-4 -4.19 86 4.7% Counts (Why) Mar 1st Cherry Blossom Classic 2025
91 Brown-B Loss 6-8 -42.83 73 4.88% Counts Mar 1st Cherry Blossom Classic 2025
56 Maryland Win 5-2 14.37 166 3.45% Counts (Why) Mar 1st Cherry Blossom Classic 2025
134 Catholic** Win 10-3 0 77 0% Ignored (Why) Mar 2nd Cherry Blossom Classic 2025
56 Maryland Win 9-3 19.83 166 4.7% Counts (Why) Mar 2nd Cherry Blossom Classic 2025
40 Haverford/Bryn Mawr Win 10-9 4.31 181 5.69% Counts Mar 2nd Cherry Blossom Classic 2025
30 Wisconsin Loss 6-12 -33.97 99 6.97% Counts Mar 29th East Coast Invite 2025
24 Minnesota Loss 7-9 -2.95 210 6.57% Counts Mar 29th East Coast Invite 2025
36 MIT Loss 7-12 -39.99 295 7.16% Counts Mar 29th East Coast Invite 2025
49 William & Mary Win 9-7 13.82 207 6.57% Counts Mar 29th East Coast Invite 2025
78 Mount Holyoke Win 11-8 -3.09 7.16% Counts Mar 30th East Coast Invite 2025
33 Cornell Loss 6-8 -15 14 6.15% Counts Mar 30th East Coast Invite 2025
66 St Olaf Win 5-2 14.86 81 4.35% Counts (Why) Mar 30th East Coast Invite 2025
**Blowout Eligible. Learn more about how this works here.

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.