(3) #115 West Chester (4-16)

950.96 (263)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
64 Connecticut Loss 7-10 -1.09 249 4.84% Counts Feb 22nd 2025 Commonwealth Cup Weekend 2
25 Georgetown** Loss 6-14 0 207 0% Ignored (Why) Feb 22nd 2025 Commonwealth Cup Weekend 2
131 Harvard Win 9-6 14.33 243 4.55% Counts Feb 22nd 2025 Commonwealth Cup Weekend 2
57 James Madison Loss 9-10 17.73 277 5.12% Counts Feb 23rd 2025 Commonwealth Cup Weekend 2
79 Columbia Loss 7-9 -0.76 289 6.27% Counts Mar 29th East Coast Invite 2025
64 Connecticut Loss 4-8 -11.28 249 5.43% Counts Mar 29th East Coast Invite 2025
60 South Carolina Loss 5-12 -11.71 251 6.55% Counts (Why) Mar 29th East Coast Invite 2025
55 St Olaf Loss 6-14 -8 182 6.83% Counts (Why) Mar 29th East Coast Invite 2025
26 Northeastern Loss 6-12 19.17 293 6.65% Counts Mar 30th East Coast Invite 2025
75 Penn State Loss 6-10 -12.6 239 6.27% Counts Mar 30th East Coast Invite 2025
71 Carnegie Mellon Loss 5-9 -14.21 197 6.58% Counts Apr 12th Pennsylvania D I Womens Conferences 2025
75 Penn State Loss 5-7 -1.33 239 6.09% Counts Apr 12th Pennsylvania D I Womens Conferences 2025
245 Pennsylvania-B** Win 12-0 0 288 0% Ignored (Why) Apr 12th Pennsylvania D I Womens Conferences 2025
245 Pennsylvania-B** Win 13-0 0 288 0% Ignored (Why) Apr 13th Pennsylvania D I Womens Conferences 2025
109 Temple Win 7-3 39.46 241 5.56% Counts (Why) Apr 13th Pennsylvania D I Womens Conferences 2025
81 Case Western Reserve Loss 6-9 -13.97 245 7.65% Counts Apr 26th Ohio Valley D I College Womens Regionals 2025
22 Ohio State** Loss 2-11 0 375 0% Ignored (Why) Apr 26th Ohio Valley D I College Womens Regionals 2025
75 Penn State Loss 2-9 -22.4 239 7.12% Counts (Why) Apr 26th Ohio Valley D I College Womens Regionals 2025
31 Pittsburgh Loss 6-8 35.07 323 7.39% Counts Apr 26th Ohio Valley D I College Womens Regionals 2025
109 Temple Loss 5-8 -29.39 241 7.12% Counts Apr 27th Ohio Valley D I College Womens Regionals 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.