(59) #130 Penn State-B (16-4)

1379.42 (13)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
359 Bentley Win 9-4 -15.3 172 4.49% Counts (Why) Mar 2nd Philly Special 2024
115 Bowdoin Win 9-8 9.88 221 5.13% Counts Mar 2nd Philly Special 2024
259 Brandeis Win 13-2 7.78 185 5.43% Counts (Why) Mar 3rd Philly Special 2024
187 College of New Jersey Win 11-9 1.91 19 5.43% Counts Mar 3rd Philly Special 2024
310 Stevens Tech** Win 13-3 0 181 0% Ignored (Why) Mar 3rd Philly Special 2024
240 SUNY-Albany Win 13-7 9.52 222 5.43% Counts (Why) Mar 3rd Philly Special 2024
139 Army Loss 9-11 -18.18 188 6.09% Counts Mar 16th Free Tournament
364 Rensselaer Polytech** Win 13-5 0 415 0% Ignored (Why) Mar 16th Free Tournament
126 Towson Win 13-7 36.79 272 6.09% Counts (Why) Mar 16th Free Tournament
171 Scranton Win 13-7 27 475 6.09% Counts (Why) Mar 16th Free Tournament
139 Army Win 15-6 36.9 188 6.09% Counts (Why) Mar 17th Free Tournament
367 Dartmouth-B** Win 15-5 0 133 0% Ignored (Why) Mar 17th Free Tournament
126 Towson Win 12-8 29.24 272 6.09% Counts Mar 17th Free Tournament
402 Case Western Reserve-B** Win 13-1 0 93 0% Ignored (Why) Apr 20th Ohio Valley Dev Mens Conferences 2024
127 Pittsburgh-B Loss 10-13 -28.22 327 8.13% Counts Apr 20th Ohio Valley Dev Mens Conferences 2024
407 West Chester-B** Win 13-1 0 200 0% Ignored (Why) Apr 20th Ohio Valley Dev Mens Conferences 2024
127 Pittsburgh-B Win 15-14 11.89 327 8.13% Counts Apr 21st Ohio Valley Dev Mens Conferences 2024
292 Kent State Win 14-11 -31.98 416 9.13% Counts May 4th Ohio Valley D I College Mens Regionals 2024
97 Lehigh Loss 9-15 -37.02 381 9.13% Counts May 4th Ohio Valley D I College Mens Regionals 2024
92 Pennsylvania Loss 3-15 -44.2 392 9.13% Counts (Why) May 4th Ohio Valley D I College Mens Regionals 2024
**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.