(25) #216 Cal Poly-Pomona (4-12)

1015.56 (160)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
84 Southern California Loss 5-13 -5.51 202 5.42% Counts (Why) Feb 1st Pres Day Quals men
127 Santa Clara Loss 7-13 -13.27 265 5.42% Counts Feb 1st Pres Day Quals men
299 California-Santa Barbara-B Win 12-10 -5.14 223 5.42% Counts Feb 1st Pres Day Quals men
376 San Diego State-B Win 12-8 -17.65 43 5.42% Counts Feb 2nd Pres Day Quals men
279 California-B Win 13-6 20.74 218 5.42% Counts (Why) Feb 2nd Pres Day Quals men
175 California-Santa Cruz-B Loss 4-12 -23.89 86 5.2% Counts (Why) Feb 2nd Pres Day Quals men
120 Arizona State Loss 6-7 11.95 241 5.03% Counts Feb 15th Vice Presidents Day Invite 2025
84 Southern California Loss 10-11 24.55 202 6.09% Counts Feb 15th Vice Presidents Day Invite 2025
109 San Diego State Loss 11-12 18.68 199 6.09% Counts Feb 15th Vice Presidents Day Invite 2025
136 California-Irvine Loss 2-13 -19.14 123 6.09% Counts (Why) Feb 16th Vice Presidents Day Invite 2025
237 Loyola Marymount Win 11-6 27.88 276 5.76% Counts (Why) Feb 16th Vice Presidents Day Invite 2025
237 Loyola Marymount Loss 9-11 -36.29 276 9.66% Counts Apr 12th SoCal D I Mens Conferences 2025
31 California-Santa Barbara Loss 6-13 26.34 201 9.66% Counts (Why) Apr 12th SoCal D I Mens Conferences 2025
84 Southern California Loss 2-13 -10.29 202 9.66% Counts (Why) Apr 12th SoCal D I Mens Conferences 2025
54 UCLA** Loss 4-13 0 169 0% Ignored (Why) Apr 12th SoCal D I Mens Conferences 2025
136 California-Irvine Loss 12-15 0.45 123 9.66% Counts Apr 13th SoCal D I Mens Conferences 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.