(12) #178 Portland (13-8)

1208.77 (347)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
235 Claremont Loss 6-10 -27.68 292 3.75% Counts Feb 3rd Stanford Open 2024
361 Oregon State-B Win 12-7 -10.56 449 4.09% Counts (Why) Feb 3rd Stanford Open 2024
124 San Jose State Win 9-7 18.05 266 3.75% Counts Feb 3rd Stanford Open 2024
235 Claremont Win 11-7 11.16 292 4.22% Counts Feb 10th DIII Grand Prix
291 Pacific Lutheran Win 11-6 3.7 318 4.1% Counts (Why) Feb 10th DIII Grand Prix
81 Lewis & Clark Loss 12-13 11.49 248 4.33% Counts Feb 10th DIII Grand Prix
239 Reed Win 12-8 10.05 567 4.33% Counts Feb 10th DIII Grand Prix
52 Whitman Loss 7-12 1.24 320 4.33% Counts Feb 11th DIII Grand Prix
173 Xavier Loss 8-10 -10.48 260 4.22% Counts Feb 11th DIII Grand Prix
276 Whitworth Win 11-6 7.87 366 4.1% Counts (Why) Feb 11th DIII Grand Prix
335 Willamette Win 13-6 -2.08 473 5.15% Counts (Why) Mar 2nd PLU Mens BBQ
239 Reed Win 13-8 15.04 567 5.15% Counts Mar 2nd PLU Mens BBQ
169 Puget Sound Loss 5-13 -30.25 9 5.15% Counts (Why) Mar 2nd PLU Mens BBQ
276 Whitworth Win 10-6 6.63 366 4.73% Counts (Why) Mar 2nd PLU Mens BBQ
291 Pacific Lutheran Win 9-4 6.22 318 4.26% Counts (Why) Mar 3rd PLU Mens BBQ
160 Washington State Loss 8-11 -15.78 330 5.15% Counts Mar 3rd PLU Mens BBQ
365 Seattle** Win 9-2 0 377 0% Ignored (Why) Mar 3rd PLU Mens BBQ
291 Pacific Lutheran Win 15-7 10.99 318 7.29% Counts (Why) Apr 13th Northwest D III Mens Conferences 2024
276 Whitworth Win 15-7 18.66 366 7.29% Counts (Why) Apr 13th Northwest D III Mens Conferences 2024
52 Whitman Loss 6-15 -4.09 320 7.29% Counts (Why) Apr 13th Northwest D III Mens Conferences 2024
169 Puget Sound Loss 12-15 -20.21 9 7.29% Counts Apr 14th Northwest D III Mens Conferences 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.