(5) #361 Oregon State-B (3-18)

440.58 (449)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
338 Cal Poly-Humboldt Loss 8-15 -30.55 536 6.47% Counts Jan 27th Trouble in Corvegas
19 Oregon State** Loss 0-15 0 229 0% Ignored (Why) Jan 27th Trouble in Corvegas
160 Washington State** Loss 5-15 0 330 0% Ignored (Why) Jan 27th Trouble in Corvegas
355 Portland State Loss 11-15 -22.86 386 6.47% Counts Jan 27th Trouble in Corvegas
338 Cal Poly-Humboldt Loss 10-12 -7.96 536 6.47% Counts Jan 28th Trouble in Corvegas
66 Western Washington** Loss 1-15 0 251 0% Ignored (Why) Jan 28th Trouble in Corvegas
235 Claremont Loss 3-13 -3.34 292 6.85% Counts (Why) Feb 3rd Stanford Open 2024
178 Portland Loss 7-12 18.22 347 6.85% Counts Feb 3rd Stanford Open 2024
124 San Jose State** Loss 4-13 0 266 0% Ignored (Why) Feb 3rd Stanford Open 2024
291 Pacific Lutheran Loss 7-10 -7.26 318 8.17% Counts Mar 2nd PLU Mens BBQ
355 Portland State Win 10-8 28.74 386 8.4% Counts Mar 2nd PLU Mens BBQ
365 Seattle Loss 9-10 -12.66 377 8.63% Counts Mar 2nd PLU Mens BBQ
155 Washington-B** Loss 3-13 0 435 0% Ignored (Why) Mar 2nd PLU Mens BBQ
335 Willamette Win 11-10 24.09 473 8.63% Counts Mar 3rd PLU Mens BBQ
276 Whitworth Loss 2-13 -18.37 366 8.63% Counts (Why) Mar 3rd PLU Mens BBQ
7 Oregon** Loss 1-15 0 221 0% Ignored (Why) Apr 13th Cascadia D I Mens Conferences 2024
22 Washington** Loss 3-15 0 214 0% Ignored (Why) Apr 13th Cascadia D I Mens Conferences 2024
355 Portland State Loss 10-15 -56.05 386 12.21% Counts Apr 13th Cascadia D I Mens Conferences 2024
66 Western Washington** Loss 5-15 0 251 0% Ignored (Why) Apr 13th Cascadia D I Mens Conferences 2024
155 Washington-B** Loss 4-15 0 435 0% Ignored (Why) Apr 14th Cascadia D I Mens Conferences 2024
355 Portland State Win 15-7 90.49 386 12.21% Counts (Why) Apr 14th Cascadia D I Mens Conferences 2024
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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.