(4) #125 Washington State (14-7)

1268.19 (10)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
253 Oregon State-B Win 15-4 2.16 39 4.19% Counts (Why) Jan 21st Pacific Confrontational Pac Con
137 Portland State Loss 11-15 -18.57 35 4.19% Counts Jan 21st Pacific Confrontational Pac Con
78 Santa Clara Loss 11-15 -7.61 30 4.19% Counts Jan 21st Pacific Confrontational Pac Con
74 Lewis & Clark Loss 8-15 -14.94 30 4.19% Counts Jan 22nd Pacific Confrontational Pac Con
241 Humboldt State Win 15-11 -5.67 21 4.19% Counts Jan 22nd Pacific Confrontational Pac Con
216 Boise State Win 11-10 -16.7 16 5.92% Counts Mar 4th Big Sky Brawl1
135 Brigham Young-B Win 13-4 35.29 12 5.92% Counts (Why) Mar 4th Big Sky Brawl1
237 Montana Win 15-5 6.13 15 5.92% Counts (Why) Mar 4th Big Sky Brawl1
216 Boise State Win 13-4 14.02 16 6.27% Counts (Why) Mar 11th Palouse Open 2023
323 Idaho** Win 13-4 0 16 0% Ignored (Why) Mar 11th Palouse Open 2023
237 Montana Win 13-6 6.52 15 6.27% Counts (Why) Mar 11th Palouse Open 2023
303 Whitworth** Win 13-2 0 27 0% Ignored (Why) Mar 11th Palouse Open 2023
216 Boise State Win 11-6 9.85 16 5.93% Counts (Why) Mar 12th Palouse Open 2023
237 Montana Win 9-7 -13.63 15 5.75% Counts Mar 12th Palouse Open 2023
303 Whitworth** Win 10-2 0 27 0% Ignored (Why) Mar 12th Palouse Open 2023
53 Utah Loss 8-12 -7.2 22 7.46% Counts Apr 1st Northwest Challenge Mens
17 Washington** Loss 5-15 0 38 0% Ignored (Why) Apr 1st Northwest Challenge Mens
46 Western Washington Loss 8-10 12.34 26 7.26% Counts Apr 1st Northwest Challenge Mens
232 Chico State Win 14-8 4.05 73 7.46% Counts (Why) Apr 2nd Northwest Challenge Mens
129 Gonzaga Win 11-9 19.15 113 7.46% Counts Apr 2nd Northwest Challenge Mens
81 Whitman Loss 8-13 -24.19 98 7.46% Counts Apr 2nd Northwest Challenge Mens
**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.