(4) #162 Washington State (15-9)

1109.49 (35)

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# Opponent Result Effect % of Ranking Status Date Event
3 Oregon** Loss 4-15 0 0% Ignored Jan 26th Flat Tail Open 2019 Mens
192 Gonzaga Loss 11-13 -11.55 3.53% Jan 26th Flat Tail Open 2019 Mens
326 Western Washington University-B Win 15-2 2.64 3.53% Jan 26th Flat Tail Open 2019 Mens
121 Puget Sound Loss 5-15 -15.67 3.53% Jan 27th Flat Tail Open 2019 Mens
116 Nevada-Reno Loss 11-15 -7.2 3.53% Jan 27th Flat Tail Open 2019 Mens
402 Oregon State-B** Win 13-4 0 0% Ignored Mar 2nd 19th Annual PLU BBQ Open
441 Pacific Lutheran-B** Win 13-0 0 0% Ignored Mar 2nd 19th Annual PLU BBQ Open
383 Washington-C** Win 13-3 0 0% Ignored Mar 2nd 19th Annual PLU BBQ Open
291 Pacific Lutheran Win 14-7 8.73 4.71% Mar 3rd 19th Annual PLU BBQ Open
192 Gonzaga Win 15-6 25.35 4.71% Mar 3rd 19th Annual PLU BBQ Open
168 Whitworth Loss 9-13 -21.78 4.71% Mar 3rd 19th Annual PLU BBQ Open
59 Oregon State Loss 7-15 -7.73 4.99% Mar 9th Palouse Open 2019
311 Central Washington Win 15-4 6.07 4.99% Mar 9th Palouse Open 2019
280 Idaho Win 15-6 12.85 4.99% Mar 9th Palouse Open 2019
168 Whitworth Loss 11-12 -7.73 4.99% Mar 10th Palouse Open 2019
326 Western Washington University-B Win 15-9 -0.64 4.99% Mar 10th Palouse Open 2019
104 Portland Loss 9-13 -11.91 5.93% Mar 30th 2019 NW Challenge Tier 2 3
200 Montana Win 11-7 20.94 5.77% Mar 30th 2019 NW Challenge Tier 2 3
289 Brigham Young-B Win 11-6 8.81 5.61% Mar 30th 2019 NW Challenge Tier 2 3
280 Idaho Win 11-7 6.84 5.77% Mar 30th 2019 NW Challenge Tier 2 3
241 Washington-B Win 12-10 1.08 5.93% Mar 30th 2019 NW Challenge Tier 2 3
200 Montana Win 13-10 12.8 5.93% Mar 31st 2019 NW Challenge Tier 2 3
280 Idaho Win 13-6 15.43 5.93% Mar 31st 2019 NW Challenge Tier 2 3
192 Gonzaga Loss 8-13 -36.77 5.93% Mar 31st 2019 NW Challenge Tier 2 3
**Blowout Eligible

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.