() #20 Washington (9-12)

2240.23 (423)

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# Opponent Result Effect % of Ranking Status Date Event
26 California Win 11-8 12.06 4.46% Feb 17th Presidents Day Invitational Tournament 2018
43 Southern California Win 14-5 16.33 4.46% Feb 17th Presidents Day Invitational Tournament 2018
9 Colorado Loss 7-13 -13.9 4.46% Feb 17th Presidents Day Invitational Tournament 2018
11 Texas Loss 7-11 -10.67 4.34% Feb 18th Presidents Day Invitational Tournament 2018
4 Stanford Loss 6-11 -4.02 4.22% Feb 18th Presidents Day Invitational Tournament 2018
43 Southern California Loss 6-9 -27.56 3.96% Feb 18th Presidents Day Invitational Tournament 2018
37 Northwestern Win 9-7 2.87 4.09% Feb 19th Presidents Day Invitational Tournament 2018
36 Colorado College Win 11-8 7.4 4.46% Feb 19th Presidents Day Invitational Tournament 2018
2 California-San Diego Loss 7-13 -3.42 5% Mar 3rd Stanford Invite 2018
12 Carleton College Loss 9-11 -3.55 5% Mar 3rd Stanford Invite 2018
43 Southern California Win 11-7 11.1 4.87% Mar 3rd Stanford Invite 2018
33 UCLA Win 13-10 7.93 5% Mar 4th Stanford Invite 2018
5 Oregon Loss 9-13 -2.54 5% Mar 4th Stanford Invite 2018
9 Colorado Loss 11-12 7.08 5% Mar 4th Stanford Invite 2018
14 Whitman Win 11-8 32.35 5.95% Mar 23rd NW Challenge 2018
5 Oregon Loss 13-15 9.87 5.95% Mar 23rd NW Challenge 2018
18 Brigham Young Loss 7-15 -35.02 5.95% Mar 24th NW Challenge 2018
1 Dartmouth** Loss 6-15 0 0% Ignored Mar 24th NW Challenge 2018
21 Michigan Loss 6-15 -38.06 5.95% Mar 24th NW Challenge 2018
69 Boston College Win 15-3 6.96 5.95% Mar 25th NW Challenge 2018
35 Cal Poly-SLO Win 15-6 25.07 5.95% Mar 25th NW Challenge 2018
**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.