(5) #33 UCLA (9-16)

2062.69 (427)

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# Opponent Result Effect % of Ranking Status Date Event
79 Chicago Win 13-8 3.02 3.36% Jan 27th Santa Barbara Invitational 2018
19 Vermont Loss 11-12 2.63 3.36% Jan 27th Santa Barbara Invitational 2018
63 Arizona Loss 9-12 -21.61 3.36% Jan 27th Santa Barbara Invitational 2018
38 Victoria Loss 9-10 -5.82 3.36% Jan 27th Santa Barbara Invitational 2018
63 Arizona Loss 9-12 -21.61 3.36% Jan 28th Santa Barbara Invitational 2018
79 Chicago Win 13-8 3.02 3.36% Jan 28th Santa Barbara Invitational 2018
37 Northwestern Win 11-8 13.77 3.99% Feb 17th Presidents Day Invitational Tournament 2018
2 California-San Diego** Loss 5-12 0 0% Ignored Feb 17th Presidents Day Invitational Tournament 2018
5 Oregon Loss 7-13 -0.4 3.99% Feb 17th Presidents Day Invitational Tournament 2018
36 Colorado College Win 13-11 8.29 3.99% Feb 18th Presidents Day Invitational Tournament 2018
9 Colorado Loss 4-11 -6.2 3.67% Feb 18th Presidents Day Invitational Tournament 2018
2 California-San Diego Loss 6-11 4.85 3.78% Feb 18th Presidents Day Invitational Tournament 2018
17 California-Santa Barbara Loss 4-11 -13.03 3.67% Feb 19th Presidents Day Invitational Tournament 2018
26 California Loss 9-10 -2.27 3.99% Feb 19th Presidents Day Invitational Tournament 2018
6 British Columbia Loss 3-13 -4.81 4.48% Mar 3rd Stanford Invite 2018
11 Texas Loss 7-11 -2.64 4.36% Mar 3rd Stanford Invite 2018
26 California Win 8-5 20.19 3.71% Mar 3rd Stanford Invite 2018
13 Ohio State Loss 8-9 9.62 4.24% Mar 4th Stanford Invite 2018
20 Washington Loss 10-13 -7.07 4.48% Mar 4th Stanford Invite 2018
37 Northwestern Loss 10-11 -8.98 5.33% Mar 24th Womens Centex 2018
123 MIT Win 13-8 -11.67 5.33% Mar 24th Womens Centex 2018
41 Georgia Tech Win 13-7 28.4 5.33% Mar 24th Womens Centex 2018
9 Colorado Loss 5-12 -8.79 5.12% Mar 24th Womens Centex 2018
42 Wisconsin Win 10-7 17.56 5.04% Mar 25th Womens Centex 2018
41 Georgia Tech Win 13-12 4.04 5.33% Mar 25th Womens Centex 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.