(12) #143 California-San Diego (6-15)

1160.92 (35)

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# Opponent Result Effect % of Ranking Status Date Event
146 Nevada-Reno Win 13-7 25.02 4.38% Jan 27th Santa Barbara Invitational 2018
18 Brigham Young** Loss 4-13 0 0% Ignored Jan 27th Santa Barbara Invitational 2018
79 California-Davis Loss 11-13 1.14 4.38% Jan 27th Santa Barbara Invitational 2018
24 Western Washington Loss 8-13 3.89 4.38% Jan 27th Santa Barbara Invitational 2018
38 Southern California Loss 8-13 -1.06 4.38% Jan 28th Santa Barbara Invitational 2018
32 California Loss 9-13 5.33 4.38% Jan 28th Santa Barbara Invitational 2018
79 California-Davis Loss 7-13 -13.92 4.38% Jan 28th Santa Barbara Invitational 2018
60 Cornell Loss 5-8 -6.36 4.31% Feb 17th Presidents Day Invitational Tournament 2018
55 Oregon State Loss 9-13 -3.37 5.21% Feb 17th Presidents Day Invitational Tournament 2018
148 San Diego State Loss 7-9 -14.72 4.78% Feb 17th Presidents Day Invitational Tournament 2018
5 Washington Loss 7-13 18.3 5.21% Feb 17th Presidents Day Invitational Tournament 2018
59 Santa Clara Loss 8-11 -1.47 5.21% Feb 18th Presidents Day Invitational Tournament 2018
76 Chicago Loss 10-11 7.11 5.21% Feb 18th Presidents Day Invitational Tournament 2018
211 Utah State Win 12-7 14.7 5.21% Feb 19th Presidents Day Invitational Tournament 2018
310 Grand Canyon** Win 12-3 0 0% Ignored Mar 24th Trouble in Vegas 2018
104 Pacific Lutheran Win 9-8 20.24 6.58% Mar 24th Trouble in Vegas 2018
90 Northern Arizona Loss 7-9 -4.27 6.38% Mar 24th Trouble in Vegas 2018
298 Cal State-Fullerton Win 12-6 0.69 6.77% Mar 24th Trouble in Vegas 2018
202 Utah Valley Win 10-9 -7.76 6.96% Mar 24th Trouble in Vegas 2018
53 UCLA Loss 6-11 -12.2 6.58% Mar 25th Trouble in Vegas 2018
159 Colorado-B Loss 4-7 -31.44 5.29% Mar 25th Trouble in Vegas 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.