(3) #120 Arizona State (15-10)

1027.17 (19)

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# Opponent Result Effect % of Ranking Status Date Event
73 Northern Arizona Win 12-11 22.67 5.09% Jan 26th New Year Fest 2019
74 Denver Loss 6-10 -9.87 4.67% Jan 26th New Year Fest 2019
86 San Diego State Loss 7-9 -3.15 4.67% Jan 26th New Year Fest 2019
277 Arizona-B** Win 13-0 0 0% Ignored Jan 26th New Year Fest 2019
118 Arizona Win 10-6 24.92 4.67% Jan 27th New Year Fest 2019
230 New Mexico** Win 13-3 0 0% Ignored Jan 27th New Year Fest 2019
216 Montana Win 13-1 0.29 5.39% Feb 2nd Big Sky Brawl 2019
123 Boise State Win 7-5 14.34 4.29% Feb 2nd Big Sky Brawl 2019
90 Colorado State Loss 5-10 -19.32 4.79% Feb 2nd Big Sky Brawl 2019
138 Oregon State Win 9-6 16.38 4.79% Feb 3rd Big Sky Brawl 2019
30 Utah** Loss 3-10 0 0% Ignored Feb 3rd Big Sky Brawl 2019
123 Boise State Loss 6-7 -6.2 4.46% Feb 3rd Big Sky Brawl 2019
113 Oklahoma Loss 6-8 -15.07 5.2% Feb 16th Big D in lil d Women
195 Texas A&M Win 11-3 8.31 5.55% Feb 16th Big D in lil d Women
102 LSU Loss 7-8 -1.86 5.38% Feb 16th Big D in lil d Women
189 Tulane Win 10-7 -2.64 5.73% Feb 16th Big D in lil d Women
113 Oklahoma Win 8-5 25.25 5.01% Feb 17th Big D in lil d Women
168 Rice Win 7-6 -7.15 5.01% Feb 17th Big D in lil d Women
72 Texas-Dallas Loss 7-12 -14.26 6.05% Feb 17th Big D in lil d Women
234 Nevada-Reno** Win 14-5 0 0% Ignored Mar 23rd Trouble in Vegas 2019
243 Colorado-B** Win 13-3 0 0% Ignored Mar 23rd Trouble in Vegas 2019
187 California-San Diego-B Win 8-3 11.47 6.29% Mar 23rd Trouble in Vegas 2019
232 California-Irvine** Win 8-1 0 0% Ignored Mar 23rd Trouble in Vegas 2019
118 Arizona Loss 3-8 -39.4 6.29% Mar 24th Trouble in Vegas 2019
107 Chico State Loss 6-7 -5.43 6.68% Mar 24th Trouble in Vegas 2019
**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.