(9) #76 Utah (14-10)

1473.73 (28)

Click on column to sort  • 
# Opponent Result Effect % of Ranking Status Date Event
56 California-San Diego Loss 7-8 -0.21 3.46% Feb 16th Presidents Day Invite 2019
45 California-Santa Barbara Win 9-6 21.77 3.46% Feb 16th Presidents Day Invite 2019
5 Cal Poly-SLO** Loss 3-10 0 0% Ignored Feb 17th Presidents Day Invite 2019
100 California-Santa Cruz Win 8-7 0.36 3.46% Feb 17th Presidents Day Invite 2019
93 California-Davis Win 8-6 7.06 3.34% Feb 18th Presidents Day Invite 2019
37 Illinois Win 10-9 15.04 3.89% Feb 18th Presidents Day Invite 2019
200 Montana Win 12-8 -2.21 4.37% Mar 2nd Big Sky Brawl 2019
305 Boise State** Win 15-4 0 0% Ignored Mar 2nd Big Sky Brawl 2019
133 Utah State Win 10-9 -4.72 4.37% Mar 2nd Big Sky Brawl 2019
191 Montana State Win 11-10 -14.78 4.37% Mar 3rd Big Sky Brawl 2019
280 Idaho Win 15-7 -5.46 4.37% Mar 3rd Big Sky Brawl 2019
238 Denver Win 13-10 -11.31 4.37% Mar 3rd Big Sky Brawl 2019
46 Iowa State Win 13-9 31.13 4.9% Mar 16th Centex 2019 Men
19 Colorado State Loss 11-12 15.5 4.9% Mar 16th Centex 2019 Men
80 Oklahoma Win 12-7 25.71 4.9% Mar 16th Centex 2019 Men
82 Texas State Loss 10-11 -8.04 4.9% Mar 16th Centex 2019 Men
31 Texas A&M Loss 9-15 -12.41 4.9% Mar 17th Centex 2019 Men
29 Texas-Dallas Win 14-12 26.76 4.9% Mar 17th Centex 2019 Men
74 Arizona Loss 7-13 -30.24 5.19% Mar 23rd Trouble in Vegas 2019
125 Colorado School of Mines Loss 9-10 -17.55 5.19% Mar 23rd Trouble in Vegas 2019
34 UCLA Loss 10-13 -4.01 5.19% Mar 23rd Trouble in Vegas 2019
16 Southern California Loss 7-13 -3.02 5.19% Mar 24th Trouble in Vegas 2019
116 Nevada-Reno Loss 9-12 -28.78 5.19% Mar 24th Trouble in Vegas 2019
184 California-B Win 13-9 -1.24 5.19% 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.