(7) #26 Utah State (8-10)

1769.41 (88)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
5 Cal Poly-SLO Loss 10-11 15.9 12 5.37% Counts Feb 17th Presidents Day Invite 2024
134 California-Irvine Win 15-9 -8.21 43 5.37% Counts Feb 17th Presidents Day Invite 2024
22 Washington Loss 10-13 -15.8 44 5.37% Counts Feb 17th Presidents Day Invite 2024
35 California-Santa Cruz Win 13-12 -0.41 50 5.37% Counts Feb 18th Presidents Day Invite 2024
65 Stanford Win 11-8 0.06 80 5.37% Counts Feb 18th Presidents Day Invite 2024
23 UCLA Loss 6-11 -27.15 49 5.08% Counts Feb 18th Presidents Day Invite 2024
24 British Columbia Win 11-9 15.9 42 5.37% Counts Feb 19th Presidents Day Invite 2024
23 UCLA Loss 8-11 -18.52 49 5.37% Counts Feb 19th Presidents Day Invite 2024
9 Brown Loss 14-15 8.38 49 6.02% Counts Mar 2nd Smoky Mountain Invite 2024
10 Carleton College Loss 12-13 7.43 87 6.02% Counts Mar 2nd Smoky Mountain Invite 2024
1 North Carolina Loss 9-13 6.45 18 6.02% Counts Mar 2nd Smoky Mountain Invite 2024
8 Vermont Loss 9-13 -9.58 36 6.02% Counts Mar 2nd Smoky Mountain Invite 2024
11 Minnesota Loss 11-15 -9.51 102 6.02% Counts Mar 3rd Smoky Mountain Invite 2024
92 Tennessee Win 15-7 6.26 16 6.02% Counts (Why) Mar 3rd Smoky Mountain Invite 2024
23 UCLA Loss 13-15 -11.23 49 6.02% Counts Mar 3rd Smoky Mountain Invite 2024
30 Utah Win 13-5 41.69 31 7.59% Counts (Why) Mar 29th Utah Valley Rally
178 Brigham Young-B** Win 13-0 0 179 0% Ignored (Why) Mar 30th Utah Valley Rally
45 Utah Valley Win 13-11 -0.63 241 7.59% Counts Mar 30th Utah Valley Rally
**Blowout Eligible. Learn more about how this works here.

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.