(55) #328 Nevada-Reno (4-13)

602 (95)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
180 Brigham Young-B Loss 0-13 -0.62 282 8.03% Counts (Why) Mar 9th Big Sky Brawl 2024
288 Montana Loss 5-8 -19.55 143 6.64% Counts Mar 9th Big Sky Brawl 2024
58 Utah Valley** Loss 4-13 0 205 0% Ignored (Why) Mar 9th Big Sky Brawl 2024
247 Northern Arizona Loss 3-8 -15.78 115 6.25% Counts (Why) Mar 9th Big Sky Brawl 2024
371 Boise State Win 8-4 21.79 260 6.38% Counts (Why) Mar 10th Big Sky Brawl 2024
288 Montana Loss 1-7 -26.05 143 5.83% Counts (Why) Mar 10th Big Sky Brawl 2024
58 Utah Valley** Loss 1-13 0 205 0% Ignored (Why) Mar 10th Big Sky Brawl 2024
235 Claremont Win 10-7 72.97 292 8.53% Counts Mar 24th Southwest Showdown 2024
192 Loyola Marymount Loss 6-13 -4.57 46 9.01% Counts (Why) Mar 24th Southwest Showdown 2024
339 Occidental Win 11-8 31.9 192 9.01% Counts Mar 24th Southwest Showdown 2024
416 San Diego State-B** Win 15-2 0 266 0% Ignored (Why) Mar 24th Southwest Showdown 2024
15 California** Loss 0-15 0 233 0% Ignored (Why) Apr 13th NorCal D I Mens Conferences 2024
230 California-Davis Loss 9-14 -7.26 167 10.72% Counts Apr 13th NorCal D I Mens Conferences 2024
67 Stanford** Loss 5-15 0 267 0% Ignored (Why) Apr 13th NorCal D I Mens Conferences 2024
338 Cal Poly-Humboldt Loss 4-7 -47.48 536 8.16% Counts Apr 14th NorCal D I Mens Conferences 2024
344 Chico State Loss 12-13 -22.43 222 10.72% Counts Apr 14th NorCal D I Mens Conferences 2024
144 Santa Clara Loss 7-14 18.17 343 10.72% Counts Apr 14th NorCal D I Mens Conferences 2024
**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.