(3) #90 Southern California (4-16)

1270.22 (35)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
4 Cal Poly-SLO** Loss 3-13 0 45 0% Ignored (Why) Jan 25th Santa Barbara Invite 2020
32 Dartmouth Loss 6-13 -10.81 7 5.47% Counts (Why) Jan 25th Santa Barbara Invite 2020
42 Utah Loss 9-13 -5.15 63 5.47% Counts Jan 25th Santa Barbara Invite 2020
52 Tulane Win 13-10 31.98 11 5.47% Counts Jan 25th Santa Barbara Invite 2020
53 Case Western Reserve Loss 9-11 -2.3 8 5.47% Counts Jan 26th Santa Barbara Invite 2020
64 Victoria Loss 9-13 -16.15 21 5.47% Counts Jan 26th Santa Barbara Invite 2020
39 California-San Diego Loss 5-11 -15.83 1 5.89% Counts (Why) Feb 15th Presidents Day Invite 2020
36 California-Santa Cruz Loss 6-14 -16.56 2 6.42% Counts (Why) Feb 15th Presidents Day Invite 2020
6 Oregon** Loss 5-15 0 10 0% Ignored (Why) Feb 15th Presidents Day Invite 2020
28 California-Santa Barbara Loss 4-12 -10.09 4 6.16% Counts (Why) Feb 16th Presidents Day Invite 2020
54 California-Davis Loss 5-11 -24.55 11 5.89% Counts (Why) Feb 16th Presidents Day Invite 2020
42 Utah Loss 4-12 -17.75 63 6.16% Counts (Why) Feb 16th Presidents Day Invite 2020
57 Illinois Win 12-9 36.22 10 6.42% Counts Feb 17th Presidents Day Invite 2020
160 San Diego State Win 15-2 21.95 15 6.42% Counts (Why) Feb 17th Presidents Day Invite 2020
15 California** Loss 4-13 0 15 0% Ignored (Why) Mar 7th Stanford Invite 2020
19 Oregon State Loss 6-13 -3.43 5 7.53% Counts (Why) Mar 7th Stanford Invite 2020
2 Washington** Loss 2-13 0 101 0% Ignored (Why) Mar 7th Stanford Invite 2020
36 California-Santa Cruz Loss 8-12 -6.72 2 7.53% Counts Mar 8th Stanford Invite 2020
59 Whitman Loss 9-12 -14.29 3 7.53% Counts Mar 8th Stanford Invite 2020
42 Utah Win 9-6 53.67 63 6.69% Counts Mar 8th Stanford Invite 2020
**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.