(15) #95 Southern California (7-17)

929.15 (79)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
125 San Diego State Win 10-0 16.19 10 4.41% Counts (Why) Feb 4th Stanford Open
47 Santa Clara Win 7-6 24.61 38 4.18% Counts Feb 4th Stanford Open
102 Claremont Win 6-5 3.48 7 3.85% Counts Feb 4th Stanford Open
34 Portland Loss 4-6 6.41 77 3.67% Counts Feb 4th Stanford Open
155 Stanford-B Win 11-1 1.39 40 4.64% Counts (Why) Feb 5th Stanford Open
59 California-Santa Cruz Loss 3-9 -11.15 23 4.18% Counts (Why) Feb 5th Stanford Open
83 Nevada-Reno Win 7-6 8.69 4 4.18% Counts Feb 5th Stanford Open
59 California-Santa Cruz Loss 2-7 -9.73 23 3.67% Counts (Why) Feb 5th Stanford Open
12 California-Santa Barbara Loss 7-10 32.06 27 5.37% Counts Feb 18th President’s Day Invite
19 California-San Diego** Loss 4-11 0 18 0% Ignored (Why) Feb 18th President’s Day Invite
58 Texas Loss 3-9 -11.78 151 4.69% Counts (Why) Feb 18th President’s Day Invite
37 Duke Loss 4-10 -4.24 0 4.96% Counts (Why) Feb 18th President’s Day Invite
12 California-Santa Barbara** Loss 2-12 0 27 0% Ignored (Why) Feb 19th President’s Day Invite
23 California-Davis** Loss 3-9 0 26 0% Ignored (Why) Feb 19th President’s Day Invite
18 Colorado State** Loss 1-10 0 208 0% Ignored (Why) Feb 19th President’s Day Invite
61 Cal Poly-SLO Loss 6-8 -1.2 44 4.87% Counts Feb 19th President’s Day Invite
30 California Loss 7-10 10.15 91 5.37% Counts Feb 20th President’s Day Invite
98 Colorado College Loss 8-13 -39.39 58 7.15% Counts Mar 18th Womens Centex1
51 Florida Loss 3-13 -13.69 55 7.15% Counts (Why) Mar 18th Womens Centex1
80 Boston University Loss 1-13 -36.13 7.15% Counts (Why) Mar 18th Womens Centex1
16 Middlebury** Loss 5-13 0 0% Ignored (Why) Mar 19th Womens Centex1
87 Trinity Loss 7-14 -40.36 163 7.15% Counts Mar 19th Womens Centex1
114 Rice Win 12-8 23.79 134 7.15% Counts Mar 19th Womens Centex1
98 Colorado College Win 10-3 38.92 58 6.24% Counts (Why) Mar 19th Womens Centex1
**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.