() #8 Colorado (13-6) SC 1

2095.44 (25)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
271 San Diego State** Win 13-2 0 38 0% Ignored (Why) Feb 16th Presidents Day Invite 2019
93 California-Davis Win 12-6 -7.16 27 4.91% Counts (Why) Feb 16th Presidents Day Invite 2019
16 Southern California Loss 6-8 -19.01 5 4.33% Counts Feb 17th Presidents Day Invite 2019
21 California Loss 6-7 -16.42 30 4.17% Counts Feb 17th Presidents Day Invite 2019
56 California-San Diego Win 11-4 4.73 17 4.63% Counts (Why) Feb 18th Presidents Day Invite 2019
34 UCLA Loss 8-9 -24.65 23 4.77% Counts Feb 18th Presidents Day Invite 2019
17 Minnesota Win 10-9 -1.16 88 5.66% Counts Mar 2nd Stanford Invite 2019
5 Cal Poly-SLO Loss 10-11 -4.56 29 5.66% Counts Mar 2nd Stanford Invite 2019
12 Texas Loss 7-10 -26.9 7 5.36% Counts Mar 2nd Stanford Invite 2019
2 Brown Loss 9-11 -6.93 63 5.66% Counts Mar 3rd Stanford Invite 2019
7 Carleton College-CUT Win 11-8 23.34 126 5.66% Counts Mar 3rd Stanford Invite 2019
13 Wisconsin Win 10-7 16.71 0 5.36% Counts Mar 3rd Stanford Invite 2019
3 Oregon Win 11-10 13.12 34 5.66% Counts Mar 3rd Stanford Invite 2019
27 LSU Win 13-8 12.12 1 6.36% Counts Mar 16th Centex 2019 Men
29 Texas-Dallas Win 13-9 6.45 7 6.36% Counts Mar 16th Centex 2019 Men
19 Colorado State Win 13-12 -4.81 23 6.36% Counts Mar 16th Centex 2019 Men
40 Dartmouth Win 14-10 -0.7 10 6.36% Counts Mar 17th Centex 2019 Men
12 Texas Win 15-7 34.93 7 6.36% Counts (Why) Mar 17th Centex 2019 Men
13 Wisconsin Win 14-13 2.07 0 6.36% Counts Mar 17th Centex 2019 Men
**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.