(1) #53 Cal Poly-SLO (10-13)

1380.02 (142)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
6 Brigham Young** Loss 6-15 0 141 0% Ignored (Why) Jan 27th Santa Barbara Invitational 2023
12 California-Santa Barbara Loss 6-12 5.94 141 5.66% Counts Jan 28th Santa Barbara Invitational 2023
29 UCLA Win 10-9 25.28 141 5.81% Counts Jan 28th Santa Barbara Invitational 2023
74 Utah Loss 2-14 -46.63 141 5.81% Counts (Why) Jan 28th Santa Barbara Invitational 2023
78 Lewis & Clark Loss 7-8 -17.78 142 5.16% Counts Jan 29th Santa Barbara Invitational 2023
42 Wisconsin Loss 6-9 -15.91 142 5.16% Counts Jan 29th Santa Barbara Invitational 2023
70 Northwestern Win 7-6 -0.82 145 4.81% Counts Jan 29th Santa Barbara Invitational 2023
24 Carleton College-Eclipse Loss 4-6 -0.6 141 4.47% Counts Feb 4th Stanford Open
178 Chico State** Win 12-1 0 146 0% Ignored (Why) Feb 4th Stanford Open
79 Nevada-Reno Win 7-4 14.35 142 4.69% Counts (Why) Feb 4th Stanford Open
24 Carleton College-Eclipse Loss 5-10 -12.8 141 5.47% Counts Feb 5th Stanford Open
- Humboldt State** Win 13-2 0 144 0% Ignored (Why) Feb 5th Stanford Open
108 California-San Diego-B Win 8-2 8.56 141 4.79% Counts (Why) Feb 5th Stanford Open
34 Portland Win 10-8 32.84 142 5.99% Counts Feb 5th Stanford Open
3 Colorado** Loss 2-15 0 141 0% Ignored (Why) Feb 18th President’s Day Invite
25 California-Davis Loss 4-12 -18.48 141 6.63% Counts (Why) Feb 18th President’s Day Invite
31 California Win 9-7 37.75 142 6.34% Counts Feb 18th President’s Day Invite
74 Utah Win 8-5 18.07 141 5.72% Counts (Why) Feb 18th President’s Day Invite
87 Southern California Win 8-6 0.41 142 5.93% Counts Feb 19th President’s Day Invite
8 Stanford** Loss 3-10 0 141 0% Ignored (Why) Feb 19th President’s Day Invite
28 Duke Loss 5-9 -14.32 139 5.93% Counts Feb 19th President’s Day Invite
74 Utah Loss 5-6 -15.58 141 5.26% Counts Feb 19th President’s Day Invite
31 California Loss 7-9 -0.09 142 6.34% Counts Feb 20th President’s Day Invite
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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.