(7) #105 Chico State (7-13)

1479.34 (419)

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# Opponent Result Effect % of Ranking Status Date Event
87 California-Santa Cruz Win 10-8 20.06 5.13% Feb 10th Stanford Open 2018
118 Lewis & Clark Win 9-7 9.98 4.84% Feb 10th Stanford Open 2018
73 San Diego State Win 8-6 25.81 4.52% Feb 10th Stanford Open 2018
87 California-Santa Cruz Loss 5-10 -22.86 4.68% Feb 11th Stanford Open 2018
77 Brown Loss 8-9 4.44 4.98% Feb 11th Stanford Open 2018
67 Puget Sound Win 8-7 20.36 4.68% Feb 11th Stanford Open 2018
79 Chicago Loss 5-9 -17.87 4.79% Feb 17th Presidents Day Invitational Tournament 2018
4 Stanford** Loss 1-13 0 0% Ignored Feb 17th Presidents Day Invitational Tournament 2018
36 Colorado College Loss 3-13 -2.73 5.58% Feb 17th Presidents Day Invitational Tournament 2018
55 Iowa State Loss 7-13 -11.26 5.58% Feb 17th Presidents Day Invitational Tournament 2018
37 Northwestern Loss 3-14 -3.03 5.58% Feb 18th Presidents Day Invitational Tournament 2018
16 Western Washington** Loss 1-15 0 0% Ignored Feb 18th Presidents Day Invitational Tournament 2018
61 California-Davis Loss 8-9 11.91 5.28% Feb 19th Presidents Day Invitational Tournament 2018
98 Northern Arizona Loss 5-9 -33.11 6.4% Mar 24th Trouble in Vegas 2018
120 California-San Diego-B Win 8-5 23.19 6.16% Mar 24th Trouble in Vegas 2018
63 Arizona Loss 2-10 -20.41 6.51% Mar 24th Trouble in Vegas 2018
200 Nevada-Reno Win 6-4 -13.18 5.41% Mar 24th Trouble in Vegas 2018
73 San Diego State Loss 2-13 -28.63 7.45% Mar 25th Trouble in Vegas 2018
138 Santa Clara Win 8-3 23.4 5.8% Mar 25th Trouble in Vegas 2018
63 Arizona Loss 7-8 12.9 6.62% Mar 25th Trouble in Vegas 2018
**Blowout Eligible

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.