(3) #57 Whitman (18-4)

1506.56 (13)

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# Opponent Result Effect % of Ranking Status Date Event
208 Occidental Win 11-5 0.75 5.13% Feb 10th Stanford Open 2018
225 California-B Win 11-7 -10.71 5.44% Feb 10th Stanford Open 2018
79 California-Davis Loss 9-10 -12.85 5.59% Feb 10th Stanford Open 2018
343 Texas-B** Win 12-4 0 0% Ignored Feb 10th Stanford Open 2018
158 Lewis & Clark Win 13-5 11.58 5.59% Feb 11th Stanford Open 2018
100 Arizona Loss 8-12 -36.26 5.59% Feb 11th Stanford Open 2018
90 Northern Arizona Win 11-8 14.02 5.59% Feb 11th Stanford Open 2018
85 Colorado College Loss 8-11 -28 5.59% Feb 11th Stanford Open 2018
146 Nevada-Reno Win 11-3 15.77 6.1% Mar 3rd Big Sky Brawl 2018
191 Montana State Win 11-6 0.71 6.29% Mar 3rd Big Sky Brawl 2018
353 Montana-B** Win 11-3 0 0% Ignored Mar 3rd Big Sky Brawl 2018
222 Brigham Young-B** Win 11-4 0 0% Ignored Mar 3rd Big Sky Brawl 2018
206 Washington State Win 11-6 -2.44 6.29% Mar 3rd Big Sky Brawl 2018
247 Boise State** Win 13-4 0 0% Ignored Mar 4th Big Sky Brawl 2018
146 Nevada-Reno Win 13-8 9.89 6.65% Mar 4th Big Sky Brawl 2018
127 Montana Win 10-7 6.05 6.29% Mar 4th Big Sky Brawl 2018
304 Olivet Nazarene** Win 12-4 0 0% Ignored Mar 17th D III Midwestern Invite 2018
192 Cedarville Win 13-3 4.93 7.46% Mar 17th D III Midwestern Invite 2018
110 Michigan Tech Win 13-9 16.4 7.46% Mar 17th D III Midwestern Invite 2018
35 Air Force Loss 11-15 -20.01 7.46% Mar 18th D III Midwestern Invite 2018
110 Michigan Tech Win 15-5 31.03 7.46% Mar 18th D III Midwestern Invite 2018
232 St. Thomas** Win 15-6 0 0% Ignored Mar 18th D III Midwestern Invite 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.