(5) #201 American (10-10)

830.17 (148)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
110 Villanova Loss 5-13 -11.75 87 4.43% Counts (Why) Jan 25th Mid Atlantic Warmup 2020
195 George Mason Loss 11-12 -5.28 149 4.43% Counts Jan 25th Mid Atlantic Warmup 2020
177 Mary Washington Win 10-9 10.27 182 4.43% Counts Jan 25th Mid Atlantic Warmup 2020
78 Boston University Loss 9-13 3.56 141 4.43% Counts Jan 25th Mid Atlantic Warmup 2020
118 Navy Loss 9-14 -7.87 154 4.43% Counts Jan 26th Mid Atlantic Warmup 2020
244 Christopher Newport Win 13-10 7.65 161 4.43% Counts Jan 26th Mid Atlantic Warmup 2020
125 SUNY-Binghamton Loss 2-11 -12.98 162 4.07% Counts (Why) Jan 26th Mid Atlantic Warmup 2020
207 Drexel Win 9-8 6.08 150 5.19% Counts Feb 22nd Oak Creek Challenge 2020
263 NYU Win 10-9 -9.1 98 5.49% Counts Feb 22nd Oak Creek Challenge 2020
278 Salisbury Win 13-7 10.91 154 5.49% Counts (Why) Feb 22nd Oak Creek Challenge 2020
177 Mary Washington Win 13-10 24.64 182 5.49% Counts Feb 22nd Oak Creek Challenge 2020
66 Georgetown Loss 6-15 -2.17 95 5.49% Counts (Why) Feb 23rd Oak Creek Challenge 2020
127 Brandeis Win 11-9 31.4 171 5.49% Counts Feb 23rd Oak Creek Challenge 2020
103 Princeton Loss 6-14 -13.05 168 5.49% Counts (Why) Feb 23rd Oak Creek Challenge 2020
213 Catholic Win 7-4 20.97 149 4.4% Counts (Why) Feb 29th Lorton Hears a Huck
195 George Mason Loss 5-9 -27.07 149 4.97% Counts Feb 29th Lorton Hears a Huck
248 New Hampshire Loss 10-11 -19.02 149 5.79% Counts Feb 29th Lorton Hears a Huck
309 Maryland-Baltimore County Win 8-2 1.82 149 4.5% Counts (Why) Feb 29th Lorton Hears a Huck
123 Virginia Commonwealth University Loss 8-12 -8.78 151 5.79% Counts Mar 1st Lorton Hears a Huck
309 Maryland-Baltimore County Win 13-7 -0.23 149 5.79% Counts (Why) Mar 1st Lorton Hears a Huck
**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.