(1) #81 Lewis & Clark (17-3)

1587.48 (248)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
235 Claremont Win 12-7 -3.8 292 5.03% Counts (Why) Feb 10th DIII Grand Prix
178 Portland Win 13-12 -13.43 347 5.03% Counts Feb 10th DIII Grand Prix
52 Whitman Win 12-8 32.31 320 5.03% Counts Feb 10th DIII Grand Prix
173 Xavier Loss 8-10 -31.73 260 4.89% Counts Feb 10th DIII Grand Prix
291 Pacific Lutheran** Win 11-4 0 318 0% Ignored (Why) Feb 11th DIII Grand Prix
239 Reed Win 13-2 0.1 567 5.03% Counts (Why) Feb 11th DIII Grand Prix
276 Whitworth** Win 13-4 0 366 0% Ignored (Why) Feb 11th DIII Grand Prix
198 Messiah Win 13-5 9 297 5.98% Counts (Why) Mar 2nd FCS D III Tune Up 2024
153 Missouri S&T Win 13-11 -3.4 401 5.98% Counts Mar 2nd FCS D III Tune Up 2024
176 Navy Win 13-9 2.77 178 5.98% Counts Mar 2nd FCS D III Tune Up 2024
172 Union (Tennessee) Win 13-4 15.66 143 5.98% Counts (Why) Mar 2nd FCS D III Tune Up 2024
114 Davidson Win 12-10 5.59 291 5.98% Counts Mar 3rd FCS D III Tune Up 2024
129 Michigan Tech Win 13-10 7.8 208 5.98% Counts Mar 3rd FCS D III Tune Up 2024
65 Richmond Loss 12-13 -2.38 311 5.98% Counts Mar 3rd FCS D III Tune Up 2024
169 Puget Sound Win 11-7 11.8 9 8.23% Counts Apr 13th Northwest D III Mens Conferences 2024
239 Reed Win 11-6 -4.47 567 8% Counts (Why) Apr 13th Northwest D III Mens Conferences 2024
365 Seattle** Win 11-4 0 377 0% Ignored (Why) Apr 13th Northwest D III Mens Conferences 2024
335 Willamette** Win 11-2 0 473 0% Ignored (Why) Apr 13th Northwest D III Mens Conferences 2024
239 Reed Win 15-5 0.17 567 8.46% Counts (Why) Apr 14th Northwest D III Mens Conferences 2024
52 Whitman Loss 10-15 -26.27 320 8.46% Counts Apr 14th Northwest D III Mens Conferences 2024
**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.