(35) #99 Oberlin (15-6)

1159.9 (115)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
110 Christopher Newport Win 13-12 2.87 25 3.5% Counts Mar 5th FCS D III Tune Up
50 Berry Loss 7-13 -9.7 19 3.5% Counts Mar 5th FCS D III Tune Up
74 Navy Win 13-11 12.55 37 3.5% Counts Mar 5th FCS D III Tune Up
181 Davidson Win 13-12 -7.56 20 3.5% Counts Mar 5th FCS D III Tune Up
87 Richmond Loss 9-10 -2.31 26 3.5% Counts Mar 6th FCS D III Tune Up
214 Wooster Win 12-8 -0.6 13 3.5% Counts Mar 6th FCS D III Tune Up
115 Miami (Ohio) Loss 0-13 -25.68 22 3.71% Counts (Why) Mar 12th Boogienights
251 Wright State Loss 7-11 -38.19 23 3.61% Counts Mar 12th Boogienights
206 Kenyon Win 12-10 -10.21 1 4.95% Counts Apr 16th Ohio D III College Mens CC 2022
324 Xavier** Win 13-5 0 8 0% Ignored (Why) Apr 16th Ohio D III College Mens CC 2022
211 Franciscan Win 13-9 -1.47 23 4.95% Counts Apr 17th Ohio D III College Mens CC 2022
206 Kenyon Win 14-11 -7.11 1 5.55% Counts Apr 30th Ohio Valley D III College Mens Regionals 2022
211 Franciscan Win 14-11 -7.85 23 5.55% Counts Apr 30th Ohio Valley D III College Mens Regionals 2022
219 Swarthmore Win 15-9 2.92 16 5.55% Counts Apr 30th Ohio Valley D III College Mens Regionals 2022
128 Scranton Win 15-11 16.14 17 5.55% Counts May 1st Ohio Valley D III College Mens Regionals 2022
34 St. Olaf Loss 13-15 11.39 21 6.6% Counts May 21st 2022 D III College Championships
146 Brandeis Win 15-9 22.42 153 6.6% Counts May 21st 2022 D III College Championships
147 Grace Win 15-9 22.42 47 6.6% Counts May 21st 2022 D III College Championships
35 Middlebury Loss 5-15 -16.21 60 6.6% Counts (Why) May 22nd 2022 D III College Championships
123 Williams Win 13-11 10.1 127 6.6% Counts May 22nd 2022 D III College Championships
68 Colorado College Win 14-12 28.41 37 6.6% Counts May 23rd 2022 D III College Championships
**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.