(15) #84 Elon (15-4)

1576.44 (334)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
86 Cedarville Loss 9-11 -14.19 200 4.99% Counts Feb 17th Commonwealth Cup Weekend 1 2024
214 North Carolina-B Win 13-7 2.88 386 4.99% Counts (Why) Feb 17th Commonwealth Cup Weekend 1 2024
254 Michigan-B** Win 13-5 0 522 0% Ignored (Why) Feb 17th Commonwealth Cup Weekend 1 2024
86 Cedarville Win 11-10 5.47 200 4.99% Counts Feb 18th Commonwealth Cup Weekend 1 2024
104 Liberty Win 11-9 8.59 308 4.99% Counts Feb 18th Commonwealth Cup Weekend 1 2024
64 Maryland Loss 7-8 -1.09 235 4.44% Counts Feb 18th Commonwealth Cup Weekend 1 2024
274 Air Force** Win 13-3 0 279 0% Ignored (Why) Mar 2nd FCS D III Tune Up 2024
88 Berry Loss 12-13 -8.89 379 5.6% Counts Mar 2nd FCS D III Tune Up 2024
198 Messiah Win 13-9 -1.71 297 5.6% Counts Mar 2nd FCS D III Tune Up 2024
123 Oberlin Win 13-12 -3.25 244 5.6% Counts Mar 2nd FCS D III Tune Up 2024
232 Butler Win 13-6 2 342 5.6% Counts (Why) Mar 3rd FCS D III Tune Up 2024
168 Kenyon Win 13-11 -5.65 493 5.6% Counts Mar 3rd FCS D III Tune Up 2024
173 Xavier Win 13-10 -0.88 260 5.6% Counts Mar 3rd FCS D III Tune Up 2024
209 Christopher Newport Win 14-5 9.63 369 8.4% Counts (Why) Apr 20th Atlantic Coast D III Mens Conferences 2024
179 North Carolina-Asheville Win 15-3 20.45 263 8.4% Counts (Why) Apr 20th Atlantic Coast D III Mens Conferences 2024
176 Navy Win 15-7 21.63 178 8.4% Counts (Why) Apr 20th Atlantic Coast D III Mens Conferences 2024
209 Christopher Newport Win 13-8 0.11 369 8.4% Counts Apr 21st Atlantic Coast D III Mens Conferences 2024
114 Davidson Loss 10-12 -34.58 291 8.4% Counts Apr 21st Atlantic Coast D III Mens Conferences 2024
306 High Point** Win 15-3 0 181 0% Ignored (Why) Apr 21st Atlantic Coast 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.