(13) #102 North Carolina-Asheville (12-6)

1459.86 (158)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
162 Brandeis Win 13-11 -0.17 256 5.79% Counts Mar 1st D III River City Showdown 2025
67 Franciscan Loss 3-13 -25.9 228 5.79% Counts (Why) Mar 1st D III River City Showdown 2025
131 Kenyon Win 10-5 24.05 270 5.14% Counts (Why) Mar 1st D III River City Showdown 2025
169 Michigan Tech Win 13-10 4.44 141 5.79% Counts Mar 1st D III River City Showdown 2025
60 Carleton College-CHOP Win 11-9 27.72 124 5.79% Counts Mar 2nd D III River City Showdown 2025
67 Franciscan Loss 10-13 -9.2 228 5.79% Counts Mar 2nd D III River City Showdown 2025
81 Rochester Win 12-11 13.53 215 5.79% Counts Mar 2nd D III River City Showdown 2025
133 Bates Loss 12-13 -20.41 266 7.29% Counts Mar 29th Easterns 2025
142 Davidson Win 13-6 33.95 237 7.29% Counts (Why) Mar 29th Easterns 2025
40 Lewis & Clark Loss 1-13 -19.84 148 7.29% Counts (Why) Mar 29th Easterns 2025
170 Messiah Win 13-10 4.98 213 7.29% Counts Mar 29th Easterns 2025
221 Christopher Newport Win 15-5 10.65 217 7.29% Counts (Why) Mar 30th Easterns 2025
221 Christopher Newport Win 11-1 11 217 7.51% Counts (Why) Apr 12th Atlantic Coast D III Mens Conferences 2025
365 High Point** Win 11-2 0 0% Ignored (Why) Apr 12th Atlantic Coast D III Mens Conferences 2025
290 Mary Washington** Win 11-2 0 0% Ignored (Why) Apr 12th Atlantic Coast D III Mens Conferences 2025
78 Richmond Loss 7-11 -29.81 234 7.97% Counts Apr 12th Atlantic Coast D III Mens Conferences 2025
142 Davidson Loss 13-14 -26.16 237 8.19% Counts Apr 13th Atlantic Coast D III Mens Conferences 2025
282 Navy** Win 15-2 0 375 0% Ignored (Why) Apr 13th Atlantic Coast D III Mens Conferences 2025
**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.