(16) #282 Navy (1-14)

763.93 (375)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
221 Christopher Newport Loss 6-13 -28.59 217 7.2% Counts (Why) Jan 25th Mid Atlantic Warm Up 2025
111 Vermont-B** Loss 2-13 0 224 0% Ignored (Why) Jan 25th Mid Atlantic Warm Up 2025
167 Pennsylvania Loss 4-13 -11.97 298 7.2% Counts (Why) Jan 25th Mid Atlantic Warm Up 2025
53 William & Mary** Loss 0-13 0 159 0% Ignored (Why) Jan 25th Mid Atlantic Warm Up 2025
172 East Carolina Loss 4-15 -13.93 295 7.2% Counts (Why) Jan 26th Mid Atlantic Warm Up 2025
231 Air Force Loss 10-11 5.64 195 9.61% Counts Mar 1st D III River City Showdown 2025
60 Carleton College-CHOP** Loss 2-13 0 124 0% Ignored (Why) Mar 1st D III River City Showdown 2025
145 Oberlin Loss 5-13 -8.41 19 9.61% Counts (Why) Mar 1st D III River City Showdown 2025
162 Brandeis Loss 3-11 -13.12 256 8.82% Counts (Why) Mar 2nd D III River City Showdown 2025
131 Kenyon Loss 6-13 -3.65 270 9.61% Counts (Why) Mar 2nd D III River City Showdown 2025
142 Davidson Loss 6-15 -11.4 237 13.59% Counts (Why) Apr 12th Atlantic Coast D III Mens Conferences 2025
33 Elon** Loss 4-15 0 238 0% Ignored (Why) Apr 12th Atlantic Coast D III Mens Conferences 2025
277 Salisbury Win 15-10 73.79 95 13.59% Counts Apr 12th Atlantic Coast D III Mens Conferences 2025
221 Christopher Newport Loss 12-13 16.73 217 13.59% Counts Apr 13th Atlantic Coast D III Mens Conferences 2025
102 North Carolina-Asheville** Loss 2-15 0 158 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.