(1) #87 Vermont-B (12-7)

1139.77 (291)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
105 Amherst Win 7-5 10.51 197 4.4% Counts Mar 2nd Bam Bam Bonanza
191 Brandeis** Win 13-0 0 176 0% Ignored (Why) Mar 2nd Bam Bam Bonanza
51 Middlebury Loss 3-8 -11.61 321 4.3% Counts (Why) Mar 2nd Bam Bam Bonanza
105 Amherst Win 10-4 32.44 197 6.09% Counts (Why) Mar 29th Northeast Classic 2025
96 Ithaca Loss 9-10 -12.8 282 6.97% Counts Mar 29th Northeast Classic 2025
56 Rochester Loss 6-11 -18.69 165 6.59% Counts Mar 29th Northeast Classic 2025
86 Wellesley Win 9-7 19.35 323 6.4% Counts Mar 29th Northeast Classic 2025
51 Middlebury Loss 8-13 -11.56 321 6.97% Counts Mar 30th Northeast Classic 2025
112 SUNY-Binghamton Win 8-6 8.32 265 5.98% Counts Mar 30th Northeast Classic 2025
120 Brown-B Win 8-4 24.03 425 6.22% Counts (Why) Apr 12th New England Dev Womens Conferences 2025
233 Northeastern-B** Win 10-2 0 118 0% Ignored (Why) Apr 12th New England Dev Womens Conferences 2025
153 Tufts-B Win 7-5 -8.6 6.22% Counts Apr 12th New England Dev Womens Conferences 2025
120 Brown-B Win 8-5 17.39 425 6.47% Counts (Why) Apr 13th New England Dev Womens Conferences 2025
183 Vermont-C** Win 13-2 0 209 0% Ignored (Why) Apr 13th New England Dev Womens Conferences 2025
148 Boston University Win 14-7 16.04 256 8.78% Counts (Why) Apr 26th New England D I College Womens Regionals 2025
174 New Hampshire Win 14-3 4.05 177 8.78% Counts (Why) Apr 26th New England D I College Womens Regionals 2025
26 Northeastern** Loss 5-13 0 293 0% Ignored (Why) Apr 26th New England D I College Womens Regionals 2025
138 Massachusetts Loss 8-9 -42.27 85 8.31% Counts Apr 27th New England D I College Womens Regionals 2025
94 Rhode Island Loss 6-8 -27.58 163 7.54% Counts Apr 27th New England D I College Womens Regionals 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.