(28) #181 Vermont-C (6-10)

610.94 (511)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
144 Skidmore Loss 3-9 -22.48 363 7% Counts (Why) Mar 30th Northeast Classic 2024
150 RIT Loss 2-13 -31.7 24 8.46% Counts (Why) Mar 30th Northeast Classic 2024
239 SUNY-Albany Win 8-5 -12.97 345 7% Counts (Why) Mar 30th Northeast Classic 2024
192 Connecticut College Win 7-5 19.35 446 6.73% Counts Mar 31st Northeast Classic 2024
191 Syracuse Loss 3-7 -43.07 243 6.14% Counts (Why) Mar 31st Northeast Classic 2024
180 SUNY-Buffalo Win 5-4 8.29 442 5.83% Counts Mar 31st Northeast Classic 2024
68 Vermont-B** Loss 2-10 0 14 0% Ignored (Why) Apr 20th New England Dev Womens Conferences 2024
216 Northeastern-B Win 8-6 -0.49 587 8.64% Counts Apr 20th New England Dev Womens Conferences 2024
208 Brown-B Win 11-4 36.39 100 9.24% Counts (Why) Apr 21st New England Dev Womens Conferences 2024
68 Vermont-B Loss 9-11 64.61 14 10.07% Counts Apr 21st New England Dev Womens Conferences 2024
216 Northeastern-B Win 11-4 29.95 587 9.24% Counts (Why) Apr 21st New England Dev Womens Conferences 2024
8 Tufts** Loss 1-15 0 164 0% Ignored (Why) May 4th New England D I College Womens Regionals 2024
68 Vermont-B** Loss 5-14 0 14 0% Ignored (Why) May 4th New England D I College Womens Regionals 2024
90 MIT** Loss 4-11 0 394 0% Ignored (Why) May 4th New England D I College Womens Regionals 2024
146 New Hampshire Loss 6-10 -24.89 131 10.37% Counts May 4th New England D I College Womens Regionals 2024
126 Massachusetts Loss 3-13 -21.4 125 11.3% Counts (Why) May 5th New England D I College Womens Regionals 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.