(20) #138 Massachusetts (9-12)

798.11 (85)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
235 Cornell-B** Win 5-1 0 317 0% Ignored (Why) Mar 1st Garden State 2025
93 NYU Loss 4-6 -2.44 1 4.46% Counts Mar 1st Garden State 2025
162 Colby Win 5-3 11.65 177 3.99% Counts (Why) Mar 2nd Garden State 2025
104 Yale Win 4-3 14.26 141 3.74% Counts (Why) Mar 2nd Garden State 2025
56 Rochester** Loss 2-6 0 165 0% Ignored (Why) Mar 2nd Garden State 2025
93 NYU Loss 2-4 -6.55 1 3.46% Counts Mar 2nd Garden State 2025
51 Middlebury** Loss 2-13 0 321 0% Ignored (Why) Mar 29th Northeast Classic 2025
86 Wellesley Loss 4-11 -19.49 323 7.11% Counts (Why) Mar 29th Northeast Classic 2025
112 SUNY-Binghamton Loss 3-8 -27.48 265 6.03% Counts (Why) Mar 29th Northeast Classic 2025
149 Dartmouth Loss 7-9 -28.27 412 7.11% Counts Mar 30th Northeast Classic 2025
163 SUNY-Geneseo Loss 6-8 -32.26 354 6.66% Counts Mar 30th Northeast Classic 2025
183 Vermont-C Win 8-6 2.01 209 6.66% Counts Mar 30th Northeast Classic 2025
61 Brown Loss 2-8 -3.41 316 6.77% Counts (Why) Apr 12th Greater New England D I Womens Conferences 2025
241 Maine** Win 11-2 0 0% Ignored (Why) Apr 12th Greater New England D I Womens Conferences 2025
5 Vermont** Loss 2-14 0 385 0% Ignored (Why) Apr 12th Greater New England D I Womens Conferences 2025
174 New Hampshire Win 5-4 -5.82 177 5.99% Counts Apr 12th Greater New England D I Womens Conferences 2025
151 Boston College Win 12-10 14.44 294 9.77% Counts Apr 26th New England D I College Womens Regionals 2025
131 Harvard Win 10-7 43.25 243 9.24% Counts Apr 26th New England D I College Womens Regionals 2025
3 Tufts** Loss 1-15 0 353 0% Ignored (Why) Apr 26th New England D I College Womens Regionals 2025
61 Brown Loss 4-15 -5.09 316 9.77% Counts (Why) Apr 27th New England D I College Womens Regionals 2025
87 Vermont-B Win 9-8 47.51 291 9.24% Counts Apr 27th New England D I College Womens Regionals 2025
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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.