(35) #201 MIT (5-13)

1116.71 (436)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
163 Columbia Loss 5-10 -19.71 317 4.53% Counts Mar 2nd No Sleep till Brooklyn 2024
283 Hofstra Win 11-10 -9.8 360 5.1% Counts Mar 2nd No Sleep till Brooklyn 2024
131 Yale Loss 5-12 -17.36 319 4.89% Counts (Why) Mar 2nd No Sleep till Brooklyn 2024
80 Bates Loss 3-12 -6.47 274 4.89% Counts (Why) Mar 3rd No Sleep till Brooklyn 2024
175 Delaware Loss 9-11 -7.74 387 5.1% Counts Mar 3rd No Sleep till Brooklyn 2024
300 SUNY-Stony Brook Win 10-6 4.63 218 4.68% Counts (Why) Mar 3rd No Sleep till Brooklyn 2024
103 SUNY-Binghamton Loss 8-11 0.6 300 6.07% Counts Mar 23rd Carousel City Classic 2024
117 Rochester Loss 4-9 -15.29 391 5.02% Counts (Why) Mar 23rd Carousel City Classic 2024
120 Syracuse Loss 11-12 10.43 214 6.07% Counts Mar 23rd Carousel City Classic 2024
55 Williams** Loss 4-15 0 225 0% Ignored (Why) Mar 24th Carousel City Classic 2024
112 Boston College Loss 8-14 -15.3 266 7.21% Counts Apr 13th Metro Boston D I Mens Conferences 2024
297 Massachusetts-Lowell Win 15-6 16.54 201 7.21% Counts (Why) Apr 13th Metro Boston D I Mens Conferences 2024
141 Boston University Loss 3-15 -29.1 274 7.21% Counts (Why) Apr 14th Metro Boston D I Mens Conferences 2024
152 Harvard Win 10-9 24.84 288 7.21% Counts Apr 14th Metro Boston D I Mens Conferences 2024
112 Boston College Win 10-8 54.83 266 8.35% Counts May 4th New England D I College Mens Regionals 2024
75 Dartmouth Loss 6-10 -0.03 367 7.87% Counts May 4th New England D I College Mens Regionals 2024
18 Northeastern** Loss 2-13 0 278 0% Ignored (Why) May 4th New England D I College Mens Regionals 2024
138 Tufts-B Loss 11-12 11.45 279 8.58% Counts May 5th New England D I College Mens 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.