(6) #25 Middlebury (16-2)

2004.07 (347)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
102 Connecticut Win 12-5 6.16 246 6.34% Counts (Why) Mar 2nd No Sleep till Brooklyn 2024
93 Princeton Win 11-10 -24.12 329 6.61% Counts Mar 2nd No Sleep till Brooklyn 2024
120 Syracuse** Win 13-1 0 214 0% Ignored (Why) Mar 2nd No Sleep till Brooklyn 2024
141 Boston University** Win 13-3 0 274 0% Ignored (Why) Mar 3rd No Sleep till Brooklyn 2024
55 Williams Loss 10-12 -34.85 225 6.61% Counts Mar 3rd No Sleep till Brooklyn 2024
75 Dartmouth Win 13-8 8.38 367 7.42% Counts Mar 16th College Mens Centex Tier 1
107 Iowa State Win 13-9 -8.76 321 7.42% Counts Mar 16th College Mens Centex Tier 1
10 Texas Loss 7-8 8.26 310 6.59% Counts Mar 16th College Mens Centex Tier 1
49 Michigan State Win 10-7 12.38 313 7.01% Counts Mar 17th College Mens Centex Tier 1
80 Bates Win 13-11 -18.99 274 9.34% Counts Apr 13th North New England D III Mens Conferences 2024
115 Bowdoin Win 15-5 3.39 221 9.34% Counts (Why) Apr 13th North New England D III Mens Conferences 2024
225 Colby** Win 15-6 0 240 0% Ignored (Why) Apr 13th North New England D III Mens Conferences 2024
279 Amherst** Win 15-3 0 223 0% Ignored (Why) May 4th New England D III College Mens Regionals 2024
80 Bates Win 12-7 13.42 274 11.11% Counts (Why) May 4th New England D III College Mens Regionals 2024
225 Colby** Win 15-2 0 240 0% Ignored (Why) May 4th New England D III College Mens Regionals 2024
218 Middlebury-B** Win 15-6 0 383 0% Ignored (Why) May 4th New England D III College Mens Regionals 2024
115 Bowdoin Win 13-6 4.11 221 11.11% Counts (Why) May 5th New England D III College Mens Regionals 2024
55 Williams Win 15-9 32.62 225 11.11% Counts May 5th New England D III College Mens Regionals 2024
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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.