(2) #75 Boston College (8-10)

1276.09 (34)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
53 Tulane Loss 9-10 2.22 24 5.38% Counts Mar 19th Mens College Centex
84 Iowa Win 10-8 12.45 8 5.24% Counts Mar 19th Mens College Centex
124 Texas State Loss 6-8 -24.38 16 4.62% Counts Mar 19th Mens College Centex
47 Florida Loss 8-11 -9.37 26 5.38% Counts Mar 19th Mens College Centex
70 Chicago Loss 11-13 -10.09 19 5.38% Counts Mar 20th Mens College Centex
77 Arkansas Win 12-9 18.59 19 5.38% Counts Mar 20th Mens College Centex
72 Texas A&M Loss 2-9 -27.33 18 4.45% Counts (Why) Mar 20th Mens College Centex
12 Northeastern Loss 4-13 -2.65 36 6.78% Counts (Why) Apr 16th Metro Boston D I College Mens CC 2022
165 MIT Win 13-8 8.59 44 6.78% Counts Apr 16th Metro Boston D I College Mens CC 2022
129 Boston University Win 10-8 2.6 31 6.6% Counts Apr 16th Metro Boston D I College Mens CC 2022
162 Massachusetts-Lowell Win 13-8 8.87 43 6.78% Counts Apr 17th Metro Boston D I College Mens CC 2022
18 Tufts Loss 9-11 13.85 28 6.78% Counts Apr 17th Metro Boston D I College Mens CC 2022
93 Harvard Win 12-5 35.89 37 6.5% Counts (Why) Apr 17th Metro Boston D I College Mens CC 2022
7 Massachusetts** Loss 5-13 0 34 0% Ignored (Why) May 7th New England D I College Mens Regionals 2022
9 Vermont** Loss 5-13 0 97 0% Ignored (Why) May 7th New England D I College Mens Regionals 2022
185 Northeastern-B Win 13-12 -29.89 90 8.06% Counts May 7th New England D I College Mens Regionals 2022
18 Tufts Loss 5-13 -14.05 28 8.06% Counts (Why) May 7th New England D I College Mens Regionals 2022
93 Harvard Win 10-8 15.19 37 7.85% Counts May 8th New England D I College Mens Regionals 2022
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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.