(23) #122 Yale (15-4)

1279.52 (82)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
118 MIT Win 13-10 18.35 58 5.17% Counts Mar 9th Atlantic City 9
77 Colby Loss 7-13 -19.88 128 5.17% Counts Mar 9th Atlantic City 9
335 College of New Jersey Win 13-6 -7.55 278 5.17% Counts (Why) Mar 9th Atlantic City 9
252 SUNY-Cortland Win 13-6 9.04 50 5.17% Counts (Why) Mar 9th Atlantic City 9
118 MIT Loss 7-9 -13.51 58 4.75% Counts Mar 10th Atlantic City 9
201 Brown-B Win 12-7 12.21 5 5.17% Counts (Why) Mar 10th Atlantic City 9
95 Bates College Loss 9-11 -8.67 182 5.17% Counts Mar 10th Atlantic City 9
426 Sacred Heart** Win 13-4 0 322 0% Ignored (Why) Mar 24th The Mightiest Huck 2019
337 Southern Connecticut State Win 11-6 -11.55 111 5.49% Counts (Why) Mar 24th The Mightiest Huck 2019
181 Massachusetts-C Win 10-9 -6.07 108 5.81% Counts Mar 24th The Mightiest Huck 2019
211 University of Massachusetts Amherst-B Win 13-8 10.4 84 5.81% Counts Mar 24th The Mightiest Huck 2019
230 Stonehill Win 12-6 12.68 108 5.65% Counts (Why) Mar 24th The Mightiest Huck 2019
217 Amherst College Win 10-3 14.03 79 5.37% Counts (Why) Mar 30th Tea Cup 2019
127 Boston College Win 10-6 29.4 32 5.65% Counts (Why) Mar 30th Tea Cup 2019
225 SUNY-Oneonta Win 10-8 -6.39 18 5.99% Counts Mar 30th Tea Cup 2019
262 Tufts-B Win 10-8 -12.55 342 5.99% Counts Mar 30th Tea Cup 2019
217 Amherst College Win 13-8 9.39 79 6.15% Counts Mar 31st Tea Cup 2019
127 Boston College Loss 8-11 -24.28 32 6.15% Counts Mar 31st Tea Cup 2019
211 University of Massachusetts Amherst-B Win 11-9 -5.13 84 6.15% Counts Mar 31st Tea Cup 2019
**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.