(10) #96 Connecticut (14-7)

1249.4 (26)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
70 Case Western Reserve Loss 9-10 -0.31 4 3.86% Counts Jan 27th Mid Atlantic Warm Up
111 SUNY-Binghamton Loss 9-11 -12.32 14 3.86% Counts Jan 27th Mid Atlantic Warm Up
208 Virginia Commonwealth Win 10-7 -2.82 52 3.65% Counts Jan 27th Mid Atlantic Warm Up
61 William & Mary Loss 9-10 2.31 50 3.86% Counts Jan 27th Mid Atlantic Warm Up
224 American Win 14-4 3.31 64 3.86% Counts (Why) Jan 28th Mid Atlantic Warm Up
208 Virginia Commonwealth Win 15-2 5.46 52 3.86% Counts (Why) Jan 28th Mid Atlantic Warm Up
116 Liberty Win 12-10 6.89 8 3.86% Counts Jan 28th Mid Atlantic Warm Up
142 Boston University Win 10-8 4.33 17 5.01% Counts Mar 2nd No Sleep till Brooklyn 2024
198 Delaware Win 9-8 -14.84 7 4.87% Counts Mar 2nd No Sleep till Brooklyn 2024
31 Middlebury Loss 5-12 -10 9 4.94% Counts (Why) Mar 2nd No Sleep till Brooklyn 2024
167 Columbia Win 10-8 -1.5 38 5.01% Counts Mar 3rd No Sleep till Brooklyn 2024
198 Delaware Win 8-6 -5.28 7 4.42% Counts Mar 3rd No Sleep till Brooklyn 2024
46 Williams Loss 10-11 8.18 34 5.15% Counts Mar 3rd No Sleep till Brooklyn 2024
150 Navy Win 12-11 -6.25 45 6.49% Counts Mar 30th East Coast Invite 2024
113 Syracuse Win 11-10 4.47 30 6.49% Counts Mar 30th East Coast Invite 2024
278 SUNY-Stony Brook** Win 11-4 0 137 0% Ignored (Why) Mar 30th East Coast Invite 2024
25 McGill Loss 9-13 7.38 130 6.49% Counts Mar 30th East Coast Invite 2024
167 Columbia Win 9-7 -0.75 38 5.96% Counts Mar 31st East Coast Invite 2024
123 Pennsylvania Loss 10-11 -15.75 59 6.49% Counts Mar 31st East Coast Invite 2024
146 Yale Win 12-7 22.99 8 6.49% Counts (Why) Mar 31st East Coast Invite 2024
107 Princeton Win 7-6 4.78 61 5.37% Counts Mar 31st East Coast Invite 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.