(9) #38 Duke (15-5)

1890.8 (74)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
150 North Carolina-B Win 15-8 -16.42 3 4.47% Counts (Why) Jan 25th Carolina Kickoff 2025
99 Emory Win 15-2 1.46 269 4.47% Counts (Why) Jan 25th Carolina Kickoff 2025
62 North Carolina State Win 12-7 13.15 81 4.47% Counts (Why) Jan 25th Carolina Kickoff 2025
9 North Carolina Loss 8-15 3.13 23 4.47% Counts Jan 25th Carolina Kickoff 2025
55 Appalachian State Win 12-8 11.68 225 4.47% Counts Jan 26th Carolina Kickoff 2025
242 Emory-B** Win 15-2 0 570 0% Ignored (Why) Jan 26th Carolina Kickoff 2025
145 Boston College** Win 9-2 0 271 0% Ignored (Why) Feb 22nd 2025 Commonwealth Cup Weekend 2
80 Carnegie Mellon Win 9-4 9.02 612 4.66% Counts (Why) Feb 22nd 2025 Commonwealth Cup Weekend 2
75 Chicago Win 6-3 7 160 3.87% Counts (Why) Feb 22nd 2025 Commonwealth Cup Weekend 2
33 Cornell Loss 6-8 -11.31 14 4.83% Counts Feb 22nd 2025 Commonwealth Cup Weekend 2
71 Central Florida Win 10-6 8.86 165 5.16% Counts (Why) Feb 23rd 2025 Commonwealth Cup Weekend 2
70 Connecticut Win 9-8 -11.12 104 5.32% Counts Feb 23rd 2025 Commonwealth Cup Weekend 2
57 James Madison Win 13-9 12.48 128 5.63% Counts Feb 23rd 2025 Commonwealth Cup Weekend 2
36 MIT Win 9-8 10.21 295 7.11% Counts Mar 29th East Coast Invite 2025
66 St Olaf Win 10-9 -11.54 81 7.51% Counts Mar 29th East Coast Invite 2025
19 Notre Dame Loss 7-11 -5.65 315 7.31% Counts Mar 29th East Coast Invite 2025
40 Haverford/Bryn Mawr Win 8-7 5.55 181 6.68% Counts Mar 29th East Coast Invite 2025
19 Notre Dame Loss 4-13 -16.63 315 7.51% Counts (Why) Mar 30th East Coast Invite 2025
23 Pennsylvania Loss 5-11 -18.14 99 6.89% Counts (Why) Mar 30th East Coast Invite 2025
36 MIT Win 5-4 7.27 295 5.17% Counts Mar 30th East Coast Invite 2025
**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.