(3) #35 Ohio (12-7)

1798.14 (23)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
31 Brown Win 11-7 34.03 25 5.9% Counts Feb 24th Commonwealth Cup Weekend 2 2024
88 Virginia Tech Win 12-10 -16.95 16 6.06% Counts Feb 24th Commonwealth Cup Weekend 2 2024
42 Purdue Win 11-9 9.8 34 6.06% Counts Feb 24th Commonwealth Cup Weekend 2 2024
38 South Carolina Win 8-3 27.96 16 4.71% Counts (Why) Feb 25th Commonwealth Cup Weekend 2 2024
90 Carnegie Mellon Win 10-5 3.79 181 5.38% Counts (Why) Feb 25th Commonwealth Cup Weekend 2 2024
39 Virginia Loss 7-8 -10.49 9 5.38% Counts Feb 25th Commonwealth Cup Weekend 2 2024
25 Pittsburgh Loss 6-7 2.1 9 5.01% Counts Feb 25th Commonwealth Cup Weekend 2 2024
63 Cincinnati Loss 5-9 -48.37 5 5.51% Counts Mar 2nd Huckleberry Flick
204 Dayton** Win 12-4 0 8 0% Ignored (Why) Mar 2nd Huckleberry Flick
87 Indiana Win 9-8 -23.94 13 6.07% Counts Mar 2nd Huckleberry Flick
63 Cincinnati Win 10-4 17.82 5 5.61% Counts (Why) Mar 3rd Huckleberry Flick
87 Indiana Win 11-2 6.56 13 5.89% Counts (Why) Mar 3rd Huckleberry Flick
143 Oberlin** Win 12-3 0 8 0% Ignored (Why) Mar 3rd Huckleberry Flick
90 Carnegie Mellon Win 13-6 8.16 181 8.09% Counts (Why) Mar 30th East Coast Invite 2024
58 Cornell Win 8-5 13.12 21 6.69% Counts (Why) Mar 30th East Coast Invite 2024
2 Vermont** Loss 4-15 0 50 0% Ignored (Why) Mar 30th East Coast Invite 2024
20 Northeastern Loss 5-13 -26.09 107 8.09% Counts (Why) Mar 30th East Coast Invite 2024
7 Tufts Loss 6-11 14.53 52 7.65% Counts Mar 31st East Coast Invite 2024
29 Wisconsin Loss 8-10 -12.58 98 7.87% 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.