(13) #34 Ohio State (10-11)

1641.87 (140)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
84 Appalachian State Win 15-8 11.2 40 4.29% Counts (Why) Feb 10th Queen City Tune Up 2024
68 James Madison Win 12-7 11.46 20 4.29% Counts (Why) Feb 10th Queen City Tune Up 2024
13 North Carolina State Loss 12-13 8.06 42 4.29% Counts Feb 10th Queen City Tune Up 2024
106 Notre Dame Win 15-3 7.55 25 4.29% Counts (Why) Feb 10th Queen City Tune Up 2024
154 Harvard Win 11-8 -11.35 116 4.29% Counts Feb 11th Queen City Tune Up 2024
1 North Carolina** Loss 5-13 0 18 0% Ignored (Why) Feb 11th Queen City Tune Up 2024
158 Kennesaw State** Win 13-3 0 9 0% Ignored (Why) Feb 24th Easterns Qualifier 2024
61 William & Mary Win 13-10 5.99 50 4.82% Counts Feb 24th Easterns Qualifier 2024
29 South Carolina Loss 9-10 -4.2 52 4.82% Counts Feb 24th Easterns Qualifier 2024
60 Temple Win 11-9 2.14 34 4.82% Counts Feb 24th Easterns Qualifier 2024
36 North Carolina-Charlotte Win 13-10 15.41 20 4.82% Counts Feb 25th Easterns Qualifier 2024
111 SUNY-Binghamton Win 12-5 7.26 14 4.62% Counts (Why) Feb 25th Easterns Qualifier 2024
16 Penn State Loss 11-12 7.81 59 4.82% Counts Feb 25th Easterns Qualifier 2024
66 Virginia Win 14-11 3.32 111 4.82% Counts Feb 25th Easterns Qualifier 2024
42 Michigan Loss 11-13 -20.91 170 6.43% Counts Mar 30th Easterns 2024
11 Minnesota Loss 9-13 -4 102 6.43% Counts Mar 30th Easterns 2024
1 North Carolina Loss 7-13 6.13 18 6.43% Counts Mar 30th Easterns 2024
8 Vermont Loss 11-13 11.54 36 6.43% Counts Mar 30th Easterns 2024
36 North Carolina-Charlotte Loss 10-13 -24.17 20 6.43% Counts Mar 31st Easterns 2024
20 Northeastern Loss 11-15 -13.24 65 6.43% Counts Mar 31st Easterns 2024
33 Wisconsin Loss 11-14 -21.28 14 6.43% Counts Mar 31st Easterns 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.