(2) #30 Ohio State (9-11)

1835.97 (6)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
107 Tennessee Win 14-6 4.45 9 4.03% Counts (Why) Feb 11th Queen City Tune Up1
49 Notre Dame Win 15-7 17.12 27 4.03% Counts (Why) Feb 11th Queen City Tune Up1
51 Virginia Win 12-11 -3.17 1 4.03% Counts Feb 11th Queen City Tune Up1
41 William & Mary Win 14-11 8.25 18 4.03% Counts Feb 11th Queen City Tune Up1
1 North Carolina Loss 8-10 12.02 30 3.93% Counts Feb 12th Queen City Tune Up1
20 North Carolina State Loss 8-13 -16.26 3 4.03% Counts Feb 12th Queen City Tune Up1
14 Carleton College Loss 10-12 -1.22 20 4.8% Counts Mar 4th Smoky Mountain Invite
6 Colorado Loss 10-13 1.69 13 4.8% Counts Mar 4th Smoky Mountain Invite
19 Georgia Win 13-10 22.33 81 4.8% Counts Mar 4th Smoky Mountain Invite
5 Vermont Loss 6-13 -11.39 7 4.8% Counts (Why) Mar 4th Smoky Mountain Invite
72 Auburn Win 15-7 13.2 54 4.8% Counts (Why) Mar 5th Smoky Mountain Invite
19 Georgia Win 14-10 25.88 81 4.8% Counts Mar 5th Smoky Mountain Invite
21 Northeastern Loss 13-15 -7.21 6 4.8% Counts Mar 5th Smoky Mountain Invite
12 Minnesota Loss 7-13 -20.76 32 6.04% Counts Apr 1st Easterns 2023
1 North Carolina Loss 2-13 -2.79 30 6.04% Counts (Why) Apr 1st Easterns 2023
25 North Carolina-Wilmington Loss 9-11 -12.93 24 6.04% Counts Apr 1st Easterns 2023
21 Northeastern Loss 7-12 -28.91 6 6.04% Counts Apr 1st Easterns 2023
72 Auburn Win 15-3 16.85 54 6.04% Counts (Why) Apr 2nd Easterns 2023
34 Michigan Win 11-9 13 44 6.04% Counts Apr 2nd Easterns 2023
19 Georgia Loss 6-14 -31.21 81 6.04% Counts (Why) Apr 2nd Easterns 2023
**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.