(1) #244 Kent State (7-15)

891.15 (16)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
127 Butler Loss 1-13 -6.99 16 4.29% Counts (Why) Mar 1st Huckin in the Hills XI
307 Cleveland State Win 5-4 -3.42 14 2.95% Counts Mar 1st Huckin in the Hills XI
215 Akron Loss 10-11 -0.82 16 4.29% Counts Mar 2nd Huckin in the Hills XI
226 West Virginia Win 11-8 18.98 15 4.29% Counts Mar 2nd Huckin in the Hills XI
179 Ohio Loss 1-13 -15.25 16 4.29% Counts (Why) Mar 2nd Huckin in the Hills XI
144 Oberlin Loss 8-12 -3.14 15 4.82% Counts Mar 15th Spring Spook
218 Miami (Ohio) Loss 6-7 -0.83 16 3.99% Counts Mar 15th Spring Spook
215 Akron Win 12-10 17.46 16 4.82% Counts Mar 16th Spring Spook
323 Cincinnati -B Win 15-7 15.17 11 4.82% Counts (Why) Mar 16th Spring Spook
144 Oberlin Loss 9-15 -6.9 15 4.82% Counts Mar 16th Spring Spook
79 Case Western Reserve** Loss 1-13 0 17 0% Ignored (Why) Apr 12th Ohio D I Mens Conferences 2025
167 Dayton Loss 5-12 -18.51 19 5.83% Counts (Why) Apr 12th Ohio D I Mens Conferences 2025
263 Toledo Win 13-10 16.64 17 6.07% Counts Apr 12th Ohio D I Mens Conferences 2025
179 Ohio Loss 7-12 -16.83 16 6.07% Counts Apr 12th Ohio D I Mens Conferences 2025
215 Akron Loss 9-11 -9.21 16 6.07% Counts Apr 13th Ohio D I Mens Conferences 2025
348 Wright State Win 15-3 10.62 15 6.07% Counts (Why) Apr 13th Ohio D I Mens Conferences 2025
179 Ohio Loss 10-14 -8.96 16 6.07% Counts Apr 13th Ohio D I Mens Conferences 2025
76 Ohio State** Loss 6-15 0 18 0% Ignored (Why) Apr 26th Ohio Valley D I College Mens Regionals 2025
30 Pittsburgh** Loss 2-15 0 23 0% Ignored (Why) Apr 26th Ohio Valley D I College Mens Regionals 2025
113 West Chester Loss 5-15 -8.42 17 6.81% Counts (Why) Apr 26th Ohio Valley D I College Mens Regionals 2025
218 Miami (Ohio) Win 15-9 45.37 16 6.81% Counts Apr 27th Ohio Valley D I College Mens Regionals 2025
179 Ohio Loss 6-15 -24.86 16 6.81% Counts (Why) Apr 27th Ohio Valley D I College Mens Regionals 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.