(1) #60 Ohio (12-7)

1299.34 (133)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
7 Carleton College** Loss 0-12 0 141 0% Ignored (Why) Feb 11th Queen City Tune Up1
38 Chicago Loss 9-10 11.85 135 7.66% Counts Feb 11th Queen City Tune Up1
64 Appalachian State Win 8-4 34.98 136 6.09% Counts (Why) Feb 11th Queen City Tune Up1
14 Virginia Loss 6-10 10.22 139 7.03% Counts Feb 11th Queen City Tune Up1
69 Case Western Reserve Win 9-6 26.99 134 6.8% Counts Feb 12th Queen City Tune Up1
40 Georgia Loss 4-9 -24.93 149 6.33% Counts (Why) Feb 12th Queen City Tune Up1
137 Cincinnati Win 9-3 1.4 133 7.53% Counts (Why) Mar 4th Huckleberry Flick Tournament
176 Dayton** Win 9-3 0 133 0% Ignored (Why) Mar 4th Huckleberry Flick Tournament
217 SUNY-Buffalo** Win 12-0 0 133 0% Ignored (Why) Mar 4th Huckleberry Flick Tournament
205 Miami (Ohio)** Win 12-3 0 133 0% Ignored (Why) Mar 4th Huckleberry Flick Tournament
137 Cincinnati Win 8-4 -1.4 133 7.24% Counts (Why) Mar 5th Huckleberry Flick Tournament
176 Dayton** Win 6-2 0 133 0% Ignored (Why) Mar 5th Huckleberry Flick Tournament
30 South Carolina Loss 5-10 -22.62 133 9.62% Counts Mar 25th Rodeo 2023
184 Georgetown-B** Win 11-3 0 138 0% Ignored (Why) Mar 25th Rodeo 2023
215 Elon** Win 13-0 0 151 0% Ignored (Why) Mar 25th Rodeo 2023
71 Massachusetts Win 12-7 55.22 145 10.83% Counts (Why) Mar 25th Rodeo 2023
28 Duke Loss 4-12 -25.2 139 10.39% Counts (Why) Mar 26th Rodeo 2023
130 Liberty Win 10-6 -3.25 124 9.94% Counts (Why) Mar 26th Rodeo 2023
58 Williams Loss 6-12 -65.26 110 10.54% Counts Mar 26th Rodeo 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.