(1) #30 South Carolina (13-6)

1660.8 (133)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
21 North Carolina State Loss 10-12 -7.56 132 5.04% Counts Jan 21st Carolina Kickoff womens and nonbinary
64 Appalachian State Win 12-4 10.85 136 4.83% Counts (Why) Jan 21st Carolina Kickoff womens and nonbinary
144 North Carolina-B** Win 14-2 0 135 0% Ignored (Why) Jan 21st Carolina Kickoff womens and nonbinary
28 Duke Win 7-6 6.36 139 4.17% Counts Jan 22nd Carolina Kickoff womens and nonbinary
1 North Carolina** Loss 1-15 0 141 0% Ignored (Why) Jan 22nd Carolina Kickoff womens and nonbinary
56 Tennessee Win 15-1 20.15 128 6.72% Counts (Why) Feb 25th Commonwealth Cup Weekend2 2023
26 Notre Dame Win 15-6 45.22 132 6.72% Counts (Why) Feb 25th Commonwealth Cup Weekend2 2023
65 Carnegie Mellon Win 14-9 6.27 115 6.72% Counts Feb 25th Commonwealth Cup Weekend2 2023
13 Pittsburgh Loss 7-13 -20.54 145 6.72% Counts Feb 26th Commonwealth Cup Weekend2 2023
33 Ohio State Win 9-7 16.6 145 6.17% Counts Feb 26th Commonwealth Cup Weekend2 2023
69 Case Western Reserve Win 13-1 13.67 134 6.72% Counts (Why) Feb 26th Commonwealth Cup Weekend2 2023
26 Notre Dame Loss 7-11 -30.76 132 6.54% Counts Feb 26th Commonwealth Cup Weekend2 2023
71 Massachusetts Win 11-7 3.56 145 8.24% Counts Mar 25th Rodeo 2023
60 Ohio Win 10-5 17.29 133 7.52% Counts (Why) Mar 25th Rodeo 2023
28 Duke Loss 2-10 -46.24 139 7.4% Counts (Why) Mar 25th Rodeo 2023
184 Georgetown-B** Win 13-2 0 138 0% Ignored (Why) Mar 25th Rodeo 2023
215 Elon** Win 13-3 0 151 0% Ignored (Why) Mar 26th Rodeo 2023
21 North Carolina State Loss 7-10 -25.62 132 8.01% Counts Mar 26th Rodeo 2023
59 Penn State Win 11-9 -10.21 119 8.47% 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.