(2) #152 North Carolina-B (10-9)

689.66 (285)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
43 Duke Loss 8-15 20.56 326 6.22% Counts Jan 25th Carolina Kickoff 2025
258 Emory-B** Win 15-0 0 159 0% Ignored (Why) Jan 25th Carolina Kickoff 2025
9 North Carolina** Loss 1-15 0 404 0% Ignored (Why) Jan 25th Carolina Kickoff 2025
69 North Carolina State** Loss 5-15 0 358 0% Ignored (Why) Jan 25th Carolina Kickoff 2025
80 Appalachian State Loss 5-11 -4.54 485 5.71% Counts (Why) Jan 26th Carolina Kickoff 2025
100 Emory Loss 7-10 -0.26 247 5.89% Counts Jan 26th Carolina Kickoff 2025
116 Cedarville Loss 6-7 8.64 264 6.12% Counts Feb 15th 2025 Commonwealth Cup Weekend 1
150 Davidson Loss 4-7 -28.7 266 5.63% Counts Feb 15th 2025 Commonwealth Cup Weekend 1
49 Kenyon** Loss 2-11 0 339 0% Ignored (Why) Feb 15th 2025 Commonwealth Cup Weekend 1
188 Wake Forest Loss 4-6 -31.77 452 5.37% Counts Feb 15th 2025 Commonwealth Cup Weekend 1
212 Georgetown-B Win 11-1 13.5 234 6.79% Counts (Why) Feb 16th 2025 Commonwealth Cup Weekend 1
213 Georgia-B Win 11-0 13.35 204 6.79% Counts (Why) Feb 16th 2025 Commonwealth Cup Weekend 1
212 Georgetown-B Win 10-7 -3.13 234 11.11% Counts Apr 12th Atlantic Coast Dev Womens Conferences 2025
239 William & Mary-B Win 8-4 -4.96 454 9.33% Counts (Why) Apr 12th Atlantic Coast Dev Womens Conferences 2025
227 South Carolina-B Win 9-6 -9.67 262 10.44% Counts Apr 12th Atlantic Coast Dev Womens Conferences 2025
260 Virginia-B** Win 12-3 0 0% Ignored (Why) Apr 12th Atlantic Coast Dev Womens Conferences 2025
252 American-B** Win 13-1 0 273 0% Ignored (Why) Apr 13th Atlantic Coast Dev Womens Conferences 2025
212 Georgetown-B Win 8-4 15.46 234 9.33% Counts (Why) Apr 13th Atlantic Coast Dev Womens Conferences 2025
227 South Carolina-B Win 12-5 12.51 262 11.27% Counts (Why) Apr 13th Atlantic Coast Dev Womens Conferences 2025
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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.