(9) #316 Virginia-B (8-11)

278.17 (1)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
151 Liberty** Loss 2-8 0 1 0% Ignored (Why) Feb 19th Commonwealth Cup Weekend 1
188 Mary Washington Loss 5-10 -1.01 1 4.21% Counts Feb 19th Commonwealth Cup Weekend 1
95 Pennsylvania** Loss 2-10 0 69 0% Ignored (Why) Feb 19th Commonwealth Cup Weekend 1
259 Pittsburgh-B Loss 6-11 -12.39 56 4.48% Counts Feb 20th Commonwealth Cup Weekend 1
277 North Carolina State-B Loss 8-10 -3.03 46 4.61% Counts Feb 20th Commonwealth Cup Weekend 1
123 South Carolina-B** Loss 3-11 0 77 0% Ignored (Why) Mar 26th Hoos Huckin
263 James Madison-B Loss 4-10 -19.79 78 5.52% Counts (Why) Mar 26th Hoos Huckin
358 Georgetown-B Win 7-5 -3.85 95 5.02% Counts Mar 26th Hoos Huckin
358 Georgetown-B Win 12-6 11.68 95 6.15% Counts (Why) Mar 27th Hoos Huckin
344 William & Mary-B Win 12-8 16.57 85 6.32% Counts Mar 27th Hoos Huckin
306 Virginia Tech-B Loss 4-12 -35.41 79 6.06% Counts (Why) Mar 27th Hoos Huckin
263 James Madison-B Loss 9-15 -21.99 78 7.96% Counts Apr 23rd Southern Atlantic Coast Dev College Mens CC 2022
344 William & Mary-B Win 12-11 -6.09 85 7.96% Counts Apr 23rd Southern Atlantic Coast Dev College Mens CC 2022
306 Virginia Tech-B Win 13-11 24.24 79 7.96% Counts Apr 24th Southern Atlantic Coast Dev College Mens CC 2022
123 South Carolina-B** Loss 2-15 0 77 0% Ignored (Why) May 7th Atlantic Coast Dev College Mens Regionals 2022
315 George Washington-B Win 15-12 29.9 212 8.94% Counts May 7th Atlantic Coast Dev College Mens Regionals 2022
356 Towson -B Win 15-6 22.22 95 8.94% Counts (Why) May 7th Atlantic Coast Dev College Mens Regionals 2022
219 Maryland-B Loss 6-15 -16.31 65 8.94% Counts (Why) May 8th Atlantic Coast Dev College Mens Regionals 2022
356 Towson -B Win 8-1 16.92 95 6.95% Counts (Why) May 8th Atlantic Coast Dev College Mens Regionals 2022
**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.