(1) #84 Virginia (11-11)

1402.14 (10)

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# Opponent Result Effect % of Ranking Status Date Event
48 Dartmouth Loss 10-13 -6.89 4.01% Feb 3rd Mid Atlantic Warmup 2018
107 Rutgers Win 13-9 13.82 4.01% Feb 3rd Mid Atlantic Warmup 2018
126 Elon Loss 10-13 -21.65 4.01% Feb 3rd Mid Atlantic Warmup 2018
78 Georgetown Loss 10-13 -13.17 4.01% Feb 3rd Mid Atlantic Warmup 2018
250 Maryland-Baltimore County** Win 15-4 0 0% Ignored Feb 4th Mid Atlantic Warmup 2018
227 Syracuse Win 15-3 1.43 4.01% Feb 4th Mid Atlantic Warmup 2018
177 Virginia Commonwealth Win 13-8 4.86 4.01% Feb 4th Mid Atlantic Warmup 2018
33 Maryland Loss 9-13 -6.43 4.5% Feb 17th Easterns Qualifier 2018
51 Ohio State Loss 11-13 -4.4 4.5% Feb 17th Easterns Qualifier 2018
46 South Carolina Win 9-5 28.39 3.86% Feb 17th Easterns Qualifier 2018
75 Tennessee-Chattanooga Loss 10-11 -5.25 4.5% Feb 17th Easterns Qualifier 2018
62 Vermont Win 11-8 20.24 4.5% Feb 17th Easterns Qualifier 2018
113 Lehigh Loss 9-11 -17.31 4.5% Feb 18th Easterns Qualifier 2018
133 Case Western Reserve Win 14-6 17.61 4.5% Feb 18th Easterns Qualifier 2018
151 George Mason Win 15-6 14.83 4.5% Feb 18th Easterns Qualifier 2018
12 North Carolina State Loss 12-14 17.78 5.67% Mar 16th Atlantic Coast Showcase ACS NCSU vs Virginia
61 James Madison Loss 12-13 -3.49 6.01% Mar 24th Atlantic Coast Open 2018
243 Rowan Win 10-6 -7.12 5.51% Mar 24th Atlantic Coast Open 2018
174 East Carolina Win 10-5 11.52 5.34% Mar 24th Atlantic Coast Open 2018
78 Georgetown Loss 11-12 -7.16 6.01% Mar 24th Atlantic Coast Open 2018
194 George Washington Win 13-11 -13.35 6.01% Mar 25th Atlantic Coast Open 2018
56 Temple Loss 8-13 -24.85 6.01% Mar 25th Atlantic Coast Open 2018
**Blowout Eligible

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.