(22) #75 Tennessee-Chattanooga (16-9)

1415.67 (83)

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# Opponent Result Effect % of Ranking Status Date Event
244 Berry Win 11-9 -13.41 3.38% Jan 27th Clutch Classic 2018
418 Kennesaw State-B** Win 13-0 0 0% Ignored Jan 27th Clutch Classic 2018
224 Georgia Southern Win 12-5 1.53 3.25% Jan 27th Clutch Classic 2018
376 Tulane-B** Win 13-1 0 0% Ignored Jan 27th Clutch Classic 2018
140 Florida Tech Loss 5-9 -23.26 2.91% Jan 28th Clutch Classic 2018
282 Wingate** Win 15-5 0 0% Ignored Jan 28th Clutch Classic 2018
33 Maryland Loss 8-13 -9.54 4.02% Feb 17th Easterns Qualifier 2018
51 Ohio State Win 13-8 25.92 4.02% Feb 17th Easterns Qualifier 2018
46 South Carolina Loss 9-13 -10.69 4.02% Feb 17th Easterns Qualifier 2018
62 Vermont Loss 9-10 -3.14 4.02% Feb 17th Easterns Qualifier 2018
84 Virginia Win 11-10 4.67 4.02% Feb 17th Easterns Qualifier 2018
61 James Madison Loss 14-15 -2.86 4.02% Feb 18th Easterns Qualifier 2018
64 North Carolina-Charlotte Loss 10-12 -8.02 4.02% Feb 18th Easterns Qualifier 2018
78 Georgetown Win 13-11 9.57 4.02% Feb 18th Easterns Qualifier 2018
150 North Carolina-Asheville Win 12-10 -2.48 5.07% Mar 17th College Southerns 2018
248 North Georgia Win 13-8 -7.76 5.07% Mar 17th College Southerns 2018
125 Georgia College Win 13-7 19.11 5.07% Mar 17th College Southerns 2018
69 Carleton College-GoP Win 12-11 8.48 5.07% Mar 17th College Southerns 2018
207 Florida-B Win 13-5 5.61 5.07% Mar 18th College Southerns 2018
125 Georgia College Loss 9-10 -17.35 5.07% Mar 18th College Southerns 2018
69 Carleton College-GoP Loss 5-13 -30.25 5.07% Mar 18th College Southerns 2018
89 John Brown Loss 12-15 -20.15 5.69% Mar 31st Huck Finn 2018
95 Purdue Win 13-10 16.02 5.69% Mar 31st Huck Finn 2018
58 Kansas Win 13-10 24.95 5.69% Mar 31st Huck Finn 2018
76 Chicago Win 15-8 34.07 5.69% Mar 31st Huck Finn 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.