(6) #65 Tennessee (8-10)

1453.54 (83)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
61 Alabama-Huntsville Loss 7-12 -34.34 41 6.31% Counts Feb 15th Queen City Tune Up 2025
60 Michigan State Win 12-9 25.48 88 6.31% Counts Feb 15th Queen City Tune Up 2025
15 Washington University Loss 5-13 -6.87 70 6.31% Counts (Why) Feb 15th Queen City Tune Up 2025
104 Alabama Win 9-7 3.98 10 5.79% Counts Feb 16th Queen City Tune Up 2025
48 Maryland Loss 8-9 -0.82 58 5.97% Counts Feb 16th Queen City Tune Up 2025
4 Carleton College Loss 6-13 11.42 64 7.09% Counts (Why) Mar 1st Smoky Mountain Invite 2025
2 Colorado** Loss 5-15 0 146 0% Ignored (Why) Mar 1st Smoky Mountain Invite 2025
10 Oregon State Loss 9-13 8.36 9 7.09% Counts Mar 1st Smoky Mountain Invite 2025
20 Vermont Loss 7-13 -11.67 36 7.09% Counts Mar 1st Smoky Mountain Invite 2025
19 Georgia Loss 4-15 -12.28 91 7.09% Counts (Why) Mar 2nd Smoky Mountain Invite 2025
31 Minnesota Loss 6-15 -25.93 33 7.09% Counts (Why) Mar 2nd Smoky Mountain Invite 2025
13 Texas Loss 9-15 0.14 15 7.09% Counts Mar 2nd Smoky Mountain Invite 2025
184 East Carolina Win 13-7 -0.62 0 8.93% Counts (Why) Mar 29th Needle in a Ho Stack 2025
232 Georgia Southern** Win 13-3 0 184 0% Ignored (Why) Mar 29th Needle in a Ho Stack 2025
199 North Carolina State-B** Win 11-3 0 404 0% Ignored (Why) Mar 29th Needle in a Ho Stack 2025
96 Appalachian State Win 12-10 5.78 68 8.93% Counts Mar 30th Needle in a Ho Stack 2025
257 East Tennessee State** Win 15-0 0 335 0% Ignored (Why) Mar 30th Needle in a Ho Stack 2025
94 Tennessee-Chattanooga Win 15-8 38.31 4 8.93% Counts (Why) Mar 30th Needle in a Ho Stack 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.