(1) #92 Tennessee (3-15)

1267.11 (16)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
91 Indiana Loss 13-14 -6.51 100 5.1% Counts Jan 27th Carolina Kickoff 2024
28 North Carolina-Wilmington Loss 6-15 -7.12 109 5.1% Counts (Why) Jan 27th Carolina Kickoff 2024
29 South Carolina Loss 8-15 -7.95 52 5.1% Counts Jan 27th Carolina Kickoff 2024
78 Carleton College-CHOP Loss 11-15 -16.08 7 5.1% Counts Jan 28th Carolina Kickoff 2024
235 North Carolina-B Win 15-12 -14.99 8 5.1% Counts Jan 28th Carolina Kickoff 2024
12 Alabama-Huntsville Loss 8-15 9.82 3 5.72% Counts Feb 10th Queen City Tune Up 2024
72 Georgetown Loss 11-15 -17.15 30 5.72% Counts Feb 10th Queen City Tune Up 2024
48 Missouri Win 15-9 46.31 13 5.72% Counts Feb 10th Queen City Tune Up 2024
29 South Carolina Loss 8-15 -8.98 52 5.72% Counts Feb 10th Queen City Tune Up 2024
154 Harvard Win 8-7 -6.37 116 5.08% Counts Feb 11th Queen City Tune Up 2024
25 McGill Loss 7-15 -5.63 130 5.72% Counts (Why) Feb 11th Queen City Tune Up 2024
9 Brown Loss 7-13 14.63 49 6.8% Counts Mar 2nd Smoky Mountain Invite 2024
15 California Loss 6-13 4.17 35 6.8% Counts (Why) Mar 2nd Smoky Mountain Invite 2024
1 North Carolina** Loss 5-15 0 18 0% Ignored (Why) Mar 2nd Smoky Mountain Invite 2024
14 Texas Loss 6-13 5.08 30 6.8% Counts (Why) Mar 2nd Smoky Mountain Invite 2024
15 California Loss 8-15 6.74 35 6.8% Counts Mar 3rd Smoky Mountain Invite 2024
13 North Carolina State Loss 9-15 11.97 42 6.8% Counts Mar 3rd Smoky Mountain Invite 2024
26 Utah State Loss 7-15 -7.13 88 6.8% Counts (Why) Mar 3rd Smoky Mountain Invite 2024
**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.