(4) #93 Tennessee (10-9)

1107.96 (93)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
243 Emory-B-B** Win 13-0 0 70 0% Ignored (Why) Jan 25th Clutch Classic 2020
92 Auburn Loss 6-7 -5.14 64 4.27% Counts Jan 25th Clutch Classic 2020
78 Central Florida Loss 3-13 -25.69 45 5.17% Counts (Why) Jan 25th Clutch Classic 2020
83 Clemson Loss 2-13 -27.56 19 5.17% Counts (Why) Jan 25th Clutch Classic 2020
122 Tulane Win 8-6 5.18 23 4.44% Counts Jan 26th Clutch Classic 2020
193 Georgia Southern Win 11-6 -12.35 83 4.89% Counts (Why) Jan 26th Clutch Classic 2020
103 Mississippi State Win 8-7 3.45 50 4.59% Counts Jan 26th Clutch Classic 2020
30 Vanderbilt Loss 3-11 -1.76 42 5.56% Counts (Why) Feb 15th Are we in love or just 2020
47 Alabama Loss 8-9 13.8 46 5.74% Counts Feb 15th Are we in love or just 2020
127 Alabama-Huntsville Loss 6-7 -17.51 103 5.02% Counts Feb 15th Are we in love or just 2020
92 Auburn Loss 8-10 -15.86 64 5.9% Counts Feb 15th Are we in love or just 2020
128 Alabama-Birmingham Loss 10-11 -22.47 75 6.06% Counts Feb 16th Are we in love or just 2020
128 Alabama-Birmingham Win 13-7 21.59 75 6.06% Counts (Why) Feb 16th Are we in love or just 2020
154 Wisconsin-Milwaukee Win 13-5 11.76 223 6.06% Counts (Why) Feb 16th Are we in love or just 2020
64 Mississippi Loss 6-9 -13.21 113 5.99% Counts Feb 29th TOTs 2020
127 Alabama-Huntsville Win 7-6 -4.82 103 5.58% Counts Feb 29th TOTs 2020
71 Purdue Win 8-7 19.05 258 5.99% Counts Feb 29th TOTs 2020
151 Georgia College Win 13-6 14.18 94 6.75% Counts (Why) Mar 1st TOTs 2020
64 Mississippi Win 13-3 58.71 113 6.75% Counts (Why) Mar 1st TOTs 2020
**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.