(11) #119 Clemson (8-17)

1283.55 (34)

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# Opponent Result Effect % of Ranking Status Date Event
61 Tennessee Win 13-8 27.98 3.52% Jan 25th Carolina Kickoff 2019
25 South Carolina Loss 6-12 -2.7 3.43% Jan 26th Carolina Kickoff 2019
69 Emory Loss 6-12 -12.58 3.43% Jan 26th Carolina Kickoff 2019
52 Notre Dame Loss 6-9 -2.44 3.13% Jan 26th Carolina Kickoff 2019
62 Duke Loss 8-15 -10.85 3.52% Jan 27th Carolina Kickoff 2019
66 Penn State Loss 9-11 0.1 3.95% Feb 9th Queen City Tune Up 2019 Men
79 Tulane Win 11-10 12.26 3.95% Feb 9th Queen City Tune Up 2019 Men
47 Maryland Loss 10-12 5.54 3.95% Feb 9th Queen City Tune Up 2019 Men
9 Massachusetts** Loss 3-13 0 0% Ignored Feb 9th Queen City Tune Up 2019 Men
24 Auburn Loss 6-15 -3.57 3.95% Feb 10th Queen City Tune Up 2019 Men
52 Notre Dame Loss 8-14 -7.94 3.95% Feb 10th Queen City Tune Up 2019 Men
79 Tulane Loss 6-7 1.62 3.27% Feb 10th Queen City Tune Up 2019 Men
53 Indiana Loss 5-9 -6.93 3.59% Feb 16th Easterns Qualifier 2019
197 George Mason Win 12-10 -1.92 4.19% Feb 16th Easterns Qualifier 2019
81 Georgia Tech Loss 9-13 -11.14 4.19% Feb 16th Easterns Qualifier 2019
64 Ohio Loss 7-13 -13.18 4.19% Feb 16th Easterns Qualifier 2019
139 Pennsylvania Win 15-12 10.78 4.19% Feb 17th Easterns Qualifier 2019
126 New Hampshire Win 12-10 10.05 4.19% Feb 17th Easterns Qualifier 2019
101 Connecticut Win 13-12 8.64 4.19% Feb 17th Easterns Qualifier 2019
103 Georgia State Loss 6-11 -25.31 4.99% Mar 16th Tally Classic XIV
43 Harvard Loss 6-12 -10.32 5.13% Mar 16th Tally Classic XIV
79 Tulane Win 10-9 16.59 5.28% Mar 16th Tally Classic XIV
52 Notre Dame Loss 14-15 12.15 5.28% Mar 16th Tally Classic XIV
159 Mississippi State Win 15-11 12.44 5.28% Mar 17th Tally Classic XIV
88 Tennessee-Chattanooga Loss 12-15 -9.18 5.28% Mar 17th Tally Classic XIV
**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.