(6) #24 Auburn (18-9)

1796.78 (116)

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# Opponent Result Effect % of Ranking Status Date Event
36 Alabama Win 9-8 1.41 2.67% Jan 26th T Town Throwdown
48 Kennesaw State Win 13-2 13.07 2.82% Jan 26th T Town Throwdown
106 Illinois State Win 12-5 3.64 2.71% Jan 26th T Town Throwdown
37 Illinois Win 11-4 13.93 2.59% Jan 26th T Town Throwdown
72 Alabama-Huntsville Win 14-11 0.02 2.82% Jan 27th T Town Throwdown
37 Illinois Win 10-9 1.41 2.82% Jan 27th T Town Throwdown
27 LSU Loss 10-11 -4.19 2.82% Jan 27th T Town Throwdown
131 Chicago Win 13-4 2.28 3.17% Feb 9th Queen City Tune Up 2019 Men
44 Virginia Win 12-6 14.45 3.09% Feb 9th Queen City Tune Up 2019 Men
26 North Carolina-Wilmington Loss 9-12 -11.82 3.17% Feb 9th Queen City Tune Up 2019 Men
64 Ohio Loss 10-12 -16.22 3.17% Feb 9th Queen City Tune Up 2019 Men
94 Appalachian State Win 15-5 5.75 3.17% Feb 10th Queen City Tune Up 2019 Men
119 Clemson Win 15-6 2.84 3.17% Feb 10th Queen City Tune Up 2019 Men
44 Virginia Win 15-9 12.77 3.17% Feb 10th Queen City Tune Up 2019 Men
143 Minnesota-Duluth Win 13-3 0.1 4.23% Mar 16th Tally Classic XIV
55 Florida State Win 13-10 6.32 4.23% Mar 16th Tally Classic XIV
88 Tennessee-Chattanooga Win 12-7 6.31 4.23% Mar 16th Tally Classic XIV
43 Harvard Win 15-11 11.34 4.23% Mar 16th Tally Classic XIV
72 Alabama-Huntsville Win 12-10 -3.3 4.23% Mar 17th Tally Classic XIV
15 Central Florida Loss 10-15 -11.49 4.23% Mar 17th Tally Classic XIV
2 Brown Loss 11-13 10.15 4.75% Mar 30th Easterns 2019 Men
28 Northeastern Loss 13-14 -7.28 4.75% Mar 30th Easterns 2019 Men
11 North Carolina State Loss 8-13 -13.23 4.75% Mar 30th Easterns 2019 Men
47 Maryland Win 13-11 4.41 4.75% Mar 30th Easterns 2019 Men
54 Virginia Tech Win 13-12 -2.61 4.75% Mar 31st Easterns 2019 Men
45 California-Santa Barbara Loss 12-13 -12.89 4.75% Mar 31st Easterns 2019 Men
22 Georgia Loss 5-15 -28.03 4.75% Mar 31st Easterns 2019 Men
**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.