() #98 Kentucky (3-4)

1416.76 (42)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
115 Michigan State Win 11-6 80.13 180 15.39% Counts (Why) Apr 1st Huck Finn1
92 Missouri S&T Win 5-3 50.95 51 10.56% Counts (Why) Apr 1st Huck Finn1
64 St. Olaf Loss 3-8 -65.05 28 12.66% Counts (Why) Apr 1st Huck Finn1
112 Illinois Win 7-6 3.76 10 13.46% Counts Apr 1st Huck Finn1
59 Cincinnati Loss 8-9 6.72 70 15.39% Counts Apr 2nd Huck Finn1
94 Saint Louis Loss 10-11 -22.74 8 16.27% Counts Apr 2nd Huck Finn1
68 Wisconsin-Milwaukee Loss 9-13 -55.47 2 16.27% Counts Apr 2nd Huck Finn1
**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.