(5) #164 Mishigami (3-3)

768.2 (3)

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# Opponent Result Effect % of Ranking Status Date Event
174 Stackcats Loss 9-11 -60.17 16.89% Counts Aug 3rd Heavyweights 2019
131 Melt Loss 10-13 -25.97 16.89% Counts Aug 3rd Heavyweights 2019
189 Mastodon Loss 8-9 -45.12 15.98% Counts Aug 3rd Heavyweights 2019
171 Mousetrap Win 11-7 84.6 16.44% Counts Aug 4th Heavyweights 2019
180 Jabba Win 13-9 68.04 16.89% Counts Aug 4th Heavyweights 2019
250 Identity Theft Win 13-8 -21.34 16.89% Counts Aug 4th Heavyweights 2019
**Blowout Eligible. Learn more about how this works here.


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.