() #193 Midnight Meat Train (6-13)

505.08 (4)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
31 Black Market I** Loss 2-13 0 5 0% Ignored (Why) Jul 6th Motown Throwdown 2019
208 Red Imp.ala Win 13-6 28.2 4 5.33% Counts (Why) Jul 6th Motown Throwdown 2019
136 Dynasty Loss 7-13 -10.56 4 5.33% Counts Jul 6th Motown Throwdown 2019
146 Babe Loss 9-13 -5.99 4 5.33% Counts Jul 7th Motown Throwdown 2019
235 Buffalo Open Win 13-5 5.93 3 5.33% Counts (Why) Jul 7th Motown Throwdown 2019
200 NEO Win 13-7 28.64 3 5.33% Counts (Why) Jul 7th Motown Throwdown 2019
207 BlackER Market X Win 11-8 15.13 4 5.33% Counts Jul 7th Motown Throwdown 2019
61 Battery** Loss 1-13 0 3 0% Ignored (Why) Aug 3rd Heavyweights 2019
103 Imperial Loss 5-13 -5.12 4 6.72% Counts (Why) Aug 3rd Heavyweights 2019
238 Kettering Win 13-5 1.96 4 6.72% Counts (Why) Aug 3rd Heavyweights 2019
178 Milwaukee Revival Loss 9-13 -22.66 4 6.72% Counts Aug 4th Heavyweights 2019
97 THE BODY Loss 6-13 -3.99 5 6.72% Counts (Why) Aug 4th Heavyweights 2019
156 Ditto A Loss 9-13 -12.82 5 6.72% Counts Aug 4th Heavyweights 2019
228 Flying Dutchmen Win 11-5 28.37 4 8.23% Counts (Why) Sep 7th East Plains Mens Club Sectional Championship 2019
200 NEO Loss 9-11 -29.4 3 8.97% Counts Sep 7th East Plains Mens Club Sectional Championship 2019
20 CLE Smokestack** Loss 2-11 0 8 0% Ignored (Why) Sep 7th East Plains Mens Club Sectional Championship 2019
133 Kentucky Flying Circus Loss 8-11 1.4 5 8.97% Counts Sep 7th East Plains Mens Club Sectional Championship 2019
84 Black Lung** Loss 2-11 0 6 0% Ignored (Why) Sep 8th East Plains Mens Club Sectional Championship 2019
135 Enigma Loss 4-11 -20.56 4 8.23% Counts (Why) Sep 8th East Plains Mens Club Sectional Championship 2019
**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.