(15) #176 Battery (6-11)

817.3 (143)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
70 OAT Loss 6-14 -0.8 108 4.27% Counts (Why) Jul 15th TCT Select Flight West 2023
87 Ghost Train Loss 7-13 -2.92 5 4.27% Counts Jul 15th TCT Select Flight West 2023
36 Kansas City Smokestack** Loss 4-13 0 68 0% Ignored (Why) Jul 15th TCT Select Flight West 2023
182 Anchor Win 11-10 4.18 54 4.27% Counts Jul 16th TCT Select Flight West 2023
78 Drought Loss 4-15 -1.93 143 4.27% Counts (Why) Jul 16th TCT Select Flight West 2023
188 Sauce Loss 10-14 -32.7 123 6.54% Counts Sep 9th 2023 Mens Nor Cal Sectional Championship
107 Ghost Loss 9-13 -3.78 136 6.54% Counts Sep 9th 2023 Mens Nor Cal Sectional Championship
211 Ursa Win 15-6 25.07 113 6.54% Counts (Why) Sep 9th 2023 Mens Nor Cal Sectional Championship
182 Anchor Win 10-9 6.55 54 6.54% Counts Sep 10th 2023 Mens Nor Cal Sectional Championship
188 Sauce Win 15-6 37.21 123 6.54% Counts (Why) Sep 10th 2023 Mens Nor Cal Sectional Championship
107 Ghost Loss 10-15 -6.24 136 6.54% Counts Sep 10th 2023 Mens Nor Cal Sectional Championship
66 OC Crows Loss 7-14 2.88 18 7.28% Counts Sep 23rd 2023 Southwest Mens Regional Championship
240 Bonsoon Win 15-3 2.64 15 7.28% Counts (Why) Sep 23rd 2023 Southwest Mens Regional Championship
70 OAT Loss 9-15 5.23 108 7.28% Counts Sep 23rd 2023 Southwest Mens Regional Championship
104 Offshore Loss 10-15 -6.18 278 7.28% Counts Sep 24th 2023 Southwest Mens Regional Championship
171 Sonoran Dog Loss 9-13 -32 1 7.28% Counts Sep 24th 2023 Southwest Mens Regional Championship
240 Bonsoon Win 15-7 2.64 15 7.28% Counts (Why) Sep 24th 2023 Southwest Mens Regional Championship
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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.