(2) #93 Battery (10-12)

883.89 (25)

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# Opponent Result Effect % of Ranking Status Date Event
81 Sundowners Loss 8-9 -2.42 3.8% Jul 7th 2018 San Diego Slammer
144 Gridlock Loss 7-8 -20.03 3.57% Jul 7th 2018 San Diego Slammer
86 Green River Swordfish Loss 6-11 -20.1 3.8% Jul 7th 2018 San Diego Slammer
- Whiskeyjacks Loss 8-11 -5.3 4.02% Jul 7th 2018 San Diego Slammer
78 Rip City Ultimate Win 12-11 9.09 4.02% Jul 8th 2018 San Diego Slammer
- Carbon Win 15-11 11.96 4.02% Jul 8th 2018 San Diego Slammer
80 ISO Atmo Win 12-11 11.66 5.54% Aug 18th Ski Town Classic 2018
89 The Killjoys Loss 10-13 -18.1 5.54% Aug 18th Ski Town Classic 2018
- NCFO Win 12-11 9.88 5.54% Aug 18th Ski Town Classic 2018
43 Clutch Loss 7-12 -8.77 5.54% Aug 18th Ski Town Classic 2018
92 Choice City Hops Win 12-10 14.19 5.54% Aug 19th Ski Town Classic 2018
43 Clutch Loss 5-13 -13.43 5.54% Aug 19th Ski Town Classic 2018
81 Sundowners Win 12-10 17.69 5.54% Aug 19th Ski Town Classic 2018
- Anchor** Win 12-5 0 0% Ignored Sep 8th Nor Cal Mens Sectional Championship 2018
- Journeymen Win 11-4 11.43 5.96% Sep 8th Nor Cal Mens Sectional Championship 2018
86 Green River Swordfish Loss 7-11 -28.93 6.32% Sep 8th Nor Cal Mens Sectional Championship 2018
19 Guerrilla Loss 9-13 17.05 6.5% Sep 9th Nor Cal Mens Sectional Championship 2018
99 Red Dawn Win 10-5 32.69 5.77% Sep 9th Nor Cal Mens Sectional Championship 2018
- Journeymen Win 12-5 11.99 6.23% Sep 9th Nor Cal Mens Sectional Championship 2018
1 Revolver** Loss 4-15 0 0% Ignored Sep 22nd Southwest Mens Regional Championship 2018
19 Guerrilla** Loss 6-15 0 0% Ignored Sep 22nd Southwest Mens Regional Championship 2018
81 Sundowners Loss 10-15 -30.36 7.23% Sep 22nd Southwest Mens Regional Championship 2018
**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.