(1) #241 defunCT (0-17)

-161.42 (0)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
94 Log Jam** Loss 3-14 0 1 0% Ignored (Why) Jul 6th AntlerLock 2019
104 Burly** Loss 4-15 0 1 0% Ignored (Why) Jul 6th AntlerLock 2019
163 One Night Loss 9-14 41.56 1 9.44% Counts Jul 6th AntlerLock 2019
225 Highlight Reel Loss 9-10 28.24 1 9.44% Counts Jul 6th AntlerLock 2019
17 Sprout** Loss 0-15 0 5 0% Ignored (Why) Jul 7th AntlerLock 2019
225 Highlight Reel Loss 7-12 -12.98 1 9.44% Counts Jul 7th AntlerLock 2019
51 Lantern** Loss 1-13 0 1 0% Ignored (Why) Aug 24th The Incident 2019 Age of Ultimatron
121 Genny The Boys** Loss 2-13 0 1 0% Ignored (Why) Aug 24th The Incident 2019 Age of Ultimatron
175 Bomb Squad** Loss 0-13 0 1 0% Ignored (Why) Aug 24th The Incident 2019 Age of Ultimatron
157 Ender's Outcasts** Loss 1-13 0 0 0% Ignored (Why) Aug 24th The Incident 2019 Age of Ultimatron
232 Bees Loss 3-9 -44.34 0 11.7% Counts (Why) Aug 25th The Incident 2019 Age of Ultimatron
206 Sky Hook Loss 4-10 -1.62 0 12.36% Counts (Why) Aug 25th The Incident 2019 Age of Ultimatron
- Festive Salmon Loss 3-13 -9.1 1 15.88% Counts (Why) Sep 7th Metro New York Mens Club Sectional Championship 2019
87 Magma Bears** Loss 2-13 0 2 0% Ignored (Why) Sep 7th Metro New York Mens Club Sectional Championship 2019
53 Colt** Loss 1-13 0 0 0% Ignored (Why) Sep 7th Metro New York Mens Club Sectional Championship 2019
237 Stuyvesant Sticky Fingers Alumni Loss 12-13 -2.65 0 15.88% Counts Sep 8th Metro New York Mens Club Sectional Championship 2019
204 Spring Break '93 Loss 4-15 -1.19 1 15.88% Counts (Why) Sep 8th Metro New York 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.