(1) #4 Ring of Fire (16-5) SE 1

1993.74 (24)

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# Opponent Result Effect % of Ranking Status Date Event
7 Chicago Machine Win 14-12 3.09 4.11% Aug 3rd 2018 US Open Club Championships
13 Johnny Bravo Win 14-10 7.78 4.11% Aug 3rd 2018 US Open Club Championships
8 Sub Zero Win 12-9 7.78 4.11% Aug 4th 2018 US Open Club Championships
3 PoNY Loss 13-15 -7.57 4.11% Aug 4th 2018 US Open Club Championships
1 Revolver Loss 13-15 -5.5 4.11% Aug 5th 2018 US Open Club Championships
20 Patrol Win 15-11 -3.85 5.09% Sep 1st TCT Pro Championships 2018
7 Chicago Machine Win 15-6 24.19 5.09% Sep 1st TCT Pro Championships 2018
13 Johnny Bravo Win 15-13 -0.17 5.09% Sep 1st TCT Pro Championships 2018
3 PoNY Loss 14-15 -4.69 5.09% Sep 2nd TCT Pro Championships 2018
11 DiG Loss 8-15 -40.82 5.09% Sep 2nd TCT Pro Championships 2018
13 Johnny Bravo Win 15-9 15.99 5.09% Sep 2nd TCT Pro Championships 2018
55 Ironmen** Win 13-4 0 0% Ignored Sep 22nd Southeast Mens Regional Championship 2018
97 Rush Hour** Win 13-2 0 0% Ignored Sep 22nd Southeast Mens Regional Championship 2018
66 Bullet** Win 13-3 0 0% Ignored Sep 22nd Southeast Mens Regional Championship 2018
37 Brickhouse Win 13-6 -6.7 5.97% Sep 22nd Southeast Mens Regional Championship 2018
15 Chain Lightning Win 15-11 5.09 5.97% Sep 23rd Southeast Mens Regional Championship 2018
7 Chicago Machine Win 15-14 -1.9 7.39% Oct 18th USA Ultimate National Championships 2018
15 Chain Lightning Win 15-13 -6.93 7.39% Oct 18th USA Ultimate National Championships 2018
6 Furious George Win 13-12 0.03 7.39% Oct 18th USA Ultimate National Championships 2018
10 Doublewide Win 14-10 17.36 7.39% Oct 19th USA Ultimate National Championships 2018
1 Revolver Loss 14-15 -3.12 7.39% Oct 20th USA Ultimate National Championships 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.