(10) #59 Green River Swordfish (13-12)

1151.82 (160)

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# Opponent Result Effect % of Ranking Status Date Event
52 Republic Win 11-8 14.56 3.18% Jul 8th San Diego Slammer 2017
36 Voodoo Loss 3-11 -10.78 3.18% Jul 8th San Diego Slammer 2017
157 Brawl** Win 11-2 0 0% Ignored Jul 8th San Diego Slammer 2017
51 Sundowners Loss 8-11 -9.3 3.18% Jul 8th San Diego Slammer 2017
70 Choice City Hops Win 11-9 5.06 3.18% Jul 8th San Diego Slammer 2017
91 Rip City Ultimate Win 15-13 0.23 3.18% Jul 9th San Diego Slammer 2017
70 Choice City Hops Win 15-9 13.82 3.18% Jul 9th San Diego Slammer 2017
36 Voodoo Loss 8-15 -14.18 4.62% Aug 26th CBR Memorial 2017
78 Ghost Train Win 15-8 20.74 4.62% Aug 26th CBR Memorial 2017
91 Rip City Ultimate Loss 13-15 -20.43 4.62% Aug 26th CBR Memorial 2017
134 Cloverleaf Win 15-9 -1.95 4.62% Aug 27th CBR Memorial 2017
78 Ghost Train Win 15-11 11.84 4.62% Aug 27th CBR Memorial 2017
55 Streetgang Loss 12-15 -12.04 4.62% Aug 27th CBR Memorial 2017
- Ultimate Impact Win 13-6 8.22 5.14% Sep 9th 2017 Nor Cal Mens Sectionals
- Journeymen Win 13-3 12.79 5.14% Sep 9th 2017 Nor Cal Mens Sectionals
18 Guerrilla Loss 10-13 7.99 5.14% Sep 9th 2017 Nor Cal Mens Sectionals
- Gulls Win 13-6 1.13 5.14% Sep 9th 2017 Nor Cal Mens Sectionals
- Sons Win 13-8 6.68 5.14% Sep 10th 2017 Nor Cal Mens Sectionals
- Sons Win 15-9 7.73 5.14% Sep 10th 2017 Nor Cal Mens Sectionals
18 Guerrilla Loss 7-13 -4.45 5.14% Sep 10th 2017 Nor Cal Mens Sectionals
52 Republic Loss 9-15 -26.59 5.72% Sep 23rd Southwest Mens Regionals 2017
1 Revolver** Loss 2-13 0 0% Ignored Sep 23rd Southwest Mens Regionals 2017
16 SoCal Condors** Loss 3-13 0 0% Ignored Sep 23rd Southwest Mens Regionals 2017
51 Sundowners Loss 11-13 -8.86 5.72% Sep 23rd Southwest Mens Regionals 2017
51 Sundowners Loss 14-15 -2.56 5.72% Sep 24th Southwest Mens Regionals 2017
**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.