(1) #98 Dallas United: Desperados (14-11)

901.67 (36)

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# Opponent Result Effect % of Ranking Status Date Event
65 Plex Loss 14-15 2.83 3.01% Jun 25th Texas Two Finger 2017
132 Supercell Win 11-9 -0.38 3.01% Jun 25th Texas Two Finger 2017
73 Rougaroux Loss 6-9 -8.85 3.01% Jun 25th Texas Two Finger 2017
30 Mad Men Loss 11-13 13.41 3.73% Jul 22nd Heavyweights 2017
116 KC SmokeStack Loss 10-11 -10.62 3.73% Jul 22nd Heavyweights 2017
- Kettering** Win 15-6 0 0% Ignored Jul 22nd Heavyweights 2017
159 Black Market II Win 15-4 0.25 3.73% Jul 22nd Heavyweights 2017
88 Wisconsin Hops Win 13-12 6.72 3.73% Jul 23rd Heavyweights 2017
97 Climax Loss 10-15 -17.42 3.73% Jul 23rd Heavyweights 2017
68 Imperial Win 15-11 21.86 3.73% Jul 23rd Heavyweights 2017
164 Rawhide Win 13-6 -2.15 4.37% Aug 12th Hootie on the Hill 2017
103 Dreadnought Loss 11-12 -6.24 4.37% Aug 12th Hootie on the Hill 2017
160 Dallas United: Neato Banditos Win 13-5 0.28 4.37% Aug 12th Hootie on the Hill 2017
89 Scythe Loss 10-13 -12.94 4.37% Aug 12th Hootie on the Hill 2017
125 Papa Bear Win 14-13 -3.82 5.41% Sep 9th 2017 Texas Mens Sectionals
168 SA Spares** Win 15-3 0 0% Ignored Sep 9th 2017 Texas Mens Sectionals
160 Dallas United: Neato Banditos Win 15-5 0.35 5.41% Sep 9th 2017 Texas Mens Sectionals
80 Singlewide Win 12-7 35.52 5.41% Sep 9th 2017 Texas Mens Sectionals
65 Plex Loss 10-15 -13.57 5.41% Sep 10th 2017 Texas Mens Sectionals
80 Singlewide Loss 13-15 -6.5 5.41% Sep 10th 2017 Texas Mens Sectionals
131 Premium Win 13-12 -8.72 6.02% Sep 23rd South Central Mens Regionals 2017
125 Papa Bear Win 13-6 26.15 6.02% Sep 23rd South Central Mens Regionals 2017
25 Inception** Loss 5-13 0 0% Ignored Sep 23rd South Central Mens Regionals 2017
112 Riverside Ultimate Win 14-13 2.72 6.02% Sep 23rd South Central Mens Regionals 2017
123 DTH Loss 14-15 -18.81 6.02% Sep 24th South Central 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.