(1) #132 Supercell (14-10)

640.16 (37)

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# Opponent Result Effect % of Ranking Status Date Event
65 Plex Loss 7-13 -2.43 2.96% Jun 25th Texas Two Finger 2017
98 Dallas United: Desperados Loss 9-11 0.37 2.96% Jun 25th Texas Two Finger 2017
73 Rougaroux Win 11-10 15.83 2.96% Jun 25th Texas Two Finger 2017
125 Papa Bear Loss 10-12 -6.76 3.86% Jul 29th PBJ 2017
160 Dallas United: Neato Banditos Win 11-6 8.6 3.86% Jul 29th PBJ 2017
150 Dallas United: Outlaws Win 10-9 -3.99 3.86% Jul 29th PBJ 2017
170 Riverside Messengers-B** Win 11-2 0 0% Ignored Jul 29th PBJ 2017
131 Premium Loss 9-11 -9.99 3.86% Jul 30th PBJ 2017
150 Dallas United: Outlaws Win 9-7 2.2 3.86% Jul 30th PBJ 2017
156 Deaf Fruit Win 9-6 5.26 3.86% Jul 30th PBJ 2017
84 Memphis Belle Loss 10-13 0.4 4.29% Aug 12th Hootie on the Hill 2017
150 Dallas United: Outlaws Win 12-11 -4.46 4.29% Aug 12th Hootie on the Hill 2017
116 KC SmokeStack Win 13-9 23.81 4.29% Aug 12th Hootie on the Hill 2017
171 The Bucket Brigade Win 13-6 -1.13 4.29% Aug 12th Hootie on the Hill 2017
164 Rawhide Win 11-10 -14.61 5.31% Sep 9th 2017 Ozarks Mens Sectionals
171 The Bucket Brigade Win 11-7 -8.89 5.31% Sep 9th 2017 Ozarks Mens Sectionals
103 Dreadnought Loss 9-11 0.05 5.31% Sep 9th 2017 Ozarks Mens Sectionals
103 Dreadnought Win 13-12 21.05 5.31% Sep 9th 2017 Ozarks Mens Sectionals
126 ISO Atmo Win 13-8 33.67 5.91% Sep 23rd South Central Mens Regionals 2017
170 Riverside Messengers-B Win 13-9 -12.38 5.91% Sep 23rd South Central Mens Regionals 2017
12 Doublewide** Loss 5-13 0 0% Ignored Sep 23rd South Central Mens Regionals 2017
123 DTH Loss 10-15 -22.67 5.91% Sep 23rd South Central Mens Regionals 2017
126 ISO Atmo Loss 11-15 -21.45 5.91% Sep 24th South Central Mens Regionals 2017
112 Riverside Ultimate Loss 13-15 -2.21 5.91% 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.