(5) #80 Singlewide (19-3)

1002.17 (85)

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# Opponent Result Effect % of Ranking Status Date Event
125 Papa Bear Win 13-12 -6.63 3.82% Jun 25th Texas Two Finger 2017
156 Deaf Fruit** Win 13-3 0 0% Ignored Jun 25th Texas Two Finger 2017
- AndyGator Win 13-10 -11.33 3.82% Jun 25th Texas Two Finger 2017
131 Premium Win 12-7 8.33 4.98% Jul 29th PBJ 2017
168 SA Spares** Win 13-3 0 0% Ignored Jul 29th PBJ 2017
171 The Bucket Brigade** Win 13-3 0 0% Ignored Jul 29th PBJ 2017
163 Spring Creek Ascension** Win 13-3 0 0% Ignored Jul 29th PBJ 2017
125 Papa Bear Win 13-6 16.13 4.98% Jul 30th PBJ 2017
73 Rougaroux Win 8-7 8.27 4.98% Jul 30th PBJ 2017
- Texas Two Step Win 10-8 9.04 4.98% Jul 30th PBJ 2017
98 Dallas United: Desperados Loss 7-12 -45.73 6.86% Sep 9th 2017 Texas Mens Sectionals
141 Fénix Ultimate Win 15-6 10.12 6.86% Sep 9th 2017 Texas Mens Sectionals
- Flash Flood** Win 15-2 0 0% Ignored Sep 9th 2017 Texas Mens Sectionals
163 Spring Creek Ascension** Win 15-5 0 0% Ignored Sep 9th 2017 Texas Mens Sectionals
131 Premium Win 15-5 17.55 6.86% Sep 10th 2017 Texas Mens Sectionals
98 Dallas United: Desperados Win 15-13 8.37 6.86% Sep 10th 2017 Texas Mens Sectionals
112 Riverside Ultimate Win 15-10 19.92 6.86% Sep 10th 2017 Texas Mens Sectionals
65 Plex Loss 10-13 -17.54 7.63% Sep 23rd South Central Mens Regionals 2017
125 Papa Bear Win 15-12 0.68 7.63% Sep 23rd South Central Mens Regionals 2017
141 Fénix Ultimate Win 13-8 2.77 7.63% Sep 23rd South Central Mens Regionals 2017
112 Riverside Ultimate Win 13-8 25.87 7.63% Sep 23rd South Central Mens Regionals 2017
103 Dreadnought Loss 10-15 -46.72 7.63% 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.