Club Men USAU Rankings

2017 Season

Updated August 16, 2017 at 2:00pm PST

FAQ
Rank Change Team Record Rating Change Region SoS Contrib Score Contrib Score % of Sos
7 Johnny Bravo 6-5 2014.44 4 South Central 2051.79 -37.31 -0.02
12 1 Doublewide 4-3 1915.71 3 South Central 1956.6 -40.86 -0.02
27 2 Inception 10-3 1589.15 5 South Central 1397.27 191.88 0.14
56 4 Singlewide 10-0 1201.38 66 South Central 866 335.37 0.39
65 1 Johnny Encore 3-2 1139.48 3 South Central 1046.8 92.69 0.09
70 1 Choice City Hops 7-6 1104 0 South Central 974.79 129.25 0.13
78 10 Riverside Ultimate 6-1 1039.43 74 South Central 695.49 343.92 0.49
92 16 Plex 6-9 996.06 60 South Central 1116.01 -119.96 -0.11
101 20 Papa Bear 7-3 939.18 85 South Central 727.13 212.05 0.29
104 5 Dallas United: Desperados 7-7 899.94 11 South Central 828.48 71.45 0.09
118 18 Dreadnought 4-6 794.56 128 South Central 852.73 -58.18 -0.07
123 2 ISO Atmo 4-9 757.37 1 South Central 911.52 -154.1 -0.17
127 4 Syndicate 3-3 744.01 2 South Central 908.95 -164.92 -0.18
131 13 Supercell 9-5 705.87 74 South Central 606.46 99.41 0.16
133 13 Premium 4-4 697.11 63 South Central 731.52 -34.42 -0.05
134 12 DTH 4-4 694.84 59 South Central 749.33 -54.5 -0.07
154 8 Spring Creek Ascension 6-5 498.4 64 South Central 540.7 -42.31 -0.08
160 13 Dallas United: Outlaws 5-10 458.4 94 South Central 559.06 -100.66 -0.18
167 12 Deaf Fruit 5-5 388.99 93 South Central 454.61 -65.62 -0.14
168 6 Dallas United: Neato Banditos 5-10 358.93 64 South Central 508.56 -149.64 -0.29
174 21 Rawhide 3-11 338.57 153 South Central 522.27 -183.71 -0.35
185 11 SA Spares 2-8 143.01 70 South Central 374.23 -231.23 -0.62
191 4 The Bucket Brigade 1-9 -97.24 17 South Central 293.97 -391.22 -1.33
192 7 Riverside Messengers-B 1-6 -109.07 71 South Central 170.26 -279.33 -1.64

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.