Club Men's USAU Rankings (SC)

2017-18 Season

Data Updated Through October 24th at 10:30pm PST

FAQ
Note
Rank Change Team Record Rating Change Region Conference SoS Contrib Score Contrib Score % of Sos
10 1 Doublewide SC 1 12-10 1812.48 15 South Central Texas 1810.66 1.82 0
13 3 Johnny Bravo SC 2 16-13 1776.46 33 South Central Rocky Mountain 1765.5 10.96 0.01
24 1 Inception 24-6 1421.34 18 South Central Rocky Mountain 1175.1 246.23 0.21
35 Nitro 19-6 1302.25 30 South Central Texas 1151.5 150.75 0.13
43 Clutch 29-4 1254.73 25 South Central Texas 984.48 270.25 0.27
69 1 Gamble 28-11 1033.45 28 South Central Texas 837.63 195.82 0.23
79 Papa Bear 23-10 959.27 28 South Central Texas 803.91 155.36 0.19
80 ISO Atmo 16-16 957.83 27 South Central Rocky Mountain 930.08 27.75 0.03
82 Riverside 21-13 944.4 28 South Central Texas 798.08 146.32 0.18
83 2 Supercell 18-9 940.63 25 South Central Ozarks 865.58 75.05 0.09
84 Gaucho 21-12 939.29 27 South Central Texas 816.12 123.17 0.15
92 1 Choice City Hops 15-17 887.99 27 South Central Rocky Mountain 948.09 -60.1 -0.06
110 3 Dreadnought 11-13 769.38 29 South Central Ozarks 696.26 73.12 0.11
129 Prime 12-18 644.69 29 South Central Texas 736.05 -91.36 -0.12
130 1 Syndicate 8-18 630.98 29 South Central Rocky Mountain 747.31 -116.33 -0.16
141 DUPlex 7-14 517.02 28 South Central Texas 668.45 -151.43 -0.23
143 Foxtrot 7-14 495.5 28 South Central Texas 571.31 -75.81 -0.13
147 DUCS 8-23 411.7 28 South Central Texas 667.82 -256.12 -0.38
150 The Bayou Boys 6-19 341.25 28 South Central Texas 495.53 -154.28 -0.31
151 1 Riverside Messengers-B 5-15 335.77 28 South Central Texas 551.79 -216.02 -0.39
153 1 Rawhide 2-18 308.14 29 South Central Ozarks 701.83 -393.69 -0.56

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.