Club Men's USAU Rankings (SC)

2024-25 Season

Data updated through July 14 at 9:00pm EDT

FAQ
Rank    Change Team                                                 Record Rating Change Region Conference SoS PDC %
23 42 Johnny Bravo-Varsity SC 1 2-4 2001.66 904 South Central 2027.34 -25.67 -0.01
27 Doublewide 3-3 1889.68 South Central Texas 1988.22 -98.53 -0.05
48 44 Fungi 7-5 1502.56 207 South Central Rocky Mountain 1437.54 65 0.05
51 49 Alamode 8-4 1484.3 281 South Central Texas 1278.1 206.21 0.16
66 38 Red Lotus 8-4 1249.73 123 South Central Rocky Mountain 1209.54 40.16 0.03
71 21 ISO Atmo 14-5 1209.37 4 South Central Rocky Mountain 1019.78 189.57 0.19
74 52 H.I.P 5-1 1186.31 203 South Central Texas 854.22 332.09 0.39
77 51 Cowtown Cannons 8-5 1143.13 237 South Central Texas 1010.32 132.82 0.13
93 78 Brawl 11-2 1031.28 432 South Central Texas 896.21 135.07 0.15
95 57 Sprawl 5-1 1017.12 251 South Central Texas 855.09 162.04 0.19
- Dreadnought 2-0 860.72 South Central Ozarks 260.73 600 2.3
124 49 BARNSTORM 4-3 780.71 262 South Central Ozarks 609.22 171.49 0.28
125 31 Riverside 7-7 771.07 100 South Central Texas 682.84 88.23 0.13
139 42 Texas Duffy 2-5 608.3 240 South Central Texas 847.54 -239.23 -0.28
144 19 Carbon 4-8 589.45 118 South Central Rocky Mountain 715.73 -127.44 -0.18
160 40 Forge 4-8 426.97 296 South Central Texas 424.16 2.82 0.01
- Rawhide 1-1 337 South Central Ozarks 522.59 -185.58 -0.36
173 23 Dallas Delinquents 2-10 212.19 163 South Central Texas 455.55 -243.36 -0.53
174 San Antonio Warhawks 2-3 201.03 South Central Texas 354.59 -153.56 -0.43
175 26 Supercell 1-7 184.45 228 South Central Ozarks 556.84 -372.38 -0.67

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.