College Women's USAU Rankings (NC)

2017-18 Season

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

FAQ
Division I // Division III
Note
Rank Change Team Record Rating Change Region Conference Div   SoS Contrib Score Contrib Score % of Sos
12 Carleton College NC 1 11-7 2421.97 426 North Central Western North Central DI 2337.26 84.72 0.04
22 1 Minnesota 9-5 2228.83 419 North Central Western North Central DI 2132.88 95.96 0.04
42 6 Wisconsin 7-9 2003.7 419 North Central Lake Superior DI 2065.07 -61.36 -0.03
55 5 Iowa State 8-13 1846.46 417 North Central Western North Central DI 1873.04 -26.58 -0.01
89 7 Iowa 4-8 1570.48 413 North Central Western North Central DI 1782.64 -212.15 -0.12
96 3 St Olaf 5-6 1526.06 447 North Central North Central DIII 1586.88 -60.8 -0.04
106 3 St Benedict 6-1 1471.97 480 North Central North Central DIII 1196.72 275.05 0.23
108 2 Wisconsin-Eau Claire 8-5 1447.12 431 North Central Lake Superior DI 1353.44 93.69 0.07
114 27 Nebraska 8-3 1406.76 276 North Central Western North Central DI 1165.78 241 0.21
124 10 Carleton College-Eclipse 11-9 1352.52 415 North Central North Central DIII 1317.45 35.12 0.03
155 1 Minnesota-Duluth 4-3 1148.05 468 North Central Western North Central DI 1165.36 -16.19 -0.01
162 14 Winona State 3-4 1120.25 639 North Central Western North Central DI 1325.43 -205.09 -0.15
168 9 Luther 5-4 1059.36 440 North Central North Central DIII 1029 30.44 0.03
191 12 Wisconsin-Milwaukee 6-5 932.96 456 North Central Lake Superior DI 858.47 74.45 0.09
198 11 Marquette 5-7 908.8 511 North Central Lake Superior DI 1008.8 -99.47 -0.1
225 8 Wisconsin-B 4-8 693.57 513 North Central Lake Superior DI 842.82 -149.43 -0.18
236 7 Drake 3-9 579.42 497 North Central North Central DIII 720.47 -140.26 -0.19

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.