College Women's USAU Rankings (NW)

2019-20 Season

Data updated through 6:00pm PDT on March 12

FAQ
Division I // Division III
Rank    Change Team                                                 Record Rating Change Region Conference Div   SoS PDC %
5 3 Washington NW 1 10-3 2145.52 52 Northwest Cascadia DI D-I 1980.48 165.05 0.08
16 1 Western Washington NW 2 6-3 1962.17 1 Northwest Cascadia DI D-I 1881 81.16 0.04
17 British Columbia NW 3 3-3 1954.58 Northwest Cascadia DI D-I 1935.1 19.48 0.01
35 Utah 6-8 1574.56 7 Northwest Big Sky DI D-I 1662.76 -88.2 -0.05
36 3 Brigham Young 9-4 1567.15 19 Northwest Big Sky DI D-I 1556.24 10.91 0.01
44 3 Whitman 7-7 1526.67 12 Northwest Big Sky DI D-I 1586.37 -59.7 -0.04
49 12 Puget Sound 10-1 1447.51 111 Northwest Northwest DIII D-III 990.6 456.91 0.46
52 5 Victoria 0-5 1408.07 40 Northwest Cascadia DI D-I 1533.07 -125 -0.08
60 4 Oregon 6-13 1346.76 58 Northwest Cascadia DI D-I 1512.99 -166.23 -0.11
76 18 Portland 8-2 1252.55 100 Northwest Northwest DIII D-III 1008.67 243.88 0.24
114 28 Pacific Lutheran 4-4 1000.51 82 Northwest Northwest DIII D-III 1002.52 -2 0
- Western Washington-B 3-1 878.34 70 Northwest Cascadia DI D-I 623.7 254.64 0.41
133 5 Oregon State 6-7 839.4 79 Northwest Cascadia DI D-I 882.06 -42.66 -0.05
136 3 Montana State University 5-3 823.08 127 Northwest Big Sky DI D-I 666.44 156.63 0.24
- Washington-B 1-3 638.96 88 Northwest Cascadia DI Dev 838.96 -200 -0.24
175 28 Lewis & Clark 0-6 498.88 78 Northwest Northwest DIII D-III 862.03 -363.15 -0.42
176 24 Portland State 1-7 489.22 55 Northwest Cascadia DI D-I 779.96 -290.74 -0.37
188 15 Boise State 3-5 402.66 127 Northwest Big Sky DI D-I 576.5 -173.84 -0.3
197 18 Montana 1-6 299.52 130 Northwest Big Sky DI D-I 632.23 -332.7 -0.53
206 22 Idaho 0-6 213.69 154 Northwest Big Sky DI D-I 498.55 -284.86 -0.57
- Pacific Lutheran-B 0-4 68.84 71 Northwest Northwest DIII D-III 668.84 -600 -0.9

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.