College Women's USAU Rankings (NW)

2022-23 Season

Data updated through March 27 at 5:00pm EDT (probabilistic bids also now updated for 22-23 season)

FAQ
Division I // Division III
Rank    Change Team                                                 Record Rating Change Region Conference Div   SoS PDC %
2 British Columbia NW 1 9-2 2422.1 119 Northwest Cascadia DI D-I 2127.56 294.54 0.14
6 1 Brigham Young NW 2 10-3 2155.72 9 Northwest Big Sky DI D-I 1943.52 212.2 0.11
9 Washington NW 3 5-8 2057.61 26 Northwest Cascadia DI D-I 2028.31 29.3 0.01
11 Oregon NW 4 13-8 1969.91 8 Northwest Cascadia DI D-I 1859.95 109.96 0.06
17 4 Victoria NW 5 5-7 1724.36 108 Northwest Northwest DI D-I 1815.53 -91.17 -0.05
20 7 Western Washington 3-8 1653.97 126 Northwest Cascadia DI D-I 1980.93 -326.96 -0.17
33 1 Portland 12-1 1499.88 37 Northwest Northwest DIII D-III 1094.42 405.46 0.37
48 9 Whitman 9-0 1345.46 26 Northwest Northwest DIII D-III 902.51 442.95 0.49
- Montana State 4-0 1336.92 37 Northwest Big Sky DI D-I 878.76 458.16 0.52
71 10 Utah 4-20 1085.46 42 Northwest Big Sky DI D-I 1388 -302.54 -0.22
74 10 Lewis & Clark 7-5 1045.81 43 Northwest Northwest DIII D-III 903.02 142.79 0.16
76 10 Oregon State 4-4 1035.52 37 Northwest Cascadia DI D-I 1079.49 -43.97 -0.04
98 5 Seattle 3-2 920.82 38 Northwest Northwest DIII D-III 818.18 102.64 0.13
127 2 Puget Sound 2-3 673.5 40 Northwest Northwest DIII D-III 716.02 -42.52 -0.06
- Montana 0-3 572.26 37 Northwest Big Sky DI D-I 1172.26 -600 -0.51
146 4 Portland-B 2-3 541.8 40 Northwest Northwest DIII Dev 628.23 -86.43 -0.14
161 Washington-B 2-4 359.18 39 Northwest Cascadia DI Dev 654.26 -295.08 -0.45
191 13 Pacific Lutheran 1-10 93.38 35 Northwest Northwest DIII D-III 407.66 -314.28 -0.77

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.