College Women's USAU Rankings (NW)

2022-23 Season

Data updated through September 25 at 10:00am EDT

FAQ
Division I // Division III
Rank    Change Team                                                 Record Rating Change Region Conference Div   SoS PDC %
2 British Columbia NW 1 9-2 2548.3 141 Northwest Cascadia DI D-I 2253.76 294.54 0.13
6 Brigham Young NW 2 10-3 2281.72 141 Northwest Big Sky DI D-I 2069.53 212.2 0.1
9 Washington NW 3 5-8 2183.52 141 Northwest Cascadia DI D-I 2154.22 29.3 0.01
11 Oregon NW 4 13-8 2096.82 141 Northwest Cascadia DI D-I 1986.86 109.96 0.06
15 1 Victoria NW 5 5-7 1852.64 141 Northwest Northwest DI D-I 1943.82 -91.17 -0.05
20 Western Washington 3-8 1780.43 141 Northwest Cascadia DI D-I 2107.39 -326.96 -0.16
34 1 Portland 13-1 1632.44 142 Northwest Northwest DIII D-III 1264.07 368.37 0.29
43 Whitman 9-1 1499 141 Northwest Northwest DIII D-III 1190.37 308.62 0.26
- Montana State 4-0 1477.14 142 Northwest Big Sky DI D-I 1018.98 458.16 0.45
74 2 Utah 4-21 1224.4 141 Northwest Big Sky DI D-I 1530.32 -305.92 -0.2
78 2 Lewis & Clark 7-5 1178.49 142 Northwest Northwest DIII D-III 1035.7 142.79 0.14
81 3 Oregon State 4-4 1173.04 142 Northwest Cascadia DI D-I 1217.01 -43.97 -0.04
92 2 Seattle 3-2 1054.32 143 Northwest Northwest DIII D-III 951.68 102.64 0.11
126 4 Puget Sound 2-3 807.54 142 Northwest Northwest DIII D-III 850.05 -42.52 -0.05
- Montana 0-3 711.01 142 Northwest Big Sky DI D-I 1311.01 -600 -0.46
141 1 Portland-B 2-3 675.14 143 Northwest Northwest DIII Dev 761.57 -86.43 -0.11
163 2 Washington-B 2-4 492.23 143 Northwest Cascadia DI Dev 787.32 -295.08 -0.37
192 2 Pacific Lutheran 1-10 224.56 144 Northwest Northwest DIII D-III 538.85 -314.28 -0.58

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.