College Men's USAU Rankings (NW)

2024-25 Season

Data updated through February 19 at 11:00am PST

FAQ
Division I // Division III
Rank    Change Team                                                 Record Rating Change Region Conference Div   SoS PDC %
1 Oregon NW 1 14-0 2000.35 Northwest Cascadia DI D-I 1655.77 344.58 0.21
3 Washington NW 2 10-4 1907.11 Northwest Cascadia DI D-I 1685.08 222.02 0.13
4 Brigham Young NW 3 13-1 1903.19 Northwest Big Sky DI D-I 1478.49 424.69 0.29
13 Oregon State NW 4 10-5 1732.03 Northwest Cascadia DI D-I 1632.29 99.74 0.06
21 British Columbia 3-2 1601.51 Northwest Cascadia DI D-I 1553.53 47.98 0.03
23 Utah 7-6 1574.11 Northwest Big Sky DI D-I 1597.96 -23.85 -0.01
28 Utah Valley 3-2 1491.76 Northwest Big Sky DI D-I 1420.72 71.04 0.05
29 Utah State 4-4 1490.27 Northwest Big Sky DI D-I 1531.77 -41.51 -0.03
30 Lewis & Clark 5-1 1486.72 Northwest Northwest DIII D-III 1141.31 345.41 0.3
33 Victoria 7-7 1439.05 Northwest Cascadia DI D-I 1504.81 -65.76 -0.04
36 Whitman 5-1 1421.49 Northwest Northwest DIII D-III 1113.68 307.81 0.28
47 Western Washington 3-3 1330.3 Northwest Cascadia DI D-I 1408.6 -78.29 -0.06
76 Puget Sound 3-3 1083.3 Northwest Northwest DIII D-III 1047.21 36.09 0.03
108 Washington-B 4-1 836.09 Northwest Cascadia DI Dev 390.37 445.71 1.14
128 Oregon State-B 3-3 638.74 Northwest Cascadia DI Dev 423.74 215 0.51
140 Brigham Young-B 2-3 532.54 Northwest Northwest Dev Dev 557.54 -25 -0.04
143 Reed 1-5 479.08 Northwest Northwest DIII D-III 822.1 -343.01 -0.42
148 Portland 2-4 417.53 Northwest Northwest DIII D-III 672.66 -255.12 -0.38
154 Pacific Lutheran 0-6 359.71 Northwest Northwest DIII D-III 782.82 -423.12 -0.54
173 Portland State 0-6 89.06 Northwest Cascadia DI D-I 689.06 -600 -0.87

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.