College Women's USAU Rankings (OV)

2024-25 Season

Data updated through March 31 at 3:45pm EDT

FAQ
Division I // Division III
Rank    Change Team                                                 Record Rating Change Region Conference Div   SoS PDC %
21 4 Ohio State OV 1 13-6 2266.62 145 Ohio Valley Ohio DI D-I 2176.2 90.44 0.04
23 1 Pennsylvania 9-8 2245.85 99 Ohio Valley Pennsylvania DI D-I 2145.62 100.24 0.05
31 2 Pittsburgh 9-7 2014.51 65 Ohio Valley Pennsylvania DI D-I 1942.85 71.68 0.04
34 Ohio 11-2 1958.56 23 Ohio Valley Ohio DI D-I 1503.06 455.44 0.3
40 16 Haverford/Bryn Mawr 13-7 1843.37 181 Ohio Valley Pennsylvania DIII D-III 1812.66 30.73 0.02
42 14 Kenyon 12-0 1837.77 145 Ohio Valley Ohio DIII D-III 1237.79 600 0.48
77 2 Penn State 8-10 1497.26 100 Ohio Valley Pennsylvania DI D-I 1627.61 -130.34 -0.08
80 70 Carnegie Mellon 5-8 1475.55 612 Ohio Valley Pennsylvania DI D-I 1594.33 -118.75 -0.07
82 6 Case Western Reserve 6-6 1445.74 17 Ohio Valley Ohio DI D-I 1303.38 142.37 0.11
102 9 Lehigh 9-12 1276.26 75 Ohio Valley Pennsylvania DIII D-III 1290.63 -14.41 -0.01
106 16 Temple 3-8 1262.45 148 Ohio Valley Pennsylvania DI D-I 1543.43 -280.96 -0.18
112 17 West Chester 1-9 1213.67 93 Ohio Valley Pennsylvania DI D-I 1602.87 -389.17 -0.24
114 22 Cedarville 8-4 1211.01 108 Ohio Valley Ohio DIII D-III 1114.18 96.92 0.09
116 28 Cincinnati 9-4 1195.23 153 Ohio Valley Ohio DI D-I 1099.27 95.98 0.09
117 15 Swarthmore 8-5 1195.07 166 Ohio Valley Pennsylvania DIII D-III 1104.33 90.74 0.08
124 16 Xavier 8-5 1134.5 88 Ohio Valley Ohio DIII D-III 1065.91 68.57 0.06
165 8 Oberlin 1-8 837.33 10 Ohio Valley Ohio DIII D-III 1153.84 -316.48 -0.27
196 27 Dayton 4-8 593.78 167 Ohio Valley Ohio DI D-I 712.99 -119.2 -0.17
209 8 Miami (Ohio) 2-4 501.43 72 Ohio Valley Ohio DI D-I 552.9 -51.44 -0.09
213 14 Dickinson 3-9 476.19 29 Ohio Valley Pennsylvania DIII D-III 595.75 -119.56 -0.2
227 14 Pennsylvania-B 0-7 323.52 77 Ohio Valley Ohio Valley Dev Dev 923.51 -600 -0.65

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.