College Women's USAU Rankings (ME)

2023-24 Season

Data updated through August 25 at 9:00pm EDT

FAQ
Division I // Division III
Rank    Change Team                                                 Record Rating Change Region Conference Div   SoS PDC %
39 2 SUNY-Binghamton ME 1 16-8 1720.35 17 Metro East Western NY DI D-I 1612.48 107.88 0.07
44 8 Yale 17-8 1646.48 52 Metro East Eastern Metro East DI D-I 1498.14 148.35 0.1
57 10 Connecticut 15-9 1529.14 127 Metro East Eastern Metro East DI D-I 1431.25 97.9 0.07
58 Cornell 15-8 1526.29 1 Metro East Eastern Metro East DI D-I 1472.73 53.56 0.04
71 4 Columbia 15-16 1407.82 33 Metro East Eastern Metro East DI D-I 1443.09 -35.27 -0.02
81 12 Wesleyan 15-6 1353.32 81 Metro East Eastern Metro East DIII D-III 1173.27 180.06 0.15
82 16 Rochester 16-6 1344.48 127 Metro East Western NY DIII D-III 1155.94 188.55 0.16
110 5 Rutgers 11-13 1165.12 8 Metro East Eastern Metro East DI D-I 1279.52 -114.4 -0.09
111 24 NYU 11-15 1141.12 230 Metro East Eastern Metro East DI D-I 1329.61 -188.49 -0.14
142 22 Ithaca 8-8 920.19 286 Metro East Western NY DIII D-III 922.79 -2.6 0
144 28 Skidmore 11-12 912.28 363 Metro East Eastern Metro East DIII D-III 890.22 22 0.02
164 12 SUNY-Stony Brook 3-7 806.94 302 Metro East Eastern Metro East DI D-I 963.52 -156.59 -0.16
191 1 Syracuse 5-11 552.54 243 Metro East Western NY DI D-I 652.98 -100.57 -0.15
192 16 Connecticut College 5-9 551.06 446 Metro East Eastern Metro East DIII D-III 699.81 -148.75 -0.21
193 28 SUNY-Geneseo 4-16 538.01 60 Metro East Western NY DIII D-III 800.91 -262.88 -0.33
201 8 Columbia-B 1-9 442.28 143 Metro East Eastern Metro East DI Dev 587.23 -144.96 -0.25
239 16 SUNY-Albany 1-12 -15.01 345 Metro East Eastern Metro East DI D-I 396.2 -411.18 -1.04
244 18 Cornell-B 1-9 -282.78 210 Metro East Western NY DI Dev -15.01 -267.79 17.84

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.