College Men's USAU Rankings (GL)

2018-19 Season

Data Updated Through April 1st at 10:30am PST. Note that the USAU Preliminary Rankings released Tuesday morning differ slightly, likely due to recently applied game exclusions due to roster validity (unknown until today)

FAQ
Division I // Division III
Rank    Change Team                                                 Record Rating Change Region Conference Div   SoS PDC %
18 3 Michigan GL 1 18-3 1908.77 37 Great Lakes Michigan DI D-I 1615.71 293.06 0.18
37 7 Illinois 14-11 1720.39 34 Great Lakes Illinois DI D-I 1668.14 52.25 0.03
38 5 Purdue 14-6 1707.04 12 Great Lakes East Plains DI D-I 1473.63 233.41 0.16
49 5 Northwestern 7-16 1637.69 39 Great Lakes Illinois DI D-I 1838.78 -201.09 -0.11
52 4 Notre Dame 12-7 1626.67 18 Great Lakes East Plains DI D-I 1509.96 116.71 0.08
53 21 Indiana 19-2 1626.62 123 Great Lakes East Plains DI D-I 1269.76 356.86 0.28
97 26 Grand Valley State 12-2 1363.8 109 Great Lakes Michigan DI D-I 1012.43 351.37 0.35
106 23 Illinois State 5-16 1327.34 119 Great Lakes Illinois DI D-I 1564.06 -236.72 -0.15
131 25 Chicago 5-10 1266.49 59 Great Lakes Illinois DI D-I 1326.29 -59.79 -0.05
132 13 Kentucky 6-8 1251.16 18 Great Lakes East Plains DI D-I 1366.5 -115.34 -0.08
148 26 Michigan-B 15-6 1181.95 74 Great Lakes Great Lakes Dev Dev 1057.34 124.61 0.12
189 1 Bradley 4-1 1025.91 19 Great Lakes Illinois DIII D-III 611.32 414.59 0.68
198 48 Valparaiso 7-4 998.06 215 Great Lakes East Plains DIII D-III 825.18 172.88 0.21
203 28 Wheaton (Illinois) 7-4 972.12 121 Great Lakes Illinois DIII D-III 893.79 78.33 0.09
215 Butler 5-0 928.33 110 Great Lakes East Plains DIII D-III 404.8 523.53 1.29
219 76 Michigan State 2-9 922.83 242 Great Lakes Michigan DI D-I 1216.13 -293.3 -0.24
224 42 DePaul 5-6 916.56 106 Great Lakes Illinois DI D-I 996.14 -79.58 -0.08
231 3 Knox 8-2 910.52 53 Great Lakes Illinois DIII D-III 664.31 246.21 0.37
237 33 Loyola-Chicago 5-8 899.86 204 Great Lakes Illinois DI D-I 936.95 -37.09 -0.04
258 9 Olivet Nazarene 7-4 830.05 122 Great Lakes Illinois DIII D-III 778.17 51.88 0.07
269 26 Ball State 6-7 785.46 13 Great Lakes East Plains DI D-I 757.36 28.1 0.04
275 9 Illinois-B 9-7 770.93 150 Great Lakes Great Lakes Dev Dev 761.05 9.88 0.01
276 9 North Park 8-8 769.64 149 Great Lakes Illinois DIII D-III 786.74 -17.1 -0.02
302 Rose-Hulman 3-6 652.23 35 Great Lakes East Plains DIII D-III 828.57 -176.33 -0.21
309 47 Illinois State-B 10-10 633.22 87 Great Lakes Illinois DI D-I 594.32 38.9 0.07
316 45 Purdue-B 8-6 599.8 395 Great Lakes Great Lakes Dev Dev 477.18 122.63 0.26
327 24 Indiana-B 6-6 575.63 47 Great Lakes Great Lakes Dev Dev 646.17 -70.54 -0.11
329 22 Northern Illinois 4-10 561.93 59 Great Lakes Illinois DI D-I 774.51 -212.59 -0.27
348 2 Western Michigan 3-8 487.57 176 Great Lakes Michigan DI D-I 679.48 -191.91 -0.28
351 18 Southern Illinois-Edwardsville 5-7 476.79 101 Great Lakes Illinois DI ? 583.77 -106.98 -0.18
355 36 Northwestern-B 6-13 458.9 28 Great Lakes Great Lakes Dev Dev 585.84 -126.93 -0.22
358 37 Trine 1-5 447.9 23 Great Lakes East Plains DIII D-III 775.02 -327.12 -0.42
360 8 Illinois-Chicago 5-8 431.2 147 Great Lakes Illinois DI D-I 437.18 -5.98 -0.01
369 4 Notre Dame-B 5-6 381.85 191 Great Lakes Great Lakes Dev Dev 366.43 15.43 0.04
370 50 Kentucky-B 4-8 370.93 59 Great Lakes Great Lakes Dev D-I 477.08 -106.15 -0.22
376 18 Indiana Wesleyan 2-9 353.42 107 Great Lakes East Plains DIII D-III 658.78 -305.35 -0.46
386 75 Southern Indiana 1-10 287.49 195 Great Lakes East Plains DI D-I 660.62 -373.13 -0.56
411 45 Eastern Illinois 1-12 159.97 30 Great Lakes Illinois DIII D-III 526.52 -366.55 -0.7
- Kettering 0-3 -48.41 20 Great Lakes Michigan DIII D-III 326.71 -375.12 -1.15

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.