College Men's USAU Rankings (ME)

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 %
83 3 Rutgers ME 1 10-12 1432.97 2 Metro East Metro NY DI D-I 1435.03 -2.06 0
101 14 Connecticut 9-11 1356.24 79 Metro East Hudson Valley DI D-I 1391.05 -34.82 -0.03
122 23 Yale 15-4 1279.52 82 Metro East Hudson Valley DI D-I 1014.61 264.91 0.26
129 20 Marist 9-1 1271.8 32 Metro East Hudson Valley DIII D-III 926.56 345.24 0.37
141 Wesleyan 3-2 1215.25 Metro East Hudson Valley DIII D-III 1046.66 168.59 0.16
142 5 Princeton 7-6 1209.71 16 Metro East Metro NY DI D-I 1163.59 46.11 0.04
149 1 SUNY-Stony Brook 11-3 1179.21 50 Metro East Metro NY DI D-I 934.98 244.23 0.26
150 12 Cornell 4-11 1178.08 2 Metro East Western NY DI D-I 1415.66 -237.57 -0.17
151 19 SUNY-Binghamton 11-9 1162.14 42 Metro East Western NY DI D-I 1132.96 29.19 0.03
153 23 SUNY-Albany 6-4 1151.01 109 Metro East Hudson Valley DI D-I 969.14 181.88 0.19
154 27 Syracuse 9-4 1150.57 84 Metro East Western NY DI D-I 982.21 168.36 0.17
163 52 SUNY-Geneseo 7-8 1106.58 194 Metro East Western NY DIII D-III 1102.05 4.53 0
171 19 RIT 8-12 1081.65 45 Metro East Western NY DI D-I 1195.39 -113.74 -0.1
178 15 Army 7-8 1059.73 21 Metro East Hudson Valley DIII D-III 1051.54 8.18 0.01
187 40 NYU 7-6 1030.6 110 Metro East Metro NY DI D-I 964.74 65.86 0.07
193 1 Colgate 8-5 1011.84 19 Metro East Western NY DIII D-III 1026.15 -14.32 -0.01
204 24 SUNY-Buffalo 6-11 971.8 58 Metro East Western NY DI D-I 1163.91 -192.11 -0.17
210 26 Rochester 6-8 953.29 65 Metro East Western NY DIII D-III 1019.38 -66.09 -0.06
213 103 Columbia 9-6 948.26 352 Metro East Metro NY DI D-I 962.52 -14.26 -0.01
214 Hartford 4-2 938.67 Metro East Hudson Valley DIII D-III 889.7 48.97 0.06
223 16 Rensselaer Polytech 5-13 916.61 24 Metro East Hudson Valley DIII D-III 1016.57 -99.96 -0.1
225 11 SUNY-Oneonta 8-4 916.54 18 Metro East Western NY DIII D-III 929.69 -13.15 -0.01
242 45 Rowan 4-10 886.46 83 Metro East Metro NY DI D-I 1029.33 -142.87 -0.14
245 9 Stevens Tech 8-4 876.22 37 Metro East Metro NY DIII D-III 918.65 -42.42 -0.05
252 37 SUNY-Cortland 5-6 845.28 50 Metro East Western NY DIII D-III 873.1 -27.82 -0.03
267 1 SUNY-Fredonia 9-6 787.71 81 Metro East Western NY DIII D-III 665.67 122.04 0.18
268 14 Ithaca 5-6 787.4 43 Metro East Western NY DIII D-III 857.14 -69.74 -0.08
281 1 Skidmore 7-6 749.6 119 Metro East Hudson Valley DIII D-III 777.45 -27.85 -0.04
290 33 Hofstra 6-8 708.47 31 Metro East Metro NY DI D-I 876.05 -167.58 -0.19
297 88 Connecticut-B 9-5 694.68 239 Metro East Metro East Dev Dev 629.29 65.39 0.1
335 College of New Jersey 3-8 541.21 278 Metro East Metro NY DIII D-III 659.37 -118.16 -0.18
337 59 Southern Connecticut State 5-7 534.13 111 Metro East Hudson Valley DI D-I 729.47 -195.34 -0.27
372 43 Rutgers-B 8-8 362.59 39 Metro East Metro East Dev Dev 485.71 -123.12 -0.25
389 42 Cornell-B 5-13 274.9 34 Metro East Metro East Dev Dev 421.41 -146.51 -0.35
396 14 SUNY-Binghamton-B 4-8 251.31 238 Metro East Metro East Dev Dev 244.24 7.07 0.03
397 19 SUNY-Albany-B 3-9 240.49 164 Metro East Metro East Dev Dev 314.14 -73.65 -0.23
412 Fairfield 1-5 151.61 Metro East Hudson Valley DIII D-III 317.24 -165.63 -0.52
413 38 Siena 5-8 148.57 44 Metro East Hudson Valley DIII D-III 189.19 -40.62 -0.21
426 84 Sacred Heart 1-9 7.92 322 Metro East Hudson Valley DI D-I 370.66 -362.74 -0.98
436 40 Yale-B 2-12 -213.49 194 Metro East Metro East Dev Dev 30.39 -243.89 -8.02
442 56 SUNY Oneonta-B 2-9 -400.84 287 Metro East Metro East Dev Dev -331.86 -68.97 0.21
443 46 Rensselaer Polytech-B 0-5 -445.91 21 Metro East Hudson Valley DIII Dev -146.35 -299.56 2.05

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.