Wilson Computer Ratings team analysis
SUNY-Oswego (18-3)

SUNY-Oswego's opponents in order of rating: 
     Team            Rating        Score  Effect  W- L
   ---------------   ------       ------- ------ -----
   Union (New York)   476.3 LOSS   75-81         17- 4 Division III
   Cortland St.       468.3 LOSS   81-86         17- 4 Division III
   SUNY-Oneonta       405.7 LOSS   77-81         14-10 Division III
>> SUNY-Oswego        458.3 <<                   18- 3 Division III
   Franklin           446.6 WIN    60-51    +    13-10 Division III
   Nazareth           435.5 WIN    77-66    +    16- 6 Division III
   St. Lawrence       407.1 WIN    92-83    +    11-10 Division III
   SUNY-Oneonta       405.7 WIN    83-62    +    14-10 Division III
   Brockport St.      398.9 WIN    92-81    +    11-11 Division III
   SUNY-Plattsburgh   379.8 WIN    74-66    +    11-10 Division III
   SUNY-Plattsburgh   379.8 WIN    84-60    +    11-10 Division III
   SUNY-New Paltz     365.7 WIN    87-58         11-11 Division III
   SUNY-New Paltz     365.7 WIN    90-70         11-11 Division III
   St. Mary's, MD     353.3 WIN    79-55          9-14 Division III
   Morrisville St.    323.6 WIN    91-69    -     8-13 Division III
   Buffalo St.        322.5 WIN    69-56    -     7-13 Division III
   SUNY-Canton        278.8 WIN    85-67    -     4-18 Division III
   SUNY-Canton        278.8 WIN   103-97    -     4-18 Division III
   Fredonia           252.6 WIN    77-66    -     2-18 Division III
   SUNY-Potsdam       232.5 WIN    91-58    --    1-20 Division III
   SUNY-Potsdam       232.5 WIN    90-79    --    1-20 Division III
   Mt. St. Vincent    230.9 WIN   106-66    --    2-19 Division III
Games against teams within about 100 rating points are often the best indicators of a team's actual strength.

"Effect" ranges from "---", a game that caused a large decrease in the team rating, to "+++", a game that produced a large increase in rating.

Note that wins over very weak teams may actually hurt a team's rating (the opposite is true for losses to very good teams).

shopify analytics ecommerce