Wilson Computer Ratings team analysis
Union (New York) (17-4)


Union (New York)'s opponents in order of rating:
     Team            Rating        Score  Effect  W- L
   ---------------   ------       ------- ------ -----
   Trinity Coll (CT)  551.6 LOSS   56-97         19- 2 Division III
   Vassar             454.7 LOSS   74-76         15- 7 Division III
   Rensselaer         453.9 LOSS   50-56         16- 5 Division III
   Middlebury         419.0 LOSS   72-73          8-14 Division III
>> Union (New York)   476.3 <<                   17- 4 Division III
   SUNY-Oswego        458.3 WIN    81-75    +    18- 3 Division III
   Rensselaer         453.9 WIN    76-59    +    16- 5 Division III
   Stevens Tech       442.9 WIN    79-66    +    14- 7 Division III
   Polytechnic        423.0 WIN    84-55    +    17- 5 Division III
   Hobart             407.4 WIN    90-72    +    11-10 Division III
   Hobart             407.4 WIN    75-68    +    11-10 Division III
   St. Lawrence       407.1 WIN    72-68    +    11-10 Division III
   Skidmore           400.9 WIN    81-73    +    10-11 Division III
   Skidmore           400.9 WIN    80-62    +    10-11 Division III
   Ithaca             389.9 WIN    81-73    +     8-13 Division III
   Ithaca             389.9 WIN    86-79    +     8-13 Division III
   SUNY-Plattsburgh   379.8 WIN    80-73         11-10 Division III
   Clarkson           373.1 WIN    85-70         11-10 Division III
   Rochester Tech     348.5 WIN    74-63    -     5-18 Division III
   Rochester Tech     348.5 WIN    94-90    -     5-18 Division III
   Manhattanville     345.8 WIN    88-66    -    10-11 Division III
   Bard               259.0 WIN    89-60    -     1-20 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