Wilson Computer Ratings team analysis
Pitt-Bradford (0-22)


Pitt-Bradford's opponents in order of rating:
     Team            Rating        Score  Effect  W- L
   ---------------   ------       ------- ------ -----
   John Carroll       578.7 LOSS   41-112   +    20- 3 Division III
   PSU-Behrend        427.5 LOSS   39-114        18- 5 Division III
   PSU-Behrend        427.5 LOSS   64-94         18- 5 Division III
   Allegheny          388.6 LOSS   37-101        11-12 Division III
   Houghton           385.1 LOSS   40-114        20- 5 Division III
   Houghton           385.1 LOSS   66-103        20- 5 Division III
   La Roche           369.8 LOSS   37-87         14-10 Division III
   La Roche           369.8 LOSS   36-119        14-10 Division III
   PSU-Altoona        363.8 LOSS   51-89         16- 7 Division III
   PSU-Altoona        363.8 LOSS   53-102        16- 7 Division III
   Geneva             358.0 LOSS   27-108         8-16 Division III
   Penn College       339.4 LOSS   34-77         20- 6 Division III
   Alfred U           312.8 LOSS   41-79         11-13 Division III
   Alfred State       304.1 LOSS   50-70         14- 9 Division III
   Alfred State       304.1 LOSS   59-85         14- 9 Division III
   Keuka              292.1 LOSS   50-65          9-14 Division III
   Mt. Aloysius       284.7 LOSS   44-71          9-14 Division III
   Mt. Aloysius       284.7 LOSS   57-80          9-14 Division III
   Carlow             228.3 LOSS   43-72          5-17 Division III
   Carlow             228.3 LOSS   66-90          5-17 Division III
   Hilbert            199.4 LOSS   61-67          3-19 Division III
   Pitt-Greensburg    157.1 LOSS   47-62          1-22 Division III
>> Pitt-Bradford      132.7 <<                    0-22 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