Wilson Computer Ratings team analysis
Neumann (13-8)

Neumann's opponents in order of rating: 
     Team            Rating        Score  Effect  W- L
   ---------------   ------       ------- ------ -----
   Swarthmore         451.7 LOSS   74-99         12- 9 Division III
   Marymount          450.4 LOSS   57-58         13- 7 Division III
   Marymount          450.4 LOSS   54-58         13- 7 Division III
   DeSales            412.8 LOSS   67-74         13- 9 Division III
   Lehman             383.8 LOSS   47-74         16- 7 Division III
   Marywood           361.4 LOSS   68-78         11-11 Division III
   Pratt              348.1 LOSS   79-84         11-10 Division III
   Immaculata         319.7 LOSS   68-75          4-18 Division III
>> Neumann            385.7 <<                   13- 8 Division III
   Muhlenberg         418.4 WIN    71-61    ++   11-10 Division III
   Gwynedd-Mercy      399.2 WIN    72-68    ++   15- 7 Division III
   Widener            373.1 WIN    93-82    +     7-15 Division III
   PSU-Brandywine     372.4 WIN    74-65    +    14-10 Division III
   Haverford          360.0 WIN    73-59    +     7-14 Division III
   Goucher            354.9 WIN    73-59    +     4-17 Division III
   Centenary (NJ)     344.3 WIN    86-70    +     8-14 Division III
   Immaculata         319.7 WIN    94-78    +     4-18 Division III
   St Elizabeth       309.1 WIN    78-73    +     6-15 Division III
   St Elizabeth       309.1 WIN    80-61    +     6-15 Division III
   PSU-Abington       297.6 WIN    87-77    +     4-21 Division III
   PSU-Schuykill      288.6 WIN    85-65          1- 6 NAIA/NCCAA/USCAA
   PSU-Lehigh         193.2 WIN    75-62    -     0- 4 (null)
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