Wilson Computer Ratings team analysis
Lander (8-14)


Lander's opponents in order of rating:
     Team            Rating        Score  Effect  W- L
   ---------------   ------       ------- ------ -----
   Lenoir-Rhyne       579.2 LOSS   61-79         20- 4 Division II
   Columbus State     575.3 LOSS   61-77         21- 3 Division II
   Columbus State     575.3 LOSS   56-70         21- 3 Division II
   Carson-Newman      546.4 LOSS   59-72         16- 8 Division II
   North Georgia      534.5 LOSS   61-72         16-10 Division II
   North Georgia      534.5 LOSS   57-79         16-10 Division II
   Beaufort SC        530.2 LOSS   60-62         16- 8 Division II
   Virginia St.       525.8 LOSS   54-67         17- 6 Division II
   Augusta            524.4 LOSS   39-71         17- 8 Division II
   Newberry           490.0 LOSS   59-60         13-13 Division II
   Clayton State      484.0 LOSS   59-66          9-14 Division II
   Georgia SW         478.2 LOSS   53-64         10-14 Division II
   Allen              475.3 LOSS   73-75         12- 8 NAIA/NCCAA/USCAA
   Georgia C&S        449.4 LOSS   49-56          9-16 Division II
>> Lander             468.7 <<                    8-14 Division II
   Augusta            524.4 WIN    66-65    ++   17- 8 Division II
   Middle Georgia     509.1 WIN    69-63    ++   17- 8 Division II
   Clayton State      484.0 WIN    89-87    ++    9-14 Division II
   SC Aiken           462.6 WIN    58-48    +     7-17 Division II
   Flagler            458.1 WIN    68-57    +     9-15 Division II
   Flagler            458.1 WIN    80-64    +     9-15 Division II
   Lincoln (PA)       350.8 WIN    70-51    -     3-23 Division II
   Erskine            336.8 WIN    72-57    -     2-23 Division II

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