Wilson Computer Ratings team analysis
CS Dom. Hills (10-13)

CS Dom. Hills's opponents in order of rating: 
     Team            Rating        Score  Effect  W- L
   ---------------   ------       ------- ------ -----
   Cal Poly-Pomona    621.7 LOSS   37-59         24- 2 Division II
   W. Washington      598.3 LOSS   46-68         20- 6 Division II
   CSU-Los Angeles    589.6 LOSS   83-87         18- 5 Division II
   Point Loma Nazar.  583.3 LOSS   48-73         20- 5 Division II
   Azusa Pacific      573.2 LOSS   77-79         17- 7 Division II
   Westmont           567.6 LOSS   55-90         18- 7 Division II
   CS Chico           562.8 LOSS   74-93         18- 8 Division II
   Humboldt St.       553.0 LOSS   55-91         16- 8 Division II
   CSU-Monterey Bay   506.9 LOSS   49-69         11-14 Division II
   CSU-East Bay       497.9 LOSS   65-75          9-16 Division II
   Seattle Pacific    488.3 LOSS   61-64          7-18 Division II
   UC Merced          462.3 LOSS   61-91          7-19 Division II
>> CS Dom. Hills      515.5 <<                   10-13 Division II
   CS Chico           562.8 WIN    64-57    ++   18- 8 Division II
   Humboldt St.       553.0 WIN    51-49    ++   16- 8 Division II
   CSU-SanBernardino  509.1 WIN    75-64    +    11-12 Division II
   CSU-Monterey Bay   506.9 WIN    65-56    +    11-14 Division II
   CSU-East Bay       497.9 WIN    93-76    +     9-16 Division II
   CalSt-San Marcos   488.2 WIN    82-76    +     7-18 Division II
   CalSt-San Marcos   488.2 WIN    59-56    +     7-18 Division II
   San Francisco St.  466.2 WIN    78-66    +     5-20 Division II
   San Francisco St.  466.2 WIN    62-60    +     5-20 Division II
   Stanislaus St      430.5 WIN    79-74    +     3-20 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