The method for rating teams in Example 7.8 is based on actual and predicted point spreads. This method can be biased if some teams “run up the score” in a few games. An alternative possibility is to...

The method for rating teams in Example 7.8 is based on actual and predicted point spreads. This method can be biased if some teams “run up the score” in a few games. An alternative possibility is to base the ratings only on wins and losses. For each game, we observe whether the home team wins. Then from the proposed ratings, we predict whether the home team will win. (We predict the home team will win if the home team advantage plus the home team’s rating is greater than the visitor team’s rating.) We want the ratings such that the number of predictions that match the actual outcomes is maximized. Try modeling this. Do you run into difficulties? (Remember that Solver doesn’t like IF functions.)