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EVALUATING HITTERS BY MONTE CARLO SIMULATION

In chapters 2 and 3 we showed how to use Runs Created and Linear Weights to evaluate a hitter's effectiveness. These metrics were primarily developed to “fit” the relationship between runs scored by a team during a season and team statistics such as walks, singles, doubles, triples, and home runs. We pointed out that for players whose event frequencies differ greatly from typical team frequencies, these metrics might do a poor job of evaluating a hitter's effectiveness.

A simple example will show how Runs Created and Linear Weights can be very inaccurate.1 Consider a player (let's call him Joe Hardy after the hero of the wonderful movie and play Damn Yankees) who hits a home run at 50% of his ...

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