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Estimating Situational Effects on OPS


  • Yates Philip A

    (California State Polytechnic University - Pomona)


`What is the offensive value of Player A?´ Of all the metrics that sabermetricians have developed to attempt to answer that question, OPS (on base percentage plus slugging percentage) has been one of the first for the mainstream media to slowly embrace as an alternative to batting average. Looking at statistics for each team on, one sees that the batting statistics are sorted by OPS as the default sort. What if the question asked was `What is the offensive value of Player A in Situation B versus Situation C?´ In 1994, Jim Albert used the Gibbs sampler to estimate the effect different in-game situations had on batting average. One example of such a situation is a player's breakdown statistics in home and away games. By employing the Gibbs sampler on each component of OPS, one can compute the situational effect on a player's OPS. The data will consist of the hitting performance of major league regulars during the 2006 season who qualified for the batting title. Part of the appeal of OPS is that it is simpler to calculate than other more complicated metrics developed by sabermetricians; however, the raw value of OPS does have limitations such as not taking into consideration ballpark effects or the differences between the two leagues.

Suggested Citation

  • Yates Philip A, 2008. "Estimating Situational Effects on OPS," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 4(2), pages 1-15, April.
  • Handle: RePEc:bpj:jqsprt:v:4:y:2008:i:2:n:2

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