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Parsing the Relationship between Baserunning and Batting Abilities within Lineups


  • Baumer Ben S.

    (CUNY Graduate School and University Center)

  • Piette James

    (University of Pennsylvania)

  • Null Brad

    (Stanford University)


A baseball team's offensive prowess is a function of two types of abilities: batting and baserunning. While each has been studied extensively in isolation, the effects of their interaction is not well understood. We model offensive output as a scalar function f of an individual player's batting and baserunning profile z. Each of these profiles is in turn estimated from Retrosheet data using heirarchical Bayesian models. We then use the SimulOutCome simulation engine as a method to generate values of f(z) over a fine grid of points. Finally, for each of several methods of taking the extra base, we graphically depict the surface f(z) over changes in the probability of advancing via that method. This framework allows us to draw conclusions both about optimal baserunning strategies in general, and about how particular offensive profiles affect a player's optimal baserunning strategy. We present many informative visualizations and analyze specific aspects of several well-known Major League players.

Suggested Citation

  • Baumer Ben S. & Piette James & Null Brad, 2012. "Parsing the Relationship between Baserunning and Batting Abilities within Lineups," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(2), pages 1-19, June.
  • Handle: RePEc:bpj:jqsprt:v:8:y:2012:i:2:n:7

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    References listed on IDEAS

    1. Albert James, 2006. "Pitching Statistics, Talent and Luck, and the Best Strikeout Seasons of All-Time," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 2(1), pages 1-32, January.
    2. Null Brad, 2009. "Modeling Baseball Player Ability with a Nested Dirichlet Distribution," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(2), pages 1-38, May.
    3. Baumer Ben S, 2009. "Using Simulation to Estimate the Impact of Baserunning Ability in Baseball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(2), pages 1-18, May.
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