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Using Simulation to Estimate the Impact of Baserunning Ability in Baseball

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  • Baumer Ben S

    (CUNY Graduate School and University Center)

Abstract

In baseball, an offensive team's run scoring ability is dependent not only upon the batting skills of its players, but also their baserunning abilities. Using a Monte Carlo simulation based on actual statistics of real players, we estimate the magnitude of the effect of baserunning skills upon a team's run scoring ability. Our results largely confirm previous non-academic estimates that the impact of baserunning upon a team's run scoring ability is typically less than ±25 runs per season. However, we show using simple heuristic algorithms, that a team composed of the best (worst) nine baserunners could gain (lose) as many as 70 (55), runs per season due to baserunning.

Suggested Citation

  • 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.
    • Handle: RePEc:bpj:jqsprt:v:5:y:2009:i:2:n:8
    DOI: 10.2202/1559-0410.1174
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    References listed on IDEAS

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    1. Turocy, Theodore L., 2005. "Offensive performance, omitted variables, and the value of speed in baseball," Economics Letters, Elsevier, vol. 89(3), pages 283-286, December.
    2. Mark D. Pankin, 1978. "Evaluating Offensive Performance in Baseball," Operations Research, INFORMS, vol. 26(4), pages 610-619, August.
    3. R. Allan Freeze, 1974. "An Analysis of Baseball Batting Order by Monte Carlo Simulation," Operations Research, INFORMS, vol. 22(4), pages 728-735, August.
    4. Bruce Bukiet & Elliotte Rusty Harold & José Luis Palacios, 1997. "A Markov Chain Approach to Baseball," Operations Research, INFORMS, vol. 45(1), pages 14-23, February.
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    Cited by:

    1. 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.
    2. Beaudoin David, 2013. "Various applications to a more realistic baseball simulator," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(3), pages 271-283, September.

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