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A Markov Process Model of the Number of Years Spent in Major League Baseball

Author

Listed:
  • Krautmann Anthony C.

    (DePaul University)

  • Ciecka James E.

    (DePaul University)

  • Skoog Gary R.

    (DePaul University)

Abstract

We treat the number of years spent in major league baseball as a random variable and estimate probability distributions for this random variable through the use of recursive formulae. Distributional characteristics, including major league baseball worklife expectancies, are estimated for players by age and current activity status in the major leagues. Data from a recent time period (1977-2007) are used to calculate current characteristics of time spent in major league baseball. However, the contemporaneous nature of our data leads to censoring because many players in our data set had not completed their major league careers by the end of 2007. We deal with censoring through a Markov process model that captures transitions between activity and inactivity in major league baseball.

Suggested Citation

  • Krautmann Anthony C. & Ciecka James E. & Skoog Gary R., 2010. "A Markov Process Model of the Number of Years Spent in Major League Baseball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(4), pages 1-25, October.
    • Handle: RePEc:bpj:jqsprt:v:6:y:2010:i:4:n:6
    DOI: 10.2202/1559-0410.1263
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    References listed on IDEAS

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    1. Skoog, Gary & Ciecka, James, 2002. "Probability mass functions for additional years of labor market activity induced by the Markov (increment-decrement) model," Economics Letters, Elsevier, vol. 77(3), pages 425-431, November.
    2. William Witnauer & Richard Rogers & Jarron Saint Onge, 2007. "Major league baseball career length in the 20th century," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(4), pages 371-386, August.
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