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Markov Analysis of APBA, a Baseball Simulation Game

Author

Listed:
  • Davis Donald M

    (Lehigh University)

Abstract

APBA baseball is a sophisticated baseball simulation game. Each major league player is represented by a card, which has numbers on it that reflect his performance in a particular season. Two people play a game by rolling dice and looking on their players' cards to see what is the outcome of the roll of the dice.In this article, we use Markov chains to analyze certain aspects of this game. For example, we can tell whether one player's batting card is more valuable than another's, and we can make informed decisions about strategy in the game.

Suggested Citation

  • Davis Donald M, 2011. "Markov Analysis of APBA, a Baseball Simulation Game," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(3), pages 1-14, July.
    • Handle: RePEc:bpj:jqsprt:v:7:y:2011:i:3:n:5
    DOI: 10.2202/1559-0410.1285
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    References listed on IDEAS

    as
    1. Joel S. Sokol, 2004. "An Intuitive Markov Chain Lesson From Baseball," INFORMS Transactions on Education, INFORMS, vol. 5(1), pages 47-55, September.
    2. 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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