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Did the Best Team Win? Analysis of the 2010 Major League Baseball Postseason Using Monte Carlo Simulation


  • Rudelius Thomas W.

    (Cornell University)


The San Francisco Giants were crowned champions of Major League Baseball in 2010 after defeating the Texas Rangers in the World Series. The World Series matchup may have come as a surprise to many baseball fanatics; the Rangers ended the regular season with the worst record of any of the eight playoff teams, and the Giants ended with the fourth worst. Did these two teams simply catch fire at the right time? Or were they better than their regular season records showed? To answer these questions, the regular season statistics of individual players on each team were used to simulate the postseason. These simulations determined the probability with which each playoff team could have been expected to win the 2010 World Series.

Suggested Citation

  • Rudelius Thomas W., 2012. "Did the Best Team Win? Analysis of the 2010 Major League Baseball Postseason Using Monte Carlo Simulation," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(1), pages 1-13, March.
  • Handle: RePEc:bpj:jqsprt:v:8:y:2012:i:1:n:10

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    References listed on IDEAS

    1. Stimel Derek S, 2011. "Dependence Relationships between On Field Performance, Wins, and Payroll in Major League Baseball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(2), pages 1-19, May.
    2. Charles E. Zech, 1981. "An Empirical Estimation of a Production Function: The Case of Major League Baseball," The American Economist, Sage Publications, vol. 25(2), pages 19-23, October.
    3. John Charles Bradbury, 2007. "Does the Baseball Labor Market Properly Value Pitchers?," Journal of Sports Economics, , vol. 8(6), pages 616-632, December.
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    Cited by:

    1. Pettigrew Stephen, 2014. "How the West will be won: using Monte Carlo simulations to estimate the effects of NHL realignment," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(3), pages 1-11, September.

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