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Data analytics effects in major league baseball

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  • Elitzur, Ramy

Abstract

The use of data analytics has enjoyed resurgence over the last two decades in professional sports, businesses, and the government. This resurgence is attributable to Moneyball, which exposed readers to the use of advanced baseball analytics by the Oakland Athletics, and how it has resulted in improved player selection and game management. Moreover, it changed managerial vocabulary, as the term “Moneyballing” now commonly describes organizations that use data analytics. The first research question that this study examines is whether the organizational knowledge related to baseball data analytics has provided any advantage in the competitive Major League Baseball (MLB) marketplace. The second research question is whether this strategic advantage can be sustained once this proprietary organizational knowledge becomes public. First, I identify “Moneyball” teams and executives, i.e., those who rely on baseball data analytics, and track their pay/performance over time. Next, using econometric models, I analyze whether these “Moneyball” teams and GMs, have enjoyed a pay-performance advantage over the rest of MLB, and whether this advantage persists after the information becomes public.

Suggested Citation

  • Elitzur, Ramy, 2020. "Data analytics effects in major league baseball," Omega, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:jomega:v:90:y:2020:i:c:s0305048318300215
    DOI: 10.1016/j.omega.2018.11.010
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    1. Michael J. Fry & Jeffrey W. Ohlmann, 2012. "Introduction to the Special Issue on Analytics in Sports, Part I: General Sports Applications," Interfaces, INFORMS, vol. 42(2), pages 105-108, April.
    2. Scully, Gerald W, 1974. "Pay and Performance in Major League Baseball," American Economic Review, American Economic Association, vol. 64(6), pages 915-930, December.
    3. Schwert, G. William, 2003. "Anomalies and market efficiency," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 15, pages 939-974, Elsevier.
    4. Timothy C. Y. Chan & Douglas Fearing, 2019. "Process Flexibility in Baseball: The Value of Positional Flexibility," Management Science, INFORMS, vol. 65(4), pages 1642-1666, April.
    5. Michael J. Fry & Jeffrey W. Ohlmann, 2012. "Introduction to the Special Issue on Analytics in Sports, Part II: Sports Scheduling Applications," Interfaces, INFORMS, vol. 42(3), pages 229-231, June.
    6. Herman Demmink, 2010. "Value of stealing bases in Major League Baseball," Public Choice, Springer, vol. 142(3), pages 497-505, March.
    7. J. Eric Bickel, 2009. "On the Decision to Take a Pitch," Decision Analysis, INFORMS, vol. 6(3), pages 186-193, September.
    8. Partha S. Mohanram, 2014. "Analysts' Cash Flow Forecasts and the Decline of the Accruals Anomaly," Contemporary Accounting Research, John Wiley & Sons, vol. 31(4), pages 1143-1170, December.
    9. Jahn K. Hakes & Raymond D. Sauer, 2006. "An Economic Evaluation of the Moneyball Hypothesis," Journal of Economic Perspectives, American Economic Association, vol. 20(3), pages 173-186, Summer.
    10. Dimitris Bertsimas & Eric Bradlow & Noah Gans & Alok Gupta, 2014. "Introduction to the Special Issue on Business Analytics," Management Science, INFORMS, vol. 60(6), pages 1351-1351, June.
    11. Matthew J. Liberatore & Wenhong Luo, 2010. "The Analytics Movement: Implications for Operations Research," Interfaces, INFORMS, vol. 40(4), pages 313-324, August.
    12. Suresh Radhakrishnan & Shu†Ling Wu, 2014. "Analysts' Cash Flow Forecasts and Accrual Mispricing," Contemporary Accounting Research, John Wiley & Sons, vol. 31(4), pages 1191-1219, December.
    13. Daniel Deli, 2013. "Assessing the Relative Importance of Inputs to a Production Function," Journal of Sports Economics, , vol. 14(2), pages 203-217, April.
    14. Gerard Miller & Melissa Weatherwax & Timothy Gardinier & Naoki Abe & Prem Melville & Cezar Pendus & David Jensen & Chandan K. Reddy & Vince Thomas & James Bennett & Gary Anderson & Brent Cooley, 2012. "Tax Collections Optimization for New York State," Interfaces, INFORMS, vol. 42(1), pages 74-84, February.
    15. Jeremiah Green & John R. M. Hand & Mark T. Soliman, 2011. "Going, Going, Gone? The Apparent Demise of the Accruals Anomaly," Management Science, INFORMS, vol. 57(5), pages 797-816, May.
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    Cited by:

    1. Bergantiños, Gustavo & Moreno-Ternero, Juan D., 2022. "Monotonicity in sharing the revenues from broadcasting sports leagues," European Journal of Operational Research, Elsevier, vol. 297(1), pages 338-346.
    2. Alan T. Murray & Antonio Ortiz & Seonga Cho, 2022. "Enhancing strategic defensive positioning and performance in the outfield," Journal of Geographical Systems, Springer, vol. 24(2), pages 223-240, April.

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