Ben Lindbergh and Travis Sawchik, The MVP Machine: How Baseball’s New Nonconformists Are Using Data to Build Better Players

New York, NY: Basic Books, 2019. vii + 373 pages. USD 30.00 (hardcover)
  • Ryan H. MurphyEmail author

The MVP Machine by Ben Lindbergh and Travis Sawchik has been hailed as the successor to Moneyball (Lewis 2003), according to some reviewers in the popular press (Hamilton 2019; Torres 2019). To set the stage for The MVP Machine, let us first consider Moneyball. In the era covered in Moneyball, Major League Baseball teams were stuck in their ways, and the cursory application of data analytics demonstrated that teams were simply not correctly valuing certain skills that were valuable for winning games, especially the skill of reaching base (i.e., on-base percentage). Subsequent analysis has shown these disparities were very much real (Hakes and Sauer 2006). Billy Beane, the general manager of the cash-strapped Oakland Athletics, was the first to act on these disparities and was able to turn it into success by finding undervalued players until his competitors caught on to the strategy.

The popular interpretation of Moneyballis that it is a book about the application of statistics to...



  1. Alexander, S. (2015a). No clarity around growth mindset. Slate Star Codex. Accessed 30 Oct 2019.
  2. Alexander, S. (2015b). I will never have the ability to clearly explain my beliefs about growth mindset. Slate Star Codex. Accessed 30 Oct 2019.
  3. Alexander, S. (2015c). Growth mindset 3: A pox on growth your houses. Slate Star Codex. Accessed 30 October 2019.
  4. Alexander, S. (2015d). Growth mindset 4: Growth of office. Slate star codex. Accessed 30 Oct 2019.
  5. Burnette, J. L., O’Boyle, E. H., VanEpps, E. M., Pollack, J. M., & Finkel, E. J. (2013). Mind-sets matter: A meta-analytic review of implicit theories and self-regulation. Psychological Bulletin, 139, 655–701.CrossRefGoogle Scholar
  6. Dweck, C. S. (2006). Mindset: The new psychology of success. New York: Random House.Google Scholar
  7. Gelman, A., & Loken, E. (2014). The statistical crisis in science. American Scientist, 102, 460–465.CrossRefGoogle Scholar
  8. Hakes, J. K., & Sauer, R. D. (2006). An economic evaluation of the Moneyball hypothesis. Journal of Economic Perspectives, 20, 173–186.CrossRefGoogle Scholar
  9. Hamilton, J. (2019). The new science of building baseball superstars. The Atlantic. Accessed 30 Oct 2019.
  10. Lewis, M. (2003). Moneyball: The art of winning an unfair game. New York: W.W. Norton & Company.Google Scholar
  11. Munafo, M. R., Nosek, B. A., Bishop, D. V. M., Button, K. S., Chambers, C. D., Percie du Sert, N., et al. (2017). A manifesto for reproducible science. Nature Human Behavior, 1, 0021.CrossRefGoogle Scholar
  12. Passan, J. (2016). The arm: Inside the billion-dollar mystery of the most valuable commodity in sports. New York: HarperCollins.Google Scholar
  13. Shmanske, S. (2007). Austrian themes, data, and sports economics. The Review of Austrian Economics, 20, 11–24.CrossRefGoogle Scholar
  14. Torres, L. (2019). The MVP Machine is a must-read. Beyond the Box Score. Accessed 30 Oct 2019.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.O’Neil Center for Global Markets and Freedom at Southern Methodist UniversityDallasUSA

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