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Performance Measurement of Major League Baseball Teams Using Network DEA

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Data Envelopment Analysis

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 208))

Abstract

Data envelopment analysis (DEA) has been extensively applied to measure the performance of individual athletes and teams in a variety of sports as well as to analyze nations competing in the Olympics. Most of the models presented in the literature are single-stage DEA models which treat the underlying process of converting inputs into outputs as a “black box.” In many situations, analysts are interested in investigating the sources of inefficiency within the organization in order to improve organizational performance. To accomplish this, researchers have developed two-stage and network DEA methodologies.

In this chapter, we model an MLB team as comprised of a front office operation which consumes money in the form of player salaries to acquire offensive and defensive talent and an on-field operation which uses the talent to outscore opponents and win games. We present a network DEA methodology to measure performance of the front office operation, the on-field operation, and the overall team. Finally, we conduct two industry-wide studies of Major League Baseball which utilize the network DEA methodology.

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Authors and Affiliations

  1. College of Business, Stony Brook University, Stony Brook, NY, 11794-3775, USA

    Herbert F. Lewis

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  1. Herbert F. Lewis
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Correspondence to Herbert F. Lewis .

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Editors and Affiliations

  1. Schulich School of Business, York University, Toronto, Ontario, Canada

    Wade D. Cook

  2. School of Business, Worcester Polytechnic Institute, Worcester, Massachusetts, USA

    Joe Zhu

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Lewis, H.F. (2014). Performance Measurement of Major League Baseball Teams Using Network DEA. In: Cook, W., Zhu, J. (eds) Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 208. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-8068-7_20

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