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Sports analytics and the big-data era

  • Trends of Data Science
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Abstract

The explosion of data, with large datasets that are available for analysis, has affected virtually every aspect of our lives. The sports industry has not been immune to these developments. In this article, we provide examples of three types of data-driven analyses that have been performed in the domain of sport: (a) field-level analysis focused on the behavior of athletes, coaches, and referees; (b) analysis of management and policymakers’ decisions; and (c) analysis of the literature that uses sports data to address various questions in the fields of economics and psychology.

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Notes

  1. Elaad, G., Kantor, J., & Krumer, A. (2016) Corruption and Contests: Cross-Country Evidence from Sensitive Soccer Matches, mimeo.

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Authors and Affiliations

  1. Department of Business Administration, Guilford Glazer Faculty of Business and Management, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Elia Morgulev & Ofer H. Azar

  2. The Academic College at Wingate, Wingate Institute, Netanya, Israel

    Elia Morgulev & Ronnie Lidor

Authors
  1. Elia Morgulev
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  2. Ofer H. Azar
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  3. Ronnie Lidor
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Correspondence to Ofer H. Azar.

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Morgulev, E., Azar, O.H. & Lidor, R. Sports analytics and the big-data era. Int J Data Sci Anal 5, 213–222 (2018). https://doi.org/10.1007/s41060-017-0093-7

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