Moneyball: Analyzing the Efficiency of English Premier League Strikers Using Data Envelopment Analysis

Author:

Essien AniekanORCID,Kremantzis Marios,Joshi Dhiraj,Zaghloul FatemaORCID

Publisher

Springer Nature Switzerland

Reference22 articles.

1. Baumer, B. S., Matthews, G. J., & Nguyen, Q. (2023). Big ideas in sports analytics and statistical tools for their investigation. Wiley Interdisciplinary Reviews: Computational Statistics, Wiley Online Library, p. e1612.

2. Lewis, M. (2004). Moneyball: The Art of Winning an Unfair Game, WW Norton & Company.

3. EY. (2019). Premier League Economic and social impact. Retrieved 31 January, 2023, from https://assets.ey.com/content/dam/ey-sites/ey-com/pt_br/topics/ey-economic-advisory-/ey-premier-league-economic-and-social-impact-january-2019.pdf.

4. Brechot, M., & Flepp, R. (2020). Dealing with randomness in match outcomes: How to rethink performance evaluation in European club football using expected goals. Journal of Sports Economics, Sage Publications Sage CA: Los Angeles, CA, 21(4), 335–362.

5. Ruiz, J. L., Pastor, D., & Pastor, J. T. (2013). Assessing professional tennis players using data envelopment analysis (DEA). Journal of Sports Economics, 14(3), 276–302.

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