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Adjusting Winning-Percentage Standard Deviations and a Measure of Competitive Balance for Home Advantage

Author

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  • Trandel Gregory A

    (University of Georgia)

  • Maxcy Joel G

    (University of Georgia)

Abstract

One measure of sports league competitive balance uses a ratio: the standard deviation of team winning percentages is divided by the so-called ideal standard deviation, which assumes a game between evenly-skilled teams is equally likely to be won by either team. In fact, a team is more likely to win when playing at home than when playing on the road. The extent of this advantage differs across sports leagues. Home advantage reduces the variability of season-long team records. Ignoring home advantage biases upward the traditionally measured ideal standard deviation and bias downward the ratio of standard deviations. The authors derive a balanced league standard deviation formula that accounts for home advantage, use it to recompute the ratio of standard deviations for major sports leagues, and consider how the adjustment affects comparisons of competitive balance across those leagues.

Suggested Citation

  • Trandel Gregory A & Maxcy Joel G, 2011. "Adjusting Winning-Percentage Standard Deviations and a Measure of Competitive Balance for Home Advantage," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(1), pages 1-17, January.
  • Handle: RePEc:bpj:jqsprt:v:7:y:2011:i:1:n:1
    DOI: 10.2202/1559-0410.1297
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    References listed on IDEAS

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    Cited by:

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    3. Young Hoon Lee & Yongdai Kim & Sara Kim, 2019. "A Bias-Corrected Estimator of Competitive Balance in Sports Leagues," Journal of Sports Economics, , vol. 20(4), pages 479-508, May.
    4. Richard Evans, 2014. "A review of measures of competitive balance in the ‘analysis of competitive balance’ literature," Birkbeck Sports Business Centre Working Papers 9, Birkbeck College, Department of Management.
    5. Young Hoon Lee & Yongdai Kim & Sara Kim, 2018. "Unbiased Estimation of Competitive Balance in Sports Leagues with Unbalanced Schedules," Working Papers 1801, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    6. Bulent Uyar & David Surdam, 2013. "Searching for On-Field Parity," Journal of Sports Economics, , vol. 14(5), pages 479-497, October.
    7. Duane W. Rockerbie, 2016. "Exploring Interleague Parity in North America," Journal of Sports Economics, , vol. 17(3), pages 286-301, April.
    8. Dorian Owen, 2014. "Measurement of competitive balance and uncertainty of outcome," Chapters, in: John Goddard & Peter Sloane (ed.), Handbook on the Economics of Professional Football, chapter 3, pages 41-59, Edward Elgar Publishing.
    9. Andrés Picazo-Tadeo & Francisco Gónzalez-Gómez & Jorge Guardiola Wanden-Berghe, 2011. "Referee home bias due to social pressure. Evidence from Spanish football," Working Papers 1119, Department of Applied Economics II, Universidad de Valencia.
    10. Jean‐Pascal Gayant & Nicolas Le Pape, 2017. "Increasing Downside or Outer Risk? The Challenge of Measuring Competitive Imbalance in Closed and Open Leagues," Southern Economic Journal, John Wiley & Sons, vol. 83(3), pages 774-795, January.
    11. Fort, Rodney & Maxcy, Joel & Diehl, Mark, 2016. "Uncertainty by regulation: Rottenberg׳s invariance principle," Research in Economics, Elsevier, vol. 70(3), pages 454-467.
    12. Rockerbie, Duane W, 2012. "Exploring inter-league parity in North America: the NBA anomaly," MPRA Paper 43088, University Library of Munich, Germany.
    13. P. Dorian Owen & Nicholas King, 2015. "Competitive Balance Measures In Sports Leagues: The Effects Of Variation In Season Length," Economic Inquiry, Western Economic Association International, vol. 53(1), pages 731-744, January.
    14. Lee, Travis, 2020. "Competitive Balance in the National Hockey League after Unrestricted Free Agency and the Salary Cap," MPRA Paper 108400, University Library of Munich, Germany.

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