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Referee Bias and Stoppage Time in Major League Soccer: A Partially Adaptive Approach

Author Info

Listed author(s):
  • Katherine G. Yewell

    ()

    (Department of Economics, Vanderbilt University, Nashville, TN 37212, USA)

  • Steven B. Caudill

    ()

    (Department of Economics, Rhodes College, Memphis, TN 38112, USA
    Department of Economics (Regions Bank Professor Emeritus), Auburn University, Auburn, AL 36849, USA)

  • Franklin G. Mixon, Jr.

    ()

    (Center for Economic Education, Columbus State University, Columbus, GA 31907, USA)

Abstract

This study extends prior research on referee bias and close bias in professional soccer by examining whether Major League Soccer (MLS) referees’ discretion over stoppage time (i.e., extra play beyond regulation) is influenced by end-of-regulation match scores and/or home field advantage. To do so, we employ a grouped-data regression model and a partially adaptive model. Both account for the imprecise measurement in reported stoppage time. For the 2011 season we find no home field advantage. In fact, stoppage time is the same with a one or two goal deficit at the end of regulation, regardless of which team is ahead. However, the 2011 results do point to an increase in stoppage time of 12 to 20 seconds for nationally televised matches. For the 2012 season, the nationally televised effect disappears due to an increase in stoppage time for those matches not nationally televised. However, a home field advantage is present. Facing a one-goal deficit at the end of regulation, the home team receives about 33 seconds more stoppage time than a visiting team facing the same deficit.

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Article provided by MDPI, Open Access Journal in its journal Econometrics.

Volume (Year): 2 (2014)
Issue (Month): 1 (February)
Pages: 1-19

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Handle: RePEc:gam:jecnmx:v:2:y:2014:i:1:p:1-19:d:32999
Contact details of provider: Web page: http://www.mdpi.com/

Keywords: partially adaptive estimation; referee bias; close bias; grouped-data regression;

Find related papers by JEL classification:

  • B23 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Econometrics; Quantitative and Mathematical Studies
  • C - Mathematical and Quantitative Methods
  • C00 - Mathematical and Quantitative Methods - - General - - - General
  • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
  • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
  • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
  • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
  • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
  • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
  • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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