IDEAS home Printed from https://ideas.repec.org/a/bpj/jqsprt/v5y2009i3n10.html
   My bibliography  Save this article

Differentiating the Top English Premier League Football Clubs from the Rest of the Pack: Identifying the Keys to Success

Author

Listed:
  • Oberstone Joel

    (University of San Francisco)

Abstract

This paper develops a robust, statistically significant, six independent variable multiple regression model that accounts for the relative success of English Premier League football clubs based on an array of twenty-four pitch actions collected during the 2007-2008 season (p

Suggested Citation

  • Oberstone Joel, 2009. "Differentiating the Top English Premier League Football Clubs from the Rest of the Pack: Identifying the Keys to Success," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(3), pages 1-29, July.
    • Handle: RePEc:bpj:jqsprt:v:5:y:2009:i:3:n:10
    DOI: 10.2202/1559-0410.1183
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1559-0410.1183
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1559-0410.1183?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fiona Carmichael & Dennis Thomas & Robert Ward, 2000. "Team performance: the case of English Premiership football," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 21(1), pages 31-45.
    2. Chris Hope, 2003. "When should you sack a football manager? Results from a simple model applied to the English Premiership," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(11), pages 1167-1176, November.
    3. P. D. Jones & N. James & S. D. Mellalieu, 2004. "Possession as a performance indicator in soccer," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 4(1), pages 98-102, August.
    4. Ian McHale & Phil Scarf, 2007. "Modelling soccer matches using bivariate discrete distributions with general dependence structure," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 61(4), pages 432-445, November.
    5. Salwa Ammar & Ronald Wright, 2004. "Comparing the Impact of Star Rookies Carmelo Anthony and Lebron James: An Example on Simulating Team Performances in the NBA League," INFORMS Transactions on Education, INFORMS, vol. 5(1), pages 67-74, September.
    6. A D Fitt & C J Howls & M Kabelka, 2006. "Valuation of soccer spread bets," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(8), pages 975-985, August.
    7. Boulier, Bryan L. & Stekler, H. O., 2003. "Predicting the outcomes of National Football League games," International Journal of Forecasting, Elsevier, vol. 19(2), pages 257-270.
    8. Andersson, Patric & Edman, Jan & Ekman, Mattias, 2005. "Predicting the World Cup 2002 in soccer: Performance and confidence of experts and non-experts," International Journal of Forecasting, Elsevier, vol. 21(3), pages 565-576.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fischer, Kai & Reade, J. James & Schmal, W. Benedikt, 2022. "What cannot be cured must be endured: The long-lasting effect of a COVID-19 infection on workplace productivity," Labour Economics, Elsevier, vol. 79(C).
    2. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos & Verousis, Thanos, 2020. "A conditional fuzzy inference approach in forecasting," European Journal of Operational Research, Elsevier, vol. 283(1), pages 196-216.
    3. Oberstone Joel, 2010. "Comparing English Premier League Goalkeepers: Identifying the Pitch Actions that Differentiate the Best from the Rest," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(1), pages 1-19, January.
    4. Avila-Cano, Antonio & Owen, P. Dorian & Triguero-Ruiz, Francisco, 2023. "Measuring competitive balance in sports leagues that award bonus points, with an application to rugby union," European Journal of Operational Research, Elsevier, vol. 309(2), pages 939-952.
    5. Fiona Carmichael & Dennis Thomas, 2014. "Team performance: production and efficiency in football," Chapters, in: John Goddard & Peter Sloane (ed.), Handbook on the Economics of Professional Football, chapter 10, pages 143-165, Edward Elgar Publishing.
    6. Lichter, Andreas & Pestel, Nico & Sommer, Eric, 2017. "Productivity effects of air pollution: Evidence from professional soccer," Labour Economics, Elsevier, vol. 48(C), pages 54-66.
    7. Kai Fischer & J. James Reade & W. Benedikt Schmal, 2021. "The Long Shadow of an Infection: COVID-19 and Performance at Work," Economics Discussion Papers em-dp2021-17, Department of Economics, University of Reading.
    8. Oberstone Joel, 2011. "Comparing Team Performance of the English Premier League, Serie A, and La Liga for the 2008-2009 Season," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(1), pages 1-18, January.
    9. Tunaru Radu S & Viney Howard P, 2010. "Valuations of Soccer Players from Statistical Performance Data," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(2), pages 1-23, April.
    10. Wu Lucas Y. & Danielson Aaron J. & Hu X. Joan & Swartz Tim B., 2021. "A contextual analysis of crossing the ball in soccer," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(1), pages 57-66, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vaughan Williams, Leighton & Stekler, Herman O., 2010. "Sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 445-447, July.
      • Herman O. Stekler, 2007. "Sports Forecasting," Working Papers 2007-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Jan 2007.
    2. Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
      • Herman O. Stekler & David Sendor & Richard Verlander, 2009. "Issues in Sports Forecasting," Working Papers 2009-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    3. Tunaru Radu S & Viney Howard P, 2010. "Valuations of Soccer Players from Statistical Performance Data," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(2), pages 1-23, April.
    4. Antonio Samagaio & Eduardo Couto & Jorge Caiado, 2009. "Sporting, financial and stock market performance in English football: an empirical analysis of structural relationships," CEMAPRE Working Papers 0906, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
    5. Song, ChiUng & Boulier, Bryan L. & Stekler, Herman O., 2007. "The comparative accuracy of judgmental and model forecasts of American football games," International Journal of Forecasting, Elsevier, vol. 23(3), pages 405-413.
    6. Butler, David & Butler, Robert & Eakins, John, 2021. "Expert performance and crowd wisdom: Evidence from English Premier League predictions," European Journal of Operational Research, Elsevier, vol. 288(1), pages 170-182.
    7. Oberstone Joel, 2010. "Comparing English Premier League Goalkeepers: Identifying the Pitch Actions that Differentiate the Best from the Rest," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(1), pages 1-19, January.
    8. del Corral, Julio & Prieto-Rodríguez, Juan, 2010. "Are differences in ranks good predictors for Grand Slam tennis matches?," International Journal of Forecasting, Elsevier, vol. 26(3), pages 551-563, July.
    9. M B Wright, 2009. "50 years of OR in sport," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 161-168, May.
    10. Scheibehenne, Benjamin & Broder, Arndt, 2007. "Predicting Wimbledon 2005 tennis results by mere player name recognition," International Journal of Forecasting, Elsevier, vol. 23(3), pages 415-426.
    11. Manuel Espitia‐Escuer & Lucia Isabel Garcia‐Cebrian, 2020. "Efficiency of football teams from an organisation management perspective," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(3), pages 321-338, April.
    12. Alessandro Innocenti & Tommaso Nannicini & Roberto Ricciuti, 2021. "The Importance of Betting Early," Risks, MDPI, vol. 9(4), pages 1-15, April.
    13. Goldstein, Daniel G. & Gigerenzer, Gerd, 2009. "Fast and frugal forecasting," International Journal of Forecasting, Elsevier, vol. 25(4), pages 760-772, October.
    14. Fiona Carmichael & Dennis Thomas, 2014. "Team performance: production and efficiency in football," Chapters, in: John Goddard & Peter Sloane (ed.), Handbook on the Economics of Professional Football, chapter 10, pages 143-165, Edward Elgar Publishing.
    15. Benjamin Leard & Joanne M. Doyle, 2011. "The Effect of Home Advantage, Momentum, and Fighting on Winning in the National Hockey League," Journal of Sports Economics, , vol. 12(5), pages 538-560, October.
    16. Scarf, Philip & Yusof, Muhammad Mat & Bilbao, Mark, 2009. "A numerical study of designs for sporting contests," European Journal of Operational Research, Elsevier, vol. 198(1), pages 190-198, October.
    17. Karol Kempa & Hannes Rusch, 2019. "Dissent, sabotage, and leader behaviour in contests: Evidence from European football," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 40(5), pages 500-514, July.
    18. Costanza Torricelli & Maria Cesira Urzì Brancati & Luca Mirtoleni, 2014. "The impact of skill and management structure on Serie A Clubs’ performance," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 14107, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    19. Markus Glaser & Thomas Langer & Martin Weber, 2007. "On the Trend Recognition and Forecasting Ability of Professional Traders," Decision Analysis, INFORMS, vol. 4(4), pages 176-193, December.
    20. S Lessmann & M-C Sung & J E V Johnson, 2011. "Towards a methodology for measuring the true degree of efficiency in a speculative market," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2120-2132, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:jqsprt:v:5:y:2009:i:3:n:10. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.