IDEAS home Printed from https://ideas.repec.org/a/bpj/jqsprt/v5y2009i4n3.html

Was Bradman Denied His Prime?

Author

Listed:
  • Bracewell Paul J

    (Offlode)

  • Farhadieh Farinaz

    (Offlode and Swinburne University of Technology)

  • Jowett Clint A

    (Offlode)

  • Forbes Don G. R.

    (Offlode)

  • Meyer Denny H

    (Swinburne University of Technology)

Abstract

Time series clustering is used to show that, relatively, the career progression of Australian legend Sir Donald Bradman's test career as a batsman was most similar to West Indian Brian Lara. Consequently, it is likely his peak performance would have occurred while the Second World War disrupted all international cricket.Data from the 20 international cricketers who played in at least 70 innings over more than 17 years and averaged more than 40 runs per dismissal (as at January 1, 2009) is used to create a number of global measures that indicate the ebb and flow of a career. As is shown in this paper, this clustering methodology, proposed by Wang et al. (2006), generates instinctive clustering results and can be applied on different length time series.Utilizing the framework created for clustering, Bradman's batting average is estimated to be 105 if his career had been uninterrupted.

Suggested Citation

  • Bracewell Paul J & Farhadieh Farinaz & Jowett Clint A & Forbes Don G. R. & Meyer Denny H, 2009. "Was Bradman Denied His Prime?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(4), pages 1-26, October.
    • Handle: RePEc:bpj:jqsprt:v:5:y:2009:i:4:n:3
    DOI: 10.2202/1559-0410.1195
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1559-0410.1195
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1559-0410.1195?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

    for a different version of it.

    References listed on IDEAS

    as
    1. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    2. Pattarin, Francesco & Paterlini, Sandra & Minerva, Tommaso, 2004. "Clustering financial time series: an application to mutual funds style analysis," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 353-372, September.
    3. Bracewell Paul J & Ruggiero Katya, 2009. "A Parametric Control Chart for Monitoring Individual Batting Performances in Cricket," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(3), pages 1-21, July.
    4. Nicolas Basalto & Francesco Carlo, 2006. "Clustering financial time series," Springer Books, in: Hideki Takayasu (ed.), Practical Fruits of Econophysics, pages 252-256, Springer.
    5. Alan C. Kimber & Alan R. Hansford, 1993. "A Statistical Analysis of Batting in Cricket," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 156(3), pages 443-455, May.
    6. Lee Tae-Hwy, 2001. "Neural Network Test and Nonparametric Kernel Test for Neglected Nonlinearity in Regression Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(4), pages 1-15, January.
    Full references (including those not matched with items on IDEAS)

    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. Fabrizio Durante & Roberta Pappadà & Nicola Torelli, 2015. "Clustering of time series via non-parametric tail dependence estimation," Statistical Papers, Springer, vol. 56(3), pages 701-721, August.
    2. Borooah Vani K & Mangan John E, 2010. "The "Bradman Class": An Exploration of Some Issues in the Evaluation of Batsmen for Test Matches, 1877-2006," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(3), pages 1-21, July.
    3. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    4. Sargent Jonathan RT & Bedford Anthony, 2012. "Using Conditional Estimates to Simulate In-Play Outcomes in Limited Overs Cricket," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(2), pages 1-20, June.
    5. Fabrizio Durante & Roberta Pappadà & Nicola Torelli, 2014. "Clustering of financial time series in risky scenarios," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(4), pages 359-376, December.
    6. Oliver G. Stevenson & Brendon J. Brewer, 2021. "Finding your feet: A Gaussian process model for estimating the abilities of batsmen in test cricket," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(2), pages 481-506, March.
    7. Stevenson Oliver George & Brewer Brendon J., 2017. "Bayesian survival analysis of batsmen in Test cricket," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(1), pages 25-36, March.
    8. Chun-Xiao Nie, 2021. "Studying the correlation structure based on market geometry," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 411-441, April.
    9. Dong, Keqiang & Zhang, Hong & Gao, You, 2017. "Dynamical mechanism in aero-engine gas path system using minimum spanning tree and detrended cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 363-369.
    10. Tanya Araújo & Francisco Louçã, 2008. "Tribes under Threat – The Collective Behavior of Firms During the Stock Market Crisis," Working Papers Department of Economics 2008/28, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    11. Michel Alexandre & Kau^e Lopes de Moraes & Francisco Aparecido Rodrigues, 2021. "Risk-dependent centrality in the Brazilian stock market," Papers 2103.09059, arXiv.org.
    12. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    13. Leonidas Sandoval Junior, 2014. "Dynamics in two networks based on stocks of the US stock market," Papers 1408.1728, arXiv.org, revised Aug 2014.
    14. Champagne, Claudia, 2014. "The international syndicated loan market network: An “unholy trinity”?," Global Finance Journal, Elsevier, vol. 25(2), pages 148-168.
    15. Xie, Yiwei & Jiao, Feng & Li, Shihan & Liu, Qingfu & Tse, Yiuman, 2022. "Systemic risk in financial institutions: A multiplex network approach," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    16. Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.
    17. Huiling Yuan & Kexin Lu & Guodong Li & Junhui Wang, 2024. "High‐Frequency‐Based Volatility Model with Network Structure," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(4), pages 533-557, July.
    18. Shi, Yongbin & Li, Le & Wang, Yougui & Chen, Jiawei & Stanley, H. Eugene, 2019. "A study of Chinese regional hierarchical structure based on surnames," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 169-176.
    19. Peter N. Posch & Daniel Ullmann & Dominik Wied, 2019. "Detecting structural changes in large portfolios," Empirical Economics, Springer, vol. 56(4), pages 1341-1357, April.
    20. Yao, Can-Zhong & Lin, Ji-Nan & Lin, Qing-Wen & Zheng, Xu-Zhou & Liu, Xiao-Feng, 2016. "A study of causality structure and dynamics in industrial electricity consumption based on Granger network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 297-320.

    More about this item

    Keywords

    ;

    Statistics

    Access and download statistics

    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:4:n:3. 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.degruyterbrill.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.