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Optimal batting orders in cricket

Author

Listed:
  • J M Norman

    (The Management School, University of Sheffield)

  • S R Clarke

    (Faculty of Life and Social Sciences, Swinburne University)

Abstract

Cricket teams are usually listed on the scoreboard in expected batting order, and although captains can choose to send in any of the remaining batsmen when a wicket falls, they rarely depart from the usual batting order. By optimizing a simplified model using dynamic programming, this paper shows that in all forms of cricket significant increases in expected score result if captains allow a variable batting order and base their decision on the state of the game, rather than using a set batting order.

Suggested Citation

  • J M Norman & S R Clarke, 2010. "Optimal batting orders in cricket," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(6), pages 980-986, June.
    • Handle: RePEc:pal:jorsoc:v:61:y:2010:i:6:d:10.1057_jors.2009.54
    DOI: 10.1057/jors.2009.54
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    References listed on IDEAS

    as
    1. R. Allan Freeze, 1974. "An Analysis of Baseball Batting Order by Monte Carlo Simulation," Operations Research, INFORMS, vol. 22(4), pages 728-735, August.
    2. J M Norman & S R Clarke, 2007. "Dynamic programming in cricket: optimizing batting order for a sticky wicket," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1678-1682, December.
    3. Bruce Bukiet & Elliotte Rusty Harold & José Luis Palacios, 1997. "A Markov Chain Approach to Baseball," Operations Research, INFORMS, vol. 45(1), pages 14-23, February.
    4. G D I Barr & B S Kantor, 2004. "A criterion for comparing and selecting batsmen in limited overs cricket," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1266-1274, December.
    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.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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    2. Norton, Hugh & Gray, Steve & Faff, Robert, 2015. "Yes, one-day international cricket ‘in-play’ trading strategies can be profitable!," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 164-176.
    3. 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.
    4. Yamini Nekkanti & Dibyojyoti Bhattacharjee, 2020. "Novel Performance Metrics to Evaluate the Duel Between a Batsman and a Bowler," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 45(2), pages 201-211, May.
    5. Arnab Adhikari & Adrija Majumdar & Gaurav Gupta & Arnab Bisi, 2020. "An innovative super-efficiency data envelopment analysis, semi-variance, and Shannon-entropy-based methodology for player selection: evidence from cricket," Annals of Operations Research, Springer, vol. 284(1), pages 1-32, January.
    6. Wei Yin & Zhixiao Ye & Wasi Ul Hassan Shah, 2023. "Indices Development for Player’s Performance Evaluation through the Super-SBM Approach in Each Department for All Three Formats of Cricket," Sustainability, MDPI, vol. 15(4), pages 1-20, February.

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