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A criterion for comparing and selecting batsmen in limited overs cricket

Author

Listed:
  • G D I Barr

    (University of Cape Town)

  • B S Kantor

    (University of Cape Town)

Abstract

The batting average statistic has been used almost exclusively to assess the worth of a batsman. It reveals a great deal about the potential performance of batsmen in cricket played at the first class level. However, in the one-day game, strict limits on the number of balls bowled have introduced a very important additional dimension to performance. In the one-day game, it is clearly not good enough for a batsman to achieve a high batting average with a low strike rate. Runs scored slowly, even without the loss of wickets, will generally result in defeat rather than victory in the one-day game. Assessing batting performance in the one-day game, therefore, requires the application of at least a two-dimensional measurement approach because of the time dimension imposed on limited overs cricket. In this paper, we use a new graphical representation with Strike rate on one axis and the Probability of getting out on the other, akin to the risk–return framework used in portfolio analysis, to obtain useful, direct and comparative insights into batting performance, particularly in the context of the one-day game. Within this two-dimensional framework we develop a selection criterion for batsmen, which combines the average and the strike rate. As an example of the application, we apply this criterion to the batting performances of the 2003 World Cup. We demonstrate the strong and consistent performances of the Australian and Indian batsmen as well as provide a ranking of batting prowess for the top 20 run scorers in the tournament.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:12:d:10.1057_palgrave.jors.2601800
    DOI: 10.1057/palgrave.jors.2601800
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Ajit Karnik, 2010. "Valuing Cricketers Using Hedonic Price Models," Journal of Sports Economics, , vol. 11(4), pages 456-469, August.
    2. Dibyojyoti Bhattacharjee & Hemanta Saikia, 2016. "An objective approach of balanced cricket team selection using binary integer programming method," OPSEARCH, Springer;Operational Research Society of India, vol. 53(2), pages 225-247, June.
    3. Hemanta Saikia, 2020. "Quantifying the Current Form of Cricket Teams and Predicting the Match Winner," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 45(2), pages 151-158, May.
    4. Sahadeb Sarkar & Anirban Banerjee, 2016. "Measuring batting consistency and comparing batting greats in test cricket: innovative applications of statistical tools," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 43(4), pages 365-400, December.
    5. A J Lewis, 2008. "Extending the range of player-performance measures in one-day cricket," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(6), pages 729-742, June.
    6. Sahadeb Sarkar & Subhasis Mishra & Sanjeev Kumar, 2022. "Development of a Comprehensive Multi-Factor Method for Comparing Batting Performances in One-Day International Cricket," IIM Kozhikode Society & Management Review, , vol. 11(1), pages 92-108, January.
    7. Shah Parag, 2016. "Measuring Fielding Performance in Cricket," Polish Journal of Sport and Tourism, Sciendo, vol. 23(2), pages 113-114, June.
    8. Apurva Jha & Arpan Kumar Kar & Agam Gupta, 2023. "Optimization of team selection in fantasy cricket: a hybrid approach using recursive feature elimination and genetic algorithm," Annals of Operations Research, Springer, vol. 325(1), pages 289-317, June.
    9. 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.
    10. 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.

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