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Novel Performance Metrics to Evaluate the Duel Between a Batsman and a Bowler

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  • Yamini Nekkanti
  • Dibyojyoti Bhattacharjee

Abstract

In the current system of cricket, the most commonly used measures to evaluate players’ performance are batting and bowling averages, strike rate and economy rate. While these measures are easy to compute and understand, they fail to reflect a complete picture of the players’ performance as they do not consider the context of the match. Various factors, such as balls faced and left, wickets remaining, the skill level of the opponent, etc., are not being considered while evaluating the players’ performance. In addition, these conventional measures fail to compare a batsman’s performance against that of a bowler or vice versa. The objective of this article is to arrive at a measure that will better explain the performance of the players while incorporating some of the factors as stated above. In this article, we use strike rate for the batsman and economy rate for the bowler to arrive at a common scale for ratings. Furthermore, we use the concept of Elo ratings in order to evaluate the duel between a batsman and a bowler. Based on the developed methodology, we evaluate the duels between the players in the Indian Premier League 2018 finals.

Suggested Citation

  • 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.
  • Handle: RePEc:sae:manlab:v:45:y:2020:i:2:p:201-211
    DOI: 10.1177/0258042X20912597
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    References listed on IDEAS

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    1. Lehmann, Robert & Wohlrabe, Klaus, 2017. "Who is the ‘Journal Grand Master’? A new ranking based on the Elo rating system," Journal of Informetrics, Elsevier, vol. 11(3), pages 800-809.
    2. M Carter & G Guthrie, 2004. "Cricket interruptus: fairness and incentive in limited overs cricket matches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 822-829, August.
    3. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.
    4. McHale, Ian G. & Asif, Muhammad, 2013. "A modified Duckworth–Lewis method for adjusting targets in interrupted limited overs cricket," European Journal of Operational Research, Elsevier, vol. 225(2), pages 353-362.
    5. Sohail Akhtar & Philip Scarf & Zahid Rasool, 2015. "Rating players in test match cricket," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(4), pages 684-695, April.
    6. Akhtar, Sohail & Scarf, Philip, 2012. "Forecasting test cricket match outcomes in play," International Journal of Forecasting, Elsevier, vol. 28(3), pages 632-643.
    7. 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.
    8. G D Sharp & W J Brettenny & J W Gonsalves & M Lourens & R A Stretch, 2011. "Integer optimisation for the selection of a Twenty20 cricket team," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(9), pages 1688-1694, September.
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