IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v53y2016i2d10.1007_s12597-015-0228-3.html
   My bibliography  Save this article

An objective approach of balanced cricket team selection using binary integer programming method

Author

Listed:
  • Dibyojyoti Bhattacharjee

    (Assam University)

  • Hemanta Saikia

    (Kaziranga University)

Abstract

Selecting a balanced playing XI in the game of cricket with the right mix of players of different specialization is a difficult decision making problem for the team management. To make the process more objective, optimization techniques can be applied to the process of selection of players from a given squad. Such an exercise has two dimensions. First, a suitable tool for performance measurement of cricketers needs to be defined. Secondly, for selecting a balanced team of XI players, an appropriate objective function and some constraints need to be formulated. Since the captain gets an obvious inclusion in the cricket team, the area specialization of the captain influences the selection of other ten positions in the playing XI. This study attempts to select the optimum balanced playing XI from a squad of players given the specialization of the captain using binary integer programming. To validate the exercise, data from the fifth season of the Indian Premier League has been used.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:opsear:v:53:y:2016:i:2:d:10.1007_s12597-015-0228-3
    DOI: 10.1007/s12597-015-0228-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-015-0228-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12597-015-0228-3?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. 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.
    2. A J Lewis, 2005. "Towards fairer measures of player performance in one-day cricket," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(7), pages 804-815, July.
    3. 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.
    4. Boon, Bart H. & Sierksma, Gerard, 2003. "Team formation: Matching quality supply and quality demand," European Journal of Operational Research, Elsevier, vol. 148(2), pages 277-292, July.
    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. Praveen Puram & Soumya Roy & Deepak Srivastav & Anand Gurumurthy, 2023. "Understanding the effect of contextual factors and decision making on team performance in Twenty20 cricket: an interpretable machine learning approach," Annals of Operations Research, Springer, vol. 325(1), pages 261-288, June.
    2. Smith Zachary J. & Bickel J. Eric, 2023. "A roster construction decision tool for MLS expansion teams," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 19(1), pages 1-14, March.
    3. 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.
    4. 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.

    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. 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.
    2. Espitia-Escuer, Manuel A. & García-Cebrián, Lucía Isabel, 2012. "Diversificación en la configuración de los equipos de la primera división española de fútbol/Diversification in the Team Configuration of the Spanish Football First Division," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 30, pages 527-544, Agosto.
    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. Ian G. McHale & Philip A. Scarf & David E. Folker, 2012. "On the Development of a Soccer Player Performance Rating System for the English Premier League," Interfaces, INFORMS, vol. 42(4), pages 339-351, August.
    5. Subhasis Ray, 2021. "Identification of Research Paradigms for Managing the Cricketing Ecosystem Using Stakeholder Analysis and Text Mining," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 46(3), pages 289-312, August.
    6. Shah Parag, 2016. "Measuring Fielding Performance in Cricket," Polish Journal of Sport and Tourism, Sciendo, vol. 23(2), pages 113-114, June.
    7. 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.
    8. 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.
    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. Jarvandi Ali & Sarkani Shahram & Mazzuchi Thomas, 2013. "Modeling team compatibility factors using a semi-Markov decision process: a data-driven approach to player selection in soccer," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(4), pages 347-366, December.
    11. 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.
    12. 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.
    13. Ajit Karnik, 2010. "Valuing Cricketers Using Hedonic Price Models," Journal of Sports Economics, , vol. 11(4), pages 456-469, August.
    14. Akhtar, Sohail & Scarf, Philip, 2012. "Forecasting test cricket match outcomes in play," International Journal of Forecasting, Elsevier, vol. 28(3), pages 632-643.
    15. Nihal Berktaş & Hande Yaman, 2021. "A Branch-and-Bound Algorithm for Team Formation on Social Networks," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1162-1176, July.
    16. Pantuso Giovanni, 2017. "The Football Team Composition Problem: a Stochastic Programming approach," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(3), pages 113-129, September.
    17. Chitresh Kumar & Girish Balasubramanian, 2023. "Comparative Analysis of Pitch Ratings in All Formats of Cricket," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 48(3), pages 307-324, August.
    18. David Boto-Garcìa & Alessandro Bucciol & Luca Zarri, 2020. "Managerial Beliefs and Firm Performance: Field Evidence from Professional Elite Soccer," Working Papers 19/2020, University of Verona, Department of Economics.
    19. David Van Bulck & Arthur Vande Weghe & Dries Goossens, 2023. "Result-based talent identification in road cycling: discovering the next Eddy Merckx," Annals of Operations Research, Springer, vol. 325(1), pages 539-556, June.
    20. Peng, Zixuan & Shan, Wenxuan & Zhu, Xiaoning & Yu, Bin, 2022. "Many-to-one stable matching for taxi-sharing service with selfish players," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 255-279.

    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:spr:opsear:v:53:y:2016:i:2:d:10.1007_s12597-015-0228-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.