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Cricket Team Selection Using Evolutionary Multi-objective Optimization

  • Faez Ahmed
  • Abhilash Jindal
  • Kalyanmoy Deb
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7077)

Abstract

Selection of players for a high performance cricket team within a finite budget is a complex task which can be viewed as a constrained multi-objective optimization problem. In cricket team formation, batting strength and bowling strength of a team are the major factors affecting its performance and an optimum trade-off needs to be reached in formation of a good team. We propose a multi-objective approach using NSGA-II algorithm to optimize overall batting and bowling strength of a team and find team members in it. Using the information from trade-off front, a decision making approach is also proposed for final selection of team. Case study using a set of players auctioned in Indian Premier League, 4th edition has been taken and player’s current T-20 statistical data is used as performance parameter. This technique can be used by franchise owners and league managers to form a good team within budget constraints given by the organizers. The methodology is generic and can be easily extended to other sports like soccer, baseball etc.

Keywords

Knee Point Knee Region Good Team Batting Average Optimal Team 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Faez Ahmed
    • 1
  • Abhilash Jindal
    • 1
  • Kalyanmoy Deb
    • 1
  1. 1.Kanpur Genetic Algorithms Laboratory (KanGAL)Indian Institute of Technology, KanpurKanpurIndia

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