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Comparative Analysis of TOPSIS and TODIM for the Performance Evaluation of Foreign Players in Indian Premier League

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  • Vaishnudebi Dutta
  • Subhomoy Haldar
  • Prabjot Kaur
  • Yuvraj Gajpal
  • Qingyuan Zhu

Abstract

Sports officials, players, and fans are concerned about overseas player rankings for the IPL auction. These rankings are becoming progressively essential to investors when premium leagues are commercialized. The decision-makers of the Indian Premier League choose cricketers based on their own experience in sports and based on performance statistics on several criteria. This paper presents a scientific way to rank the players. Our research examines and contrasts different multicriteria decision-making algorithms for ranking foreign players under various criteria to assess their performance and efficiency. The paper uses three MCDM algorithms, TOPSIS, TODIM, and NR-TOPSIS, for foreign players ranking in the Indian Premier League. Our analysis is limited to the batsmen and bowlers only. We perform the analysis using Python language, a popular high-level programming language. Finally, we perform a sensitivity analysis to determine the stability of each method when the weights of the criterion or the value of a parameter was changed. Our analysis exhibits the superiority of TODIM over TOPSIS and NR-TOPSIS.

Suggested Citation

  • Vaishnudebi Dutta & Subhomoy Haldar & Prabjot Kaur & Yuvraj Gajpal & Qingyuan Zhu, 2022. "Comparative Analysis of TOPSIS and TODIM for the Performance Evaluation of Foreign Players in Indian Premier League," Complexity, Hindawi, vol. 2022, pages 1-20, April.
    • Handle: RePEc:hin:complx:9986137
    DOI: 10.1155/2022/9986137
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    Cited by:

    1. Pengfei Wang & Yang Liu & Qinqin Sun & Yingqi Bai & Chaopeng Li, 2022. "Research on Data Cleaning Algorithm Based on Multi Type Construction Waste," Sustainability, MDPI, vol. 14(19), pages 1-16, September.

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