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Evaluating the Performance of Test Cricket Players Using Principal Component Analysis and the Weighted Average Method

  1. Arjun Prakash Mane Manav Rachna International Institute of Research and Studies, Faridabad
  2. Jaydip Yuvaraj Patil SNBP College of Arts, Commerce, Science and Management of Studies, Pune

Abstract

This study evaluates cricket player performance using Principal Component Analysis (PCA) and a weighted average approach. In order to achieve this, we analyzed detailed batting and bowling datasets from the International Cricket Council (ICC) to calculate player performance based on various performance indicators. The datasets included comprehensive statistics from multiple matches and tournaments, allowing for an in-depth evaluation of players’ skills and contributions. PCA ranked players according to their participation level, with the first three principal components accounting for nearly 90% of the data's variability, which demonstrates the robustness of the approach in capturing the majority of information inherent in the data. Our analysis reveals Sachin Tendulkar and Muthaiya Muralidharan as top-ranked batsmen and bowlers, respectively, based on the combined assessment of their performance metrics. This study provides a comprehensive evaluation of cricket player performance, highlighting the effectiveness of both PCA and weighted average approaches in producing accurate and meaningful rankings. The findings clearly demonstrate the applicability of this methodology in selecting the best cricket squad, while also offering detailed insights into the strengths and weaknesses of top players. Overall, this research makes a significant contribution to the field of sports analytics by providing a robust and reliable framework for evaluating cricket player performance. The study further informs decision-making processes in team selection and strategy development, supporting coaches, analysts, and managers in making data-driven choices for optimizing team performance and achieving competitive success.

Keywords

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