Data-Driven Strategies for Enhancing Performance in Indian Premier League: A Case Study of Royal Challengers Bangalore

The main objective of any sports team is consistently winning, and cricket is no exception. The Indian Premier League (IPL) is a highly viewed, competitive, and professional league with significant investments made to ensure team success. The Royal Challengers Bangalore (RCB) is a founding team of the IPL with a large fan base and a roster of talented players. However, they have been plagued by inconsistency in their performance over the years. This research aims to devise strategies to increase RCB’s win rate by analyzing crucial factors that contribute to its success.Ball-by-ball data for IPL seasons from 2008 to 2022 was utilized to identify the most important factors for RCB’s victory.. Firstly, Quantitative features were filtered, qualitative features excluded, and correlation with the target variable was determined. Missing data and outliers were handled, and the dataset was split into training and testing sets. Machine learning algorithms were applied to forecast team win percentages while considering key attributes of a cricket match. The machine learning models employed include Linear Regression, Support Vector Classifier (SVC), Gaussian Naive Bayes, Decision Tree, Random Forest, and Extreme Gradient Boosting (XGB).The study identified the most influential attributes for RCB’s win percentage in the following order: 1) Bowling second innings middle overs economy, 2) Batting second innings death overs strike rate, 3) Net first innings boundary percentage, 4) Bowling first innings strike rate, 5) Bowling second innings strike rate, 6) Batting first innings average, 7) Bowling second innings powerplay overs strike rate, 8) Bowling middle overs average, 9) Batting second innings average, 10) Batting second innings death average, 11) Batting first innings middle overs strike rate, and 12) Bowling first innings bowling average.The findings of this study can be used by RCB’s recruiting and scouting teams to make informed decisions about player signings. By considering advanced statistics like boundary percentage and focusing on the phase in which a player operates, a better evaluation of player performance in T20 cricket can be achieved. The paper highlights the need to revamp traditional methods of valuing players and emphasizes the essential factors that teams should focus on to win IPL matches.