Influential Factors in Successful Run Chases in T20 International Cricket: A Statistical and Predictive Analysis

Abstract

This study investigates the factors influencing successful run chases in T20 International cricket using data from 458 limited-overs matches. Variables such as innings scores, toss outcomes, and venue characteristics were analysed. Correlation analysis revealed significant relationships between first-innings scores and match outcomes, while the Shapiro-Wilk normality test indicated that second-innings scores deviate from normality, impacts model selection. Logistic regression identified batting order and match conditions as key predictors of run chasing success. The model demonstrated stability, evidenced by low variance inflation factors, and achieved high predictive accuracy validated by metrics including the area under the curve (AUC), precision, and F1 score. Findings indicate that a stable top order, favourable match conditions, and winning the toss significantly enhance the likelihood of successful chases. Additionally, strong middle orders and adaptive strategies contribute to overcoming high first-innings scores. Future research should focus on machine learning applications to explore complex variable interactions and the influence of psychological factors on run chases.