AI RESEARCH
Simulation-Based Optimisation of Batting Order and Bowling Plans in T20 Cricket
arXiv CS.LG
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ArXi:2604.13861v1 Announce Type: new This paper develops a unified Marko Decision Process (MDP) framework for optimising two recurring in-match decisions in T20 cricket namely batting order selection and bowling plan assignment, directly in terms of win and defend probability rather than expected runs. A three-phase player profile engine (Powerplay, Middle, Death) with James-Stein shrinkage is estimated from 1,161 IPL ball-by-ball records (2008-2025). Win/defend probabilities are evaluated by vectorised Monte Carlo simulation over N = 50,000 innings trajectories.