Stochastic differential theory of cricket

TL;DR

This paper introduces a stochastic differential equation framework to model cricket game progression, providing a quantitative and physically meaningful representation of teams and a novel method to calculate winning probabilities over time.

Contribution

The paper presents a new SDE-based formalism for cricket analysis, contrasting with traditional statistical ratings, and offers a method to compute winning probabilities as the game progresses.

Findings

Quantitative team representation with three key variables.

New method to calculate winning probability over balls.

Formalism offers physical interpretability.

Abstract

A new formalism for analyzing the progression of cricket game using Stochastic differential equation (SDE) is introduced. This theory enables a quantitative way of representing every team using three key variables which have physical meaning associated with them. This is in contrast with the traditional system of rating/ranking teams based on combination of different statical cumulants. Further more, using this formalism, a new method to calculate the winning probability as a progression of number of balls is given.