CAMP: A Context-Aware Cricket Players Performance Metric

TL;DR

CAMP is a novel context-aware performance metric for cricket that accurately evaluates individual contributions by considering game circumstances, outperforming existing methods and aligning closely with expert judgments.

Contribution

This paper introduces CAMP, a new data-driven, context-aware metric for assessing cricket players' performance, incorporating game circumstances and outperforming existing measures.

Findings

CAMP's top-rated players match expert-selected Man of the Match in 83% of games.

CAMP outperforms the DLS method in evaluating player contributions.

Empirical evaluation on 961 matches demonstrates CAMP's effectiveness.

Abstract

Cricket is the second most popular sport after soccer in terms of viewership. However, the assessment of individual player performance, a fundamental task in team sports, is currently primarily based on aggregate performance statistics, including average runs and wickets taken. We propose Context-Aware Metric of player Performance, CAMP, to quantify individual players' contributions toward a cricket match outcome. CAMP employs data mining methods and enables effective data-driven decision-making for selection and drafting, coaching and training, team line-ups, and strategy development. CAMP incorporates the exact context of performance, such as opponents' strengths and specific circumstances of games, such as pressure situations. We empirically evaluate CAMP on data of limited-over cricket matches between 2001 and 2019. In every match, a committee of experts declares one player as the best player, called Man of the M}atch (MoM). The top two rated players by CAMP match with MoM in 83\% of the 961 games. Thus, the CAMP rating of the best player closely matches that of the domain experts. By this measure, CAMP significantly outperforms the current best-known players' contribution measure based on the Duckworth-Lewis-Stern (DLS) method.