An Augmented Rating System for Test cricket: adapting Glicko's model

TL;DR

This paper introduces an improved cricket team rating system that incorporates contextual factors and margin of victory, resulting in more accurate and fair team rankings.

Contribution

It develops an augmented Glicko-based model that accounts for home advantage, toss impact, scheduling, and margin of victory in Test cricket rankings.

Findings

Enhanced expected score estimation and predictive accuracy.

Ratings are stable across different match schedules.

Framework offers a fairer, statistically consistent ranking method.

Abstract

ICC's current ranking system does not adequately account for key contextual factors such as home advantage, toss impact and scheduling imbalances; leading to inconsistencies in team evaluation in Test cricket. This study develops an enhanced rating framework by adapting and enhancing Glicko's model to incorporate these influences alongside Margin of Victory, an important indicator of dominance a contest. This enables a more dynamic and probabilistically grounded assessment of team performance. Using past match data, the model demonstrates improved expected score estimation and predictive accuracy. Robustness of the resulting ratings is demonstrated through bootstrap resampling, confirming stability with respect to match scheduling. Overall, the framework provides a fairer and more statistically consistent approach to ranking Test teams.