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Ranking sportsmen whose careers took place in different eras is often acontentious issue and the topic of much debate. In this paper we focus oncricket and examine what conclusions may be drawn about the ranking of Testbatsmen using data on batting scores from the first Test in 1877 onwards. Theoverlapping nature of playing careers is exploited to form a bridge from pastto present so that all players can be compared simultaneously, rather than justrelative to their contemporaries. The natural variation in runs scored by abatsman is modelled by an additive log-linear model with year, age andcricket-specific components used to extract the innate ability of an individualcricketer. Incomplete innings are handled via censoring and a zero-inflatedcomponent is incorporated into the model to allow for an excess of frailty atthe start of an innings. The innings-by-innings variation of runs scored byeach batsman leads to uncertainty in their ranking position. A Bayesianapproach is used to fit the model and realisations from the posteriordistribution are obtained by deploying a Markov Chain Monte Carlo algorithm.Posterior summaries of innate player ability are then used to assessuncertainty in ranking position and this is contrasted with rankings determinedvia the posterior mean runs scored. Posterior predictive checks show that themodel provides a reasonably accurate description of runs scored.

On the ranking of Test match batsmen