On the ranking of Test match batsmen

06/14/2018
by   Richard J. Boys, et al.
0

Ranking sportsmen whose careers took place in different eras is often a contentious issue and the topic of much debate. In this paper we focus on cricket and examine what conclusions may be drawn about the ranking of Test batsmen using data on batting scores from the first Test in 1877 onwards. The overlapping nature of playing careers is exploited to form a bridge from past to present so that all players can be compared simultaneously, rather than just relative to their contemporaries. The natural variation in runs scored by a batsman is modelled by an additive log-linear model with year, age and cricket-specific components used to extract the innate ability of an individual cricketer. Incomplete innings are handled via censoring and a zero-inflated component is incorporated into the model to allow for an excess of frailty at the start of an innings. The innings-by-innings variation of runs scored by each batsman leads to uncertainty in their ranking position. A Bayesian approach is used to fit the model and realisations from the posterior distribution are obtained by deploying a Markov Chain Monte Carlo algorithm. Posterior summaries of innate player ability are then used to assess uncertainty in ranking position and this is contrasted with rankings determined via the posterior mean runs scored. Posterior predictive checks show that the model provides a reasonably accurate description of runs scored.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/01/2021

A truncated mean-parameterised Conway-Maxwell-Poisson model for the analysis of Test match bowlers

Assessing the relative merits of sportsmen and women whose careers took ...
research
02/09/2018

Bayesian inference for bivariate ranks

A recommender system based on ranks is proposed, where an expert's ranki...
research
06/13/2020

Faster MCMC for Gaussian Latent Position Network Models

Latent position network models are a versatile tool in network science; ...
research
12/11/2019

Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection

Despite their successes, deep neural networks still make unreliable pred...
research
10/17/2022

A Mixing Time Lower Bound for a Simplified Version of BART

Bayesian Additive Regression Trees (BART) is a popular Bayesian non-para...
research
03/22/2021

Modelling intransitivity in pairwise comparisons with application to baseball data

In most commonly used ranking systems, some level of underlying transiti...
research
07/10/2019

Bayesian inferences on uncertain ranks and orderings

It is common to be interested in rankings or order relationships among e...

Please sign up or login with your details

Forgot password? Click here to reset