  In the sport of cricket, player batting ability is traditionally measured
using the batting average. However, the batting average fails to measure both
short-term changes in ability that occur during an innings, and long-term
changes that occur between innings, due to the likes of age and experience in
various match conditions. We derive and fit a Bayesian parametric model that
employs a Gaussian process to measure and predict how the batting abilities of
cricket players vary and fluctuate over the course of entire playing careers.
The results allow us to better quantify and predict player batting ability,
compared with both traditional cricket statistics, such as the batting average,
and more complex models, such as the official International Cricket Council
ratings.
