Class handicapping methods enable different classes of athletes to compete on equal terms. Different sports use a variety of algorithms, which are usually based on historical data and subjective opinions. A recent proposal is to use an interactive shrinkage method for class handicapping, as this is generic across sports and uses data from the current competition only. This article presents a mathematical justification of the interactive shrinkage method for class handicapping, based on an objective Bayesian analysis of a suitable probability model. It also investigates how this approach performs in the context of paralympic sports, by analysing actual competition data and comparing the results with those from existing schemes. Our findings suggest that this method is robust, convenient and fair. A discussion follows, to explore possible extensions of this procedure.