The relative age effect in European elite soccer: A practical guide to Poisson regression modelling.

Many disciplines of scholarship are interested in the Relative Age Effect (RAE), whereby age-banding confers advantages on older members of the cohort over younger ones. Most research does not test this relationship in a manner consistent with theory (which requires a decline in frequency across the cohort year), instead resorting to non-parametric, non-directional approaches. In this article, the authors address this disconnect, provide an overview of the benefits associated with Poisson regression modelling, and two managerially useful measures for quantifying RAE bias, namely the Indices of Discrimination and Wastage.

Relative age effect in elite soccer: More early-born players, but no better valued, and no paragon clubs or countries.

The paper analyses two datasets of elite soccer players (top 1000 professionals and UEFA Under-19 Youth League). In both, we find a Relative Age Effect (RAE) for frequency, but not for value. That is, while there are more players born at the start of the competition year, their transfer values are no higher, nor are they given more game time.

Tails of the Travelling Gaussian model and the relative age effect: Tales of age discrimination and wasted talent.

The Relative Age Effect (RAE) documents the inherent disadvantages of being younger rather than older in an age-banded cohort, typically a school- or competition-year, to the detriment of career-progression, earnings and wellbeing into adulthood. We develop the Tails of the Travelling Gaussian (TTG) to model the mechanisms behind RAE. TTG has notable advantages over existing approaches, which have been largely descriptive, potentially confounded, and non-comparable across contexts.