Predicting the Unpredictable

A predictive model learns the pathway that produced its training data, and in youth sport that pathway is already bent by relative age, early maturation and early selection. Pointed at 12-year-olds, such a model reproduces those distortions with more confidence and less visibility than a human selector would. This paper sets the evidence on athlete development, where the overwhelming majority of elite pathways are non-linear and junior and senior predictors run in opposite directions, against the assumptions of supervised learning, which require a stable world, a representative sample and a meaningful label. It identifies three routes of inherited error in drift, sampling and labels, noting that using selection as a proxy for talent writes the bias into the target itself. It then addresses performativity, since a score that shapes a deselection has become part of the treatment, and a model retrained on the result measures its own influence and calls it accuracy. Five reporting rules follow, covering current status, uncertainty, maturation context, individual change over time, and no verdict below mid-adolescence. Procurement, not the individual club, is identified as the practical lever.