Maturity-based correction mechanism for talent identification: When is it needed, does it work, and does it help to better predict who will make it to the pros? - Charbonnet, B.; Sieghartsleitner, R.; Schmid, J.; Zuber, C.; Zibung, M.; Conzelmann, A. (Journal of Sports Science & Medicine, 2022)
When identifying talent, the confounding influence of maturity status on motor performances is an acknowledged problem. To solve this problem, correction mechanisms have been proposed to transform maturity-biased test scores into maturity-unbiased ones. Whether or not such corrections also improve predictive validity remains unclear. To address this question, we calculated correlations between maturity indicators and motor performance variables among a sample of 121 fifteen-year-old elite youth football players in Switzerland. We corrected motor performance scores identified as maturity-biased, and we assessed correction procedure efficacy. Subsequently, we examined whether corrected scores better predicted levels of performance achievement 6 years after data collection (47 professionals vs. 74 non-professional players) compared with raw scores using point biserial correlations, binary logistic regression models, and DeLong tests. Expectedly, maturity indicators correlated with raw scores (0.16 = | r | = 0.72; ps < 0.05), yet not with corrected scores. Contrary to expectations, corrected scores were not associated with an additional predictive benefit (univariate: no significant r-change; multivariate: 0.02 = ?AUC = 0.03, ps > 0.05). We do not interpret raw and corrected score equivalent predictions as a sign of correction mechanism futility (more work for the same output); rather we view them as an invitation to take corrected scores seriously into account (same output, one fewer problem) and to revise correction-related expectations according to initial predictive validity of motor variables, validity of maturity indicators, initial maturity-bias, and selection systems. Recommending maturity-based corrections is legitimate, yet currently based on theoretical rather than empirical (predictive) arguments.