A framework for test measurement selection in athlete physical preparation

Preparing athletes for competition requires the diagnosis and monitoring of relevant physical qualities (e.g., strength, power, speed, endurance characteristics). Decisions regarding test selection that attempt to measure these physical attributes are fundamental to the training process yet are complicated by the myriad of tests and measurements available. This article presents an evidenced based process to inform test measurement selection for the physical preparation of athletes. We describe a method for incorporating multiple layers of validity to link test measurement to competition outcome. This is followed by a framework by which to evaluate the suitability of test measurements based on contemporary validity theory that considers technical, decision-making, and organisational factors. Example applications of the framework are described to demonstrate its utility in different settings. The systems presented here will assist in distilling the range of measurements available into those most likely to have the greatest impact on competition performance

The influence of age-policy changes on the relative age effect across the Australian Rules football talent pathway

Objectives: To identify the influence of age-policy changes on the relative age effect (RAE) across the Australian Football League (AFL) talent pathway. Design: Retrospective cross-sectional analysis of junior AFL players attending the National Draft (National), State, and State Under 16s (U16) combines between 1999–2016. Methods: Birth-date data was obtained for players attending the AFL State U16 (n = 663, age: 15.9 ± 0.4 years), State (n = 803, age: 19.1 ± 1.7 years), National (n = 1111, age: 18.3 ± 0.8 years) combines. Corresponding aged-matched Australian general population birth rate data was also collected. Results: A chi-squared analysis comparing birth month distributions found all combine groups differed significantly from the general population (Under 16s: χ2 = 62.61, State: χ2 = 38.83, National: χ2 = 129.13, p < 0.001). Specifically, Under 16s had greater birth frequencies for months January to March (≥2%, p < 0.05), with more State players born in January (4.9%, p < 0.05). Age-policy changes at the National level reduced birth distribution bias for some months, however the RAE remained for March, June and July (3.9%, 6.1%, 4.3%, p < 0.05). State U16s and National players had 2–9% lower birth frequencies for November–December births compared general population. Conclusions: Selection bias exists towards older players is present at the AFL’s State U16, and is maintained at State and National level combines. Age-policy changes are only partially successful at addressing the RAE at the National level, with alternative strategies also recommended in order to address the RAE across the AFL talent pathways.No Full Tex