MacGabhann, Stephen, Waddington, Gordon, Witchalls, Jeremy, Cobley, Stephen, Dowse, Rebecca and Newman, Phillip (2026) Multisensory assessment and machine learning for athlete classification in talent identification. Journal of Science and Medicine in Sport. (In Press)

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Abstract

Background
Talent identification in elite sport is challenged by maturation confounding and limited objective assessment tools. This preliminary study examined whether visual-vestibular-somatosensory and autonomic (VVS-A) measures distinguished podium-level from entry-level divers using machine learning.
Objectives
(1) Identify VVS-A features distinguishing podium-level divers from a Come and Try group using traditional statistical comparisons; (2) evaluate machine-learning models' ability to classify podium-level athletes; and (3) examine the distribution of classification probabilities using lift-curve analysis.
Design
Cross-sectional exploratory study with machine-learning classification.
Methods
Sixty participants from an Olympic diving talent identification programme underwent VVS-A assessment. Somatosensory function was evaluated via ankle proprioception using the AMEDA device. Visual, vestibular, and autonomic functions were assessed using the Prism-Neuro Eye system. Group differences were examined using independent-sample Student's t-tests. Supervised ML models were trained on selected VVS-A measures and evaluated using cross-validation and a held-out test set.
Results
Podium-level athletes demonstrated superior ankle proprioception (Left: p < 0.001, d = 1.57; Right: p < 0.001, d = 1.83) and visual-vestibular smooth pursuit (p = 0.001, r = 0.51). No group differences were observed for voluntary saccades or autonomic metrics. A calibrated Ridge Logistic Regression model classified podium-level athletes with high accuracy within this sample (94.4%; AUC = 0.889).
Conclusions
Selected VVS-A measures were associated with differences in current performance level in Olympic diving. However, the cross-sectional design, age differences between groups, and limited sample size preclude conclusions regarding predictive validity, necessitating longitudinal sport-specific validation before informing applied practice within talent identification contexts.

Item Type:	Article
Status:	In Press
DOI:	10.1016/j.jsams.2026.03.011
School/Department:	School of Science, Technology and Health
URI:	https://ray.yorksj.ac.uk/id/eprint/14616

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