Table 1_Deployability of machine-learning prediction models in elite and high-level team sports: a task-specific systematic review.xlsx

Pre-adjudication agreement for the overall DPV classification was 85/87 (97.7%; κ = 0.968; linearly weighted κ = 0.978), whilst domain-level exact agreement ranged from 75/87 to 87/87. In post hoc sensitivity analyses, 19/55 Core units met the primary DPV threshold and had Sufficient validation; 14/55 met the primary threshold and had at least partial evidence of predictive reliability or probability-quality; and 9/55 met the primary threshold and both additional conditions.

PROBAST risk of bias was High for 56/78 units, Unclear for 21/78, and Low for one. The main limitations were evaluation designs that did not adequately reflect intended future use and limited assessment of predictive reliability. Overall, the evidence supports selective methodological readiness rather than general deployability, with different requirements for pre-game, in-game, and athlete-monitoring applications.</p>Systematic review registration<p>crd.york.ac.uk/PROSPERO/view/CRD420261425179, identifier CRD420261425179.</p>