@Article{Laterza2026,
journal="Biology of Sport",
issn="0860-021X",
year="2026",
title="An innovative RPE-based approach using machine learning to analyse starter and substitute training load in soccer",
abstract=" Current methods to distinguish starters from substitutes are typically based on playing time. Not  considering the physical demands and internal load of different positions can lead to ineffective training and  recovery	protocols.	The	aim	of	this	study	was	to	examine	whether	a k-means	clustering	approach	applied	to	 session-RPE	can	generate	role-specific	thresholds	that	meaningfully	differentiate	match	load	profiles	between	 starters	and	substitutes.	We	analysed	1,450 player-matches	from	four	professional	Italian	Serie	A teams,	using	 video match analysis to measure total distance (TD) and high-intensity activities: metabolic power events (MPE),  high-speed running (HSR), and sprint running (SR). Players were divided based on the role as follows: forwards  (FWs),	midfielders	(MFs),	full-backs	(FBs),	and	centre-backs	(CBs).	Individualized	sRPE	zones	(low,	medium,	high)	 were	identified	with	the	K-means	clustering	approach	discriminating	starters	from	substituted.	FWs,	MFs,	and	 FBs were considered substituted, and compensatory training was recommended when the sRPE was within the  medium	sRPE	zone	or	lower	(FWs ≤ 695 a.u.,	MFs ≤ 711 a.u.,	and	FBs ≤ 726 a.u.).	Compensatory	training	 particularly	focused	on	SR	was	recommended	at	sRPE =	low	for	FWs	(≤ 326.1 a.u.),	and	at	a sRPE ≤ medium	 for MFs (≤ 711 a.u.).	CBs	were	defined	as	starters	when	reporting	sRPE	values ≥	medium	sRPE	(\> 446 a.u.),	 and	SR	training	was	always	recommended.	The	proposed	sRPE-based	k-means	approach	distinguishes	fatigued	 from non-fatigued players, guiding decisions about who should prioritise recovery. Role-specific sprint  recommendations help coaches provide appropriate high-velocity exposure to prevent hamstring injuries. ",
author="Laterza, Francesco
and Chamari, Karim
and Caminiti, Giuseppe
and Annino, Giuseppe
and Beato, Marco
and Bovenzi, Antonio
and D’Onofrio, Rosario
and Manzi, Vincenzo",
pages="1473--1485",
doi="10.5114/biolsport.2026.162046",
url="http://dx.doi.org/10.5114/biolsport.2026.162046"
}