@Article{Benéitez-Andrés2026,
journal="Biology of Sport",
issn="0860-021X",
year="2026",
title="The influence of contextual factors on the physical demands of 
soccer match-play",
abstract="This observational longitudinal study examined the impact of six contextual on the match demands of professional soccer players using Principal Component Analysis (PCA). Data were collected from 17 male	players	across	37 official	matches	(September	2023–May	2024)	of	a Tier	3 Spanish	team,	utilizing	10 Hz	GPS	units.	PCA,	combined	with	hierarchical	cluster	analysis,	effectively	reduced	the	17 initial	external	load	metrics	to	eight	representative	variables,	optimizing	relevant	information	and	minimizing	redundancy	inherent in performance monitoring systems. Six contextual factors (match outcome, location, player position, goal	difference,	halftime	score	evolution,	and	competitive	block)	were	analyzed	for	their	influence	using	ANOVA.	Results	indicated	that	player	position	was	the	most	influential	variable	(p ≤ 0.001,	large	effect	sizes),	significantly	affecting	all	external	load	metrics,	with	distinct	profiles	for	forwards,	midfielders,	and	defenders.	Specifically,	forwards	excelled	in	high-intensity	actions;	midfielders	recorded	higher	values	in	medium-intensity	distances	and decelerations, while defenders consistently exhibited the lowest overall physical demands. Match location significantly	influenced	high-intensity	distance	and	decelerations	(higher	at	home,	small	effect	sizes).	The	competitive	block	showed	a significant	effect	only	on	low-intensity	distance,	peaking	during	intermediate	periods,	suggesting	that	effective	load	management	strategies	mitigated	fluctuations	in	high-intensity	activity.	Conversely,	match	outcome,	goal	difference,	and	score	difference	evolution	had	no	significant	effects	on	most	physical	demands.	This	study	confirms	player	position	as	the	predominant	contextual	factor	and	highlights	the	utility	of	PCA	in	refining	load	monitoring.	Practical	applications	include	individualized	training	regimens	tailored	to	positional	demands	and	optimized	monitoring	strategies	for	efficient	performance	analysis.",
author="Benéitez-Andrés, Enrique
and Sánchez-Sánchez, Javier
and Rodríguez-Fernández, Alejandro
and Sánchez-Barba, Mercedes
and Rojas-Valverde, Daniel
and Sánchez, Mario",
pages="729--741",
doi="10.5114/biolsport.2026.157995",
url="http://dx.doi.org/10.5114/biolsport.2026.157995"
}