Abstract Pillitteri, G, Clemente, FM, Petrucci, M, Rossi, A, Bellafiore, M, Bianco, A, Palma, A,
and Battaglia, G. Toward a new conceptual approach to “intensity” in soccer player's …

The aim of this study was to test a machine learning (ML) model to predict high-intensity
actions and body impacts during youth football training. Sixty under-15,-17, and-19 sub-elite …

Different long-term exposure to match-play might have implications for maintaining the
collective fitness levels within a football team. However, there is a lack of clarity regarding …

The aims of this study were to analyze the effects of a congested period (three games in four
days) on countermovement (CMJ) jump-landing metrics, heart rate variability (HRV), and …

Applying data-reduction techniques to extract meaningful information from electronic
performance and tracking systems (EPTS) has become a hot topic in football training load …

Introduction The application of muscle force is a determinant of football success as it is
inherent to the motor control and sport. The aims of this study are:(1) to describe force …

This study compared weekly training-load (TL), training-monotony (TM), and training-strain
(TS) in 80 professional football players (28.1±3.2 yrs, 78.0±5.9 kg, and 182.0±4.8 cm) …

Introduction A promising approach to optimizing recovery in youth football has been the use
of machine learning (ML) models to predict recovery states and prevent mental fatigue. This …

Utilizing techniques for reducing multivariate data is essential for comprehensively
understanding the variations and relationships within both biomechanical and physiological …

Esta investigación tuvo como objetivo analizar los efectos fijos y aleatorios durante el
entrenamiento de la carga física con respecto a la posición de juego, según el tipo de …