ORIGINAL ARTICLE  EXERCISE PHYSIOLOGY AND BIOMECHANICS 

The Journal of Sports Medicine and Physical Fitness 2019 October;59(10):1640-50

DOI: 10.23736/S0022-4707.19.09772-X

Copyright © 2019 EDIZIONI MINERVA MEDICA

language: English

Physical performance metrics in elite soccer: do power and acceleration metrics provide insight into positional demands and match-related fatigue in the 4-3-3 system?

Cristoforo FILETTI ¹ ✉, Bruno RUSCELLO ^{1, 2, 3}, Giampiero ASCENZI ⁴, Michele DI MASCIO ⁵, Stefano D’OTTAVIO ^{1, 6}

¹ Faculty of Medicine and Surgery, School of Sport and Exercise Sciences, Tor Vergata University, Rome, Italy; ² School of Sport and Exercise, San Raffaele University, Rome, Italy; ³ Department of Industrial Engineering, Faculty of Engineering, Tor Vergata University, Rome, Italy; ⁴ Department of Sports and Computing, Faculty of Sport Pablo de Olavide, University of Sevilla, Sevilla, Spain; ⁵ Sunderland AFC, Sunderland, UK; ⁶ FIGC - Federazione Italiana Giuoco Calcio, Rome, Italy

BACKGROUND: The aim of this study was to quantify power and acceleration metrics in elite soccer matches to gain an insight into positional demands and match-related fatigue patterns.
METHODS: Elite players (N.=212, observations =522) were analysed during 50 matches of the Italian Serie A using a semi-automatic tracking system (K-Sport, Montelabbate, Pesaro-Urbino, Italy - Stats, Leeds, UK) during the 2015/16 season. A principal component analysis (PCA) was performed to find the latent variables that better explain the huge amount of data collected; an ANOVA was performed to find differences among positional roles and a mixed factorial analysis of mixed data (FAMD) was carried out to investigate the patterns of fatigue over time.
RESULTS: Power and acceleration were defined as the latent variables out of the 19 investigated that provided most of the variance (90.39%); significant differences among roles were found (P<0.05; Effect Size (ES) as ω2>0.14) and significant patterns of fatigue (P<0.05) with a moderate to large ES were observed over time in some of the key performance indicators.
CONCLUSIONS: The data demonstrate that there are implications for developing power and acceleration in training sessions and assessing these components during a game. With the introduction of “live streaming” of GPS data, the movement patterns could be observed in real time, and interchanges could be made before the onset of fatigue and before evident reductions in performance might be observed.

KEY WORDS: Soccer; Exercise; Mentoring