De Silva_sports-06-00130 (2).pdf (6.84 MB)

Player tracking data analytics as a tool for physical performance management in football: A case study from Chelsea Football Club Academy

Download (6.84 MB)
journal contribution
posted on 24.10.2018 by Varuna De Silva, Michael Caine, James Skinner, Safak Dogan, Ahmet Kondoz, Tilson Peter, Elliott Axtell, Matt Birnie, Ben Smith
Background: Global positioning system (GPS) based player movement tracking data are widely used by professional football (soccer) clubs and academies to provide insights into activity demands during training and competitive matches. However, the use of movement tracking data to inform the design of training programmes is still an open research question. Objectives: The objective of this study is to analyze player tracking data to understand the activity level differences between training and match sessions, with respect to different playing positions. Methods: This study analyses per-session summary of historical movement data collected through GPS tracking to profile high speed running activity as well as distance covered during training sessions as a whole and competitive matches. We utilize 20913 data points collected from 53 football players aged between 18-23 at an elite football academy, across four full seasons (2014-2018). Through ANOVA analysis and probability distribution analysis, we compare the activity demands, measured by the number of high speed runs, amount of high speed distance and distance covered by players in key playing positions, such as Central Midfielders, Full Backs and Centre Forwards. Results and Implications: While there are significant positional differences of physical activity demands during competitive matches, the physical activity levels during training sessions does not show positional variations. In matches, the Centre Forwards face the highest demand for HSRs, compared to Central Midfielders and Full Backs. However on average the Central Midfielders tend to cover more distance than Centre Forwards and Full Backs. An increase in high speed work demand in matches and training over the past 4 seasons, also shown by a gradual change in the extreme values of high speed running activity was also found. This large-scale, longitudinal study makes an important contribution to the literature, providing novel insights from an elite performance environment about the relationship between player activity levels during training and match play, and how these vary by playing position.



  • Loughborough University London

Published in

MDPI Sports


DE SILVA, V. ... et al, 2018. Player tracking data analytics as a tool for physical performance management in football: A case study from Chelsea Football Club Academy. Sports, 6(4): 130


MDPI AG © The Authors


NA (Not Applicable or Unknown)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: by/4.0/

Acceptance date


Publication date



This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at:







Logo branding