Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Contextualised high-intensity running profiles of elite football players with reference to general and specialised tactical roles

Ju, W, Doran, DA, Hawkins, R, Evans, M, Laws, A and Bradley, P (2022) Contextualised high-intensity running profiles of elite football players with reference to general and specialised tactical roles. Biology of Sport, 40 (1). pp. 291-301. ISSN 0860-021X

BS_Art_46976-10.pdf - Published Version
Available under License Creative Commons Attribution Share Alike.

Download (1MB) | Preview


The present study aimed to contextualise physical metrics with tactical actions according to general and specialised tactical roles. A total of 244 English Premier League players were analysed by coding player’s physical-tactical actions via the fusion of tracking data and video. Data were analysed across 5 general (Central Defensive Players = CDP, Wide Defensive Players = WDP, Central Midfield Players = CMP, Wide Offensive Players = WOP, Central Offensive Players = COP) and 11 specialised positions (Centre Backs = CB, Full-Backs = FB, Wing-Backs = WB, Box-to-Box Midfielders = B2BM, Central Defensive Midfielders = CDM, Central Attacking Midfielders = CAM, Wide Midfielders = WM, Wide Forwards = WF, Centre Forwards = CF). COP covered more distance at high-intensity (> 19.8 km· h-1) when performing actions such as ‘Break into Box’, Run in Behind/Penetrate’, and ‘Close Down/Press’ than other positions (ES: 0.6–5.2, P < 0.01). WOP covered more high-intensity ‘Run with Ball’ distance (ES: 0.7–1.7, P < 0.01) whereas WDP performed more ‘Over/Underlap’ distance than other positions (ES: 0.9–1.4, P < 0.01). CDP and WDP covered more high-intensity ‘Covering’ distances than other positions (ES: 0.4–2.4, P < 0.01). Nonetheless, data demonstrated that implementing specialised positional analysis relative to a generalised approach is more sensitive in measuring physical-tactical performances of players with the latter over or underestimating the match demands of the players compared to the former. A contextualised analysis may assist coaches and practitioners when designing position or even player-specific training drills since the data provides unique physical-tactical trends across specialised roles.

Item Type: Article
Uncontrolled Keywords: Sport Sciences; 1106 Human Movement and Sports Sciences
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine > RC1200 Sports Medicine
Divisions: Computer Science & Mathematics
Sport & Exercise Sciences
Publisher: Termedia Sp. z.o.o.
SWORD Depositor: A Symplectic
Date Deposited: 06 Jul 2022 09:56
Last Modified: 06 Jul 2022 10:00
DOI or ID number: 10.5114/biolsport.2023.116003
URI: https://researchonline.ljmu.ac.uk/id/eprint/17199
View Item View Item