Functional adaptability in playing style: A key determinant of competitive football performance

HE, Qixiang, ARAÚJO, Duarte, DAVIDS, Keith, KEE, Ying Hwa and KOMAR, John (2023). Functional adaptability in playing style: A key determinant of competitive football performance. Adaptive Behavior: 1059712323.

Preview

PDF Davids-FunctionalAdaptabilityPlaying(AM).pdf - Accepted Version Creative Commons Attribution Non-commercial No Derivatives. Download (663kB) | Preview

Abstract

Purpose: The present study examined the relationship between playing style adaptability and team match performance indicators throughout the season. Three playing style adaptability metrics were analysed, namely, (1) flexibility (i.e., exhibiting a wide range of playing styles), (2) reactivity (i.e., adapting playing style based on opposition) and (3) imposition (i.e., executing predetermined playing style regardless of opposition). Methods: Team playing styles were derived through a clustering analysis of 21,708 matches played in the top five male European leagues from 2014/15 to 2019/20. Spearman’s correlation was utilized to assess the association between the three playing style adaptability metrics and four team match performance indicators (e.g., shots taken in opposition penalty box; shots conceded in own penalty box; goals scored; goals conceded; and total wins). Results: Playing style flexibility was positively associated with both offensive and defensive match performance indicators and win frequency. Conversely, playing style reactivity and imposition were negatively associated with these team match performance indicators. Conclusions: Our results suggest that the capacity to exhibit a wide range of playing styles throughout a season is associated with greater team performance. Furthermore, it is possible that high performing teams are capable of functionally switching between playing style reactivity and imposition, depending on match dynamics.

Item Type:	Article
Uncontrolled Keywords:	0801 Artificial Intelligence and Image Processing; 1701 Psychology; 1702 Cognitive Sciences; Artificial Intelligence & Image Processing; 4602 Artificial intelligence; 4608 Human-centred computing; 4611 Machine learning
Identification Number:	https://doi.org/10.1177/10597123231178942
SWORD Depositor:	Symplectic Elements
Depositing User:	Symplectic Elements
Date Deposited:	10 Jul 2023 16:10
Last Modified:	11 Oct 2023 13:31
URI:	https://shura.shu.ac.uk/id/eprint/32111

Actions (login required)

View Item

Downloads

Publication Metrics