Unlocking the potential of big data to support tactical performance analysis in professional soccer: A systematic review.
Eur J Sport Sci
; 21(4): 481-496, 2021 Apr.
Article
en En
| MEDLINE
| ID: mdl-32297547
ABSTRACT
In professional soccer, increasing amounts of data are collected that harness great potential when it comes to analysing tactical behaviour. Unlocking this potential is difficult as big data challenges the data management and analytics methods commonly employed in sports. By joining forces with computer science, solutions to these challenges could be achieved, helping sports science to find new insights, as is happening in other scientific domains. We aim to bring multiple domains together in the context of analysing tactical behaviour in soccer using position tracking data. A systematic literature search for studies employing position tracking data to study tactical behaviour in soccer was conducted in seven electronic databases, resulting in 2338 identified studies and finally the inclusion of 73 papers. Each domain clearly contributes to the analysis of tactical behaviour, albeit in - sometimes radically - different ways. Accordingly, we present a multidisciplinary framework where each domain's contributions to feature construction, modelling and interpretation can be situated. We discuss a set of key challenges concerning the data analytics process, specifically feature construction, spatial and temporal aggregation. Moreover, we discuss how these challenges could be resolved through multidisciplinary collaboration, which is pivotal in unlocking the potential of position tracking data in sports analytics.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Fútbol
/
Rendimiento Atlético
/
Macrodatos
/
Análisis de Datos
Tipo de estudio:
Systematic_reviews
Límite:
Humans
Idioma:
En
Año:
2021
Tipo del documento:
Article