Can we really predict injuries in team sports?

• Dae-Jin Lee ^[1] ; Lore Zumeta-Olaskoaga ^[2]
  1. [1] BCAM-Basque Center for Applied Mathematics
  2. [2] Universidad del Pa´ıs Vasco (UPV/EHU)
• Localización: BEIO, Boletín de Estadística e Investigación Operativa, ISSN 1889-3805, Vol. 38, Nº. 3, 2022
• Idioma: inglés
• Enlaces
  • Texto completo (pdf)
• Resumen

  • In the last decade several works have emerged in which statistical and machine learning methods have been proposed for the prediction of sports injuries. The field of medicine and sports science has included in its area multidisciplinary profiles with expertise in data analysis, injury epidemiology or artificial intelligence. However, injury phenomena are very complex and multifactorial. Understanding the mechanisms that produce an injury remains extremely complex and requires expert knowledge.

    This paper aims to illustrate from a statistical perspective what challenges need to be addressed from data collection, analysis of athlete performance and scientific reflection on questions of interest for knowledge-based decision making in data analysis in sport.