The Role of Veracity on the Load Monitoring of Professional Soccer Players: A Systematic Review in the Face of the Big Data Era

• Published in: Applied sciences Vol. 11; no. 14; p. 6479
• Main Authors: Claudino, João Gustavo, Cardoso Filho, Carlos Alberto, Boullosa, Daniel, Lima-Alves, Adriano, Carrion, Gustavo Rejano, GianonI, Rodrigo Luiz da Silva, Guimarães, Rodrigo dos Santos, Ventura, Fúlvio Martins, Araujo, André Luiz Costa, Del Rosso, Sebastián, Afonso, José, Serrão, Julio Cerca
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-07-2021
• Subjects: Accuracy; Big Data; data analytics; Datasets; fitness; illness; Injuries; injury; Monitoring; Physical fitness; Professional soccer; recovery; Reviews; Soccer; Standard deviation; Systematic review
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app11146479

Big Data has real value when the veracity of the collected data has been previously identified. However, data veracity for load monitoring in professional soccer players has not been analyzed yet. This systematic review aims to evaluate the current evidence from the scientific literature related to data veracity for load monitoring in professional soccer. Systematic searches through the PubMed, Scopus, and Web of Science databases were conducted for reports onthe data veracity of diverse load monitoring tools and the associated parameters used in professional soccer. Ninety-four studies were finally included in the review, with 39 different tools used and 578 associated parameters identified. The pooled sample consisted of 2066 footballers (95% male: 24 ± 3 years and 5% female: 24 ± 1 years). Seventy-three percent of these studies did not report veracity metrics for anyof the parameters from these tools. Thus, data veracity was found for 54% of tools and 23% of parameters. The current information will assist in the selection of the most appropriate tools and parameters to be used for load monitoring with traditional and Big Data approaches while identifying those still requiring the analysis of their veracity metrics or their improvement to acceptable veracity levels.