A new approach to comparing the demands of small-sided games and soccer matches.

Euclidean distance External load Overload Performance Similarity

Journal

Biology of sport
ISSN: 0860-021X
Titre abrégé: Biol Sport
Pays: Poland
ID NLM: 8700872

Informations de publication

Date de publication:
Jul 2024
Historique:
received: 24 12 2022
revised: 13 08 2023
accepted: 22 10 2023
medline: 2 7 2024
pubmed: 2 7 2024
entrez: 2 7 2024
Statut: ppublish

Résumé

To improve soccer performance, coaches should be able to replicate the match's physical efforts during the training sessions. For this goal, small-sided games (SSGs) are widely used. The main purpose of the current study was to develop similarity and overload scores to quantify the degree of similarity and the extent to which the SSG was able to replicate match intensity. GPSs were employed to collect external load and were grouped in three vectors (kinematic, metabolic, and mechanical). Euclidean distance was used to calculate the distance between training and match vectors, which was subsequently converted into a similarity score. The average of the pairwise difference between vectors was used to develop the overload scores. Three similarity (Sim

Identifiants

pubmed: 38952897
doi: 10.5114/biolsport.2024.132989
pii: 51818
pmc: PMC11167457
doi:

Types de publication

Journal Article

Langues

eng

Pagination

15-28

Informations de copyright

Copyright © Institute of Sport – National Research Instutite.

Déclaration de conflit d'intérêts

The authors have declared that no conflicts/competing interests exist.

Auteurs

Mauro Mandorino (M)

Performance and Analytics Department, Parma Calcio 1913, 43121 Parma, Italy.
Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Piazza L. de Bosis 6, 00135 Rome, Italy.

Antonio Tessitore (A)

Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Piazza L. de Bosis 6, 00135 Rome, Italy.

Sebastien Coustou (S)

Performance and Analytics Department, Parma Calcio 1913, 43121 Parma, Italy.

Andrea Riboli (A)

MilanLab Research Department, AC Milan S.p.a., Milan, Italy.
Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy.

Mathieu Lacome (M)

Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Piazza L. de Bosis 6, 00135 Rome, Italy.
French Institute of Sport (INSEP), Research Department, Laboratory Sport, Expertise and 11 Performance (EA 7370), Paris, France.

Classifications MeSH