Literature DB >> 30844980

Looking for Complementary Intensity Variables in Different Training Games in Football.

David Casamichana1, Julen Castellano2, Antonio Gómez Díaz3,4, Andrés Martín-García3.   

Abstract

Casamichana, D, Castellano, J, Díaz, AG, and Martín-García, A. Looking for complementary intensity variables in different training games in football. J Strength Cond Res XX(X): 000-000, 2018-The main aim of this study was to identify which combination of external intensity training load (iTL) metrics capture similar or unique information for different training game (TG) formats and official matches (OMs) in football using principal component (PC) analysis. Ten metrics of iTL were collected from 24 professional male football players using global positioning technology. A total of 348, 383, 120, 127, 148, and 207 individual files for small-sided possession games, medium-sided possession games, small-sided games, medium-sided games, large-sided games, and OMs, respectively, were studied. Principal component analysis was conducted on each game format. Extraction criteria were set at an eigenvalue of greater than one. Varimax rotation mode was used to extract more than one PC. Intensity training load metrics with PC "loadings" above 0.7 were deemed to possess well-defined relationships with the extracted PC. In each TG and OM, 3 PCs were identified. For the first PC, eigenvalues for each game format ranged from 3.89 to 4.45, which explained 39-44% of the information (i.e., variance) provided by the 10 iTL metrics. For the second PC, eigenvalues ranged from 2.17 to 2.47, explaining 22-26% of iTL information. For the third PC, eigenvalues ranged from 1.41 to 1.98, explaining 14-20% of iTL information. This would suggest that TG and OM have multidimensional demands; so, the use of only a single iTL could potentially lead to an underestimation of the physical demands. Consequently, a combination of 3 iTL metrics is required during professional football game formats.

Entities:  

Year:  2019        PMID: 30844980     DOI: 10.1519/JSC.0000000000003025

Source DB:  PubMed          Journal:  J Strength Cond Res        ISSN: 1064-8011            Impact factor:   3.775


  8 in total

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Review 2.  From big data mining to technical sport reports: the case of inertial measurement units.

Authors:  Daniel Rojas-Valverde; Carlos D Gómez-Carmona; Randall Gutiérrez-Vargas; Jose Pino-Ortega
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3.  Selecting Training-Load Measures to Explain Variability in Football Training Games.

Authors:  Unai Zurutuza; Julen Castellano; Ibon Echeazarra; Ibai Guridi; David Casamichana
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4.  A Systematic Review of Methods and Criteria Standard Proposal for the Use of Principal Component Analysis in Team's Sports Science.

Authors:  Daniel Rojas-Valverde; José Pino-Ortega; Carlos D Gómez-Carmona; Markel Rico-González
Journal:  Int J Environ Res Public Health       Date:  2020-11-24       Impact factor: 3.390

5.  Influence of Players' Maximum Running Speed on the Team's Ranking Position at the End of the Spanish LaLiga.

Authors:  Juan Del Coso; Diego Brito de Souza; Víctor Moreno-Perez; Javier M Buldú; Fabio Nevado; Ricardo Resta; Roberto López-Del Campo
Journal:  Int J Environ Res Public Health       Date:  2020-11-27       Impact factor: 3.390

6.  Simplifying External Load Data in NCAA Division-I Men's Basketball Competitions: A Principal Component Analysis.

Authors:  Jason D Stone; Justin J Merrigan; Jad Ramadan; Robert Shaun Brown; Gerald T Cheng; W Guy Hornsby; Holden Smith; Scott M Galster; Joshua A Hagen
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7.  External Workload Compared Between Competitive and Non-Competitive Matches for Professional Male Soccer Players.

Authors:  Jose Asian-Clemente; Bermardo Requena; Adam Owen; Alfredo Santalla
Journal:  J Hum Kinet       Date:  2022-09-08       Impact factor: 2.923

Review 8.  Training Design, Performance Analysis, and Talent Identification-A Systematic Review about the Most Relevant Variables through the Principal Component Analysis in Soccer, Basketball, and Rugby.

Authors:  José Pino-Ortega; Daniel Rojas-Valverde; Carlos D Gómez-Carmona; Markel Rico-González
Journal:  Int J Environ Res Public Health       Date:  2021-03-05       Impact factor: 3.390

  8 in total

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