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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

Author

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  • José Pino-Ortega

    (Department of Physical Activity and Sport Sciences, Faculty of Sports Sciences, International Excellence Campus “Mare Nostrum”, University of Murcia, 30720 San Javier, Spain
    BIOVETMED & SPORTSCI Research Group, University of Murcia, 30100 Murcia, Spain)

  • Daniel Rojas-Valverde

    (Centro de Investigación y Diagnóstico en Salud y Deporte (CIDISAD), Escuela de Ciencias del Movimiento Humano y Calidad de Vida (CIEMHCAVI), Universidad Nacional, Heredia 86-3000, Costa Rica)

  • Carlos D. Gómez-Carmona

    (Research Group in Optimization of Training and Sports Performance (GOERD), Department of Didactics of Music, Plastic and Body Expression, Sports Science Faculty, University of Extremadura, 10071 Caceres, Spain)

  • Markel Rico-González

    (BIOVETMED & SPORTSCI Research Group, University of Murcia, 30100 Murcia, Spain
    Departament of Physical Education and Sport, University of the Basque Country, UPV-EHU, Lasarte 71, 01007 Vitoria-Gasteiz, Spain)

Abstract

Since the accelerating development of technology applied to team sports and its subsequent high amount of information available, the need for data mining leads to the use of data reduction techniques such as Principal Component Analysis (PCA). This systematic review aims to identify determinant variables in soccer, basketball and rugby using exploratory factor analysis for, training design, performance analysis and talent identification. Three electronic databases (PubMed, Web of Science, SPORTDiscus) were systematically searched and 34 studies were finally included in the qualitative synthesis. Through PCA, data sets were reduced by 75.07%, and 3.9 ± 2.53 factors were retained that explained 80 ± 0.14% of the total variance. All team sports should be analyzed or trained based on the high level of aerobic capacity combined with adequate levels of power and strength to perform repeated high-intensity actions in a very short time, which differ between team sports. Accelerations and decelerations are mainly significant in soccer, jumps and landings are crucial in basketball, and impacts are primarily identified in rugby. Besides, from these team sports, primary information about different technical/tactical variables was extracted such as (a) soccer: occupied space, ball controls, passes, and shots; (b) basketball: throws, rebounds, and turnovers; or (c) rugby: possession game pace and team formation. Regarding talent identification, both anthropometrics and some physical capacity measures are relevant in soccer and basketball. Although overall, since these variables have been identified in different investigations, further studies should perform PCA on data sets that involve variables from different dimensions (technical, tactical, conditional).

Suggested Citation

  • José Pino-Ortega & Daniel Rojas-Valverde & Carlos D. Gómez-Carmona & Markel Rico-González, 2021. "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," IJERPH, MDPI, vol. 18(5), pages 1-19, March.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:5:p:2642-:d:511562
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    References listed on IDEAS

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    1. Daniel Rojas-Valverde & José Pino-Ortega & Carlos D. Gómez-Carmona & Markel Rico-González, 2020. "A Systematic Review of Methods and Criteria Standard Proposal for the Use of Principal Component Analysis in Team’s Sports Science," IJERPH, MDPI, vol. 17(23), pages 1-13, November.
    2. Carlota Torrents & Angel Ric & Robert Hristovski & Lorena Torres-Ronda & Emili Vicente & Jaime Sampaio, 2016. "Emergence of Exploratory, Technical and Tactical Behavior in Small-Sided Soccer Games when Manipulating the Number of Teammates and Opponents," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-15, December.
    3. Leonardo Ricotti & Jacopo Rigosa & Alberto Niosi & Arianna Menciassi, 2013. "Analysis of Balance, Rapidity, Force and Reaction Times of Soccer Players at Different Levels of Competition," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-1, October.
    4. Nimai Parmar & Nic James & Gary Hearne & Ben Jones, 2018. "Using principal component analysis to develop performance indicators in professional rugby league," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 18(6), pages 938-949, November.
    5. Daniel Rojas-Valverde & Braulio Sánchez-Ureña & José Pino-Ortega & Carlos Gómez-Carmona & Randall Gutiérrez-Vargas & Rafael Timón & Guillermo Olcina, 2019. "External Workload Indicators of Muscle and Kidney Mechanical Injury in Endurance Trail Running," IJERPH, MDPI, vol. 16(20), pages 1-13, October.
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