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A Systematic Review of Methods and Criteria Standard Proposal for the Use of Principal Component Analysis in Team’s Sports Science

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  • 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
    Grupo de Avances en el Entrenamiento Deportivo y Acondicionamiento Físico (GAEDAF), Facultad Ciencias del Deporte, Universidad de Extremadura, 10071 Cáceres, Spain)

  • José Pino-Ortega

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

  • 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

The availability of critical information about training and competition is fundamental on performance. Principal components analysis (PCA) is widely used in sports as a multivariate technique to manage big data from different technological assessments. This systematic review aimed to explore the methods reported and statistical criteria used in team’s sports science and to propose a criteria standard to report PCA in further applications. A systematic electronic search was developed through four electronic databases and a total of 45 studies were included in the review for final analysis. Inclusion criteria: (i) of the studies we looked at, 22.22% performed factorability processes with different retention criteria ( r > 0.4–0.7); (ii) 21 studies confirmed sample adequacy using Kaiser-Meyer-Olkim (KMO > 5–8) and 22 reported Bartlett’s sphericity; (iii) factor retention was considered if eigenvalues >1–1.5 ( n = 29); (iv) 23 studies reported loading retention (>0.4–0.7); and (v) used VariMax as the rotation method (48.9%). A lack of consistency and serious voids in reporting of essential methodological information was found. Twenty-one items were selected to provide a standard quality criterion to report methods sections when using PCA. These evidence-based criteria will lead to a better understanding and applicability of the results and future study replications.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:23:p:8712-:d:450011
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    References listed on IDEAS

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    1. 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.
    2. Craig Wright & Steve Atkins & Bryan Jones & Jason Todd, 2013. "The role of performance analysts within the coaching process: Performance Analysts Survey ‘The role of performance analysts in elite football club settings.’," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 13(1), pages 240-261, April.
    3. M. Theodoros Bampouras & Colum Cronin & K. Paul Miller, 2012. "Performance analytic processes in elite sport practice: An exploratory investigation of the perspectives of a sport scientist, coach and athlete," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 12(2), pages 468-483, August.
    4. 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.
    5. 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.
    6. 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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