Principal component analysis identifies different representative match load profiles in international women’s field hockey based on playing positions. [El análisis de componentes principales identifica diferentes perfiles de rendimiento en función de las posiciones en partidos internacionales de hockey hierba femenino].
Resumen
Abstract
The aim of this study was to assess the principal components (PC) of women’s field hockey players´ TL distinguishing by playing positions (i.e., back, midfielder, forward). Data were collected from sixteen players belonging to the Spanish National women’s field hockey team during 13 official matches from the European Championship, World Series, and Pre-Olympic tournament. The Principal Component Analysis (PCA) grouped a total of 16 variables in five to six PC, explaining between 68.6 and 80% of the total variance. Different variables formed the PC that explain the player’s performance in different field positions. There were differences by positions in the distance covered at 21 to 24 km·h-1 (midfielders>forwards), decelerations from 5 to 4 m·s-2 (midfielders>forwards), and in maximum accelerations (midfielders>backs). Overall, strength and conditioning coaches should combine exercises which induce a high degree of aerobic endurance and power. However, some specification should be made by playing position: (1) defenders should perform training sessions with at least the same amount of volume as in the matches; (2) forwards should perform training efforts that ensure high repeated sprint ability; and (3) midfielders should perform a high training volume to develop high-intensity aerobic endurance, in combination with short-term efforts.
Resumen
El objetivo de este estudio fue evaluar los componentes principales (CP) de rendimiento de las jugadoras de hockey hierba en diferentes posiciones del campo (defensiva, mediocampista, delantera). Se registraron datos de 16 jugadoras de la selección española absoluta de hockey hierba femenino durante 13 partidos oficiales del Campeonato de Europa, Serie Mundial y del Torneo Preolímpico. El Análisis de Componentes Principales (ACP) agrupó un total de 16 variables en cinco/seis CP, lo que explica entre el 68,6 y el 80% de la varianza total. Diferentes variables formaron los PC que explican el rendimiento de las jugadoras en diferentes posiciones del campo. Se encontraron diferencias por posiciones en distancia de 21 a 24 km/h (centrocampistas > delanteras), deceleraciones de 5 a 4 m/s (mediocampistas > delanteras) y en aceleraciones máximas (mediocampistas > defensas). En general, los preparadores físicos deben combinar ejercicios que lleven a un alto grado de resistencia aeróbica y potencia, aunque se deben hacer algunas especificaciones por posición de juego: (1) las defensoras deben realizan sesiones de entrenamiento con al menos la misma cantidad de volumen que en el partido; (2) las delanteras deben realizar durante los entrenamientos esfuerzos que aseguren una alta capacidad de repetir carreras de alta intensidad; y (3) las mediocampistas deben desarrollar una resistencia aeróbica de alta intensidad en combinación con esfuerzos cortos e intensos.
https://doi.org/10.5232/ricyde2021.06401
References/referencias
Agras, H.; Ferragut, C., & Abraldes, J. A. (2016). Match analysis in futsal: A systematic review. International Journal of Performance Analysis in Sport, 16(2), 652–686.
https://doi.org/10.1080/24748668.2016.11868915
Bartlett, M. S. (1954). A Note on the Multiplying Factors for Various χ2 Approximations. Journal of the Royal Statistical Society. Series B (Methodological), 16(2), 296–298. JSTOR.
Bastida-Castillo, A.; Gómez Carmona, C. D.; Pino Ortega, J., & de la Cruz Sánchez, E. (2017). Validity of an inertial system to measure sprint time and sport task time: A proposal for the integration of photocells in an inertial system. International Journal of Performance Analysis in Sport, 17(4), 600–608.
https://doi.org/10.1080/24748668.2017.1374633
Bastida-Castillo, A.; Gómez-Carmona, C. D.; De La Cruz Sánchez, E., & Pino-Ortega, J. (2019). Comparing accuracy between global positioning systems and ultra-wideband-based position tracking systems used for tactical analyses in soccer. European Journal of Sport Science, 19(9), 1157–1165.
https://doi.org/10.1080/17461391.2019.1584248
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed). L. Erlbaum Associates.
Delves, R. I.; Bahnisch, J.; Ball, K., & Duthie, G. M. (2019). Quantifying Mean Peak Running Intensities in Elite Field Hockey. Journal of Strength and Conditioning Research.
Gabbett, T. J. (2010). GPS analysis of elite women´s field hockey training and competition. Journal of Strength and Conditioning Research, 24(5), 4.
Groth, D.; Hartmann, S.; Klie, S., & Selbig, J. (2013). Principal Components Analysis. In B. Reisfeld & A. N. Mayeno (Eds.), Computational Toxicology (Vol. 930, pp. 527–547). Humana Press.
https://doi.org/10.1007/978-1-62703-059-5_22
Hair, J. F.; Anderson, R. E.; Tatham, R. L., & Black, W. C. (1995). Multivariate data analysis (4th ed.): With readings. Prentice-Hall, Inc.
Hodun, M.; Clarke, R., & Hughes, J. D. (2016). Global Positioning System Analysis of Running Performance in Female Field Sports: A Review of the Literature. Strength and Conditioning Journal, 38(2), 8.
Jackson, B. M.; Polglaze, T.; Dawson, B.; King, T., & Peeling, P. (2018). Comparing Global Positioning System and Global Navigation Satellite System Measures of Team-Sport Movements. International Journal of Sports Physiology and Performance, 13(8), 1005–1010.
https://doi.org/10.1123/ijspp.2017-0529
Kaiser, H. F. (1960). The Application of Electronic Computers to Factor Analysis. Educational and Psychological Measurement, 20(1), 141–151.
https://doi.org/10.1177/001316446002000116
Kim, D. J.-O., & Mueller, C. W. (1978). Introduction to Factor Analysis: What It Is and How To Do It (Edición: 1). SAGE Publications, Inc.
Lythe, J., & Kilding, A. E. (2011). Physical Demands and Physiological Responses During Elite Field Hockey. International Journal of Sports Medicine, 32(07), 523–528.
https://doi.org/10.1055/s-0031-1273710
Macutkiewicz, D., & Sunderland, C. (2011). The use of GPS to evaluate activity profiles of elite women hockey players during match-play. Journal of Sports Sciences, 29(9), 967–973.
https://doi.org/10.1080/02640414.2011.570774
McGuinness, A.; Malone, S.; Hughes, B.; Collins, K., & Passmore, D. (2019). Physical Activity and Physiological Profiles of Elite International Female Field Hockey Players Across the Quarters of Competitive Match Play. Journal of Strength and Conditioning Research, 33(9), 2513–2522.
https://doi.org/10.1519/JSC.0000000000002483
McGuinness, A.; Malone, S.; Petrakos, G., & Collins, K. (2019). Physical and Physiological Demands of Elite International Female Field Hockey Players During Competitive Match Play. Journal of Strength and Conditioning Research, 33(11), 3105–3113.
https://doi.org/10.1519/JSC.0000000000002158
Morencos, E.; Casamichana, D.; Torres, L.; Haro, X., & Rodas, G. (2019). Kinematic Demands of International Competition in Women’s Field Hockey. Apunts Educación Física y Deportes, 137, 56–70.
https://doi.org/10.5672/apunts.2014-0983.es.(2019/3).137.05
Muazu, R. (2019). Determining Youth Profile using Principle Component Analysis for Identifying Talent in Sports. International Journal of Recent Technology and Engineering, 8(2S7), 212–215.
https://doi.org/10.35940/ijrte.B1052.0782S719
Oliva-Lozano, J. M.; Rojas-Valverde, D.; Gómez-Carmona, C. D.; Fortes, V., & Pino-Ortega, J. (2020). Impact Of Contextual Variables On The Representative External Load Profile Of Spanish Professional Soccer Match-Play: A Full Season Study. European Journal of Sport Science, 1–22.
https://doi.org/10.1080/17461391.2020.1751305
Rico-González, M.; Los Arcos, A.; Rojas-Valverde, D.; Clemente, F. M., & Pino-Ortega, J. (2020). A Survey to Assess the Quality of the Data Obtained by Radio-Frequency Technologies and Microelectromechanical Systems to Measure External Workload and Collective Behavior Variables in Team Sports. Sensors, 16.
Robbins, S. M.; Renaud, P. J., & Pearsall, D. J. (2018). Principal component analysis identifies differences in ice hockey skating stride between high- and low-calibre players. Sports Biomechanics, 1–19.
https://doi.org/10.1080/14763141.2018.1524510
Rojas-Valverde, D.; Sánchez-Ureña, B.; Pino-Ortega, J.; Gómez-Carmona, C.; Gutiérrez-Vargas, R.; Timón, R., & Olcina, G. (2019). External Workload Indicators of Muscle and Kidney Mechanical Injury in Endurance Trail Running. International Journal of Environmental Research and Public Health, 16(20), 3909.
https://doi.org/10.3390/ijerph16203909
Romero-Moraleda, B.; Morencos-Martínez, E.; Torres-Ronda, L., & Casamichana, D. (2020). Analysis of congested schedule on competition external load in field hockey. RICYDE. Revista Internacional de Ciencias Del Deporte, 16(60), 143–152.
https://doi.org/10.5232/ricyde2020.06003
Tabachnick, B., & Fidell, L. (2007). Using Multivariate Statistics (6th ed.). Pearson Education.
Thompson, B. (Ed.). (2004). Exploratory and Confirmatory Factor Analysis: Understanding Concepts and Applications (1 edition). American Psychological Association.
Vescovi, J. D., & Frayne, D. H. (2015). Motion Characteristics of Division I College Field Hockey: Female Athletes in Motion (FAiM) Study. International Journal of Sports Physiology and Performance, 10(4), 476–481.
https://doi.org/10.1123/ijspp.2014-0324
Weaving, D.; Marshall, P.; Earle, K.; Nevill, A., & Abt, G. (2014). Combining Internal- and External-Training-Load Measures in Professional Rugby League. International Journal of Sports Physiology and Performance, 9(6), 905–912.
https://doi.org/10.1123/ijspp.2013-0444
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RICYDE. Revista Internacional de Ciencias del Deporte
Publisher: Ramón Cantó Alcaraz
ISSN:1885-3137 - Periodicidad Trimestral / Quarterly