Literature DB >> 30160085

Does stroke performance in amateur tennis players depend on functional power generating capacity?

Gabriel Delgado-García1,2, Jos Vanrenterghem3, Alejandro Muñoz-García4,5, Alejandro Molina-Molina4,5, Víctor M Soto-Hermoso4,5.   

Abstract

BACKGROUND: Physical preparation is becoming more important in amateur tennis player training programs. Yet, when studying stroke performance in these players, there is a lack of evidence on the role of functional power generating capacity. The aim of the study was therefore to determine whether functional power generating capacity correlates with speed and accuracy of forehand and backhand groundstrokes in amateur players. We also studied the correlation with handgrip strength as a more classical measurement of general muscle strength.
METHODS: A total of 21 male amateur players, aged 33.7±4.6 with 17.1±6.7 years of play, were tested. They performed a medicine ball side throw test, a handgrip dynamometer test, and a stroke performance test.
RESULTS: Distance of the medicine ball throw on the dominant side positively correlated to the speed of the fastest forehand (r=0.52; P=0.017) and backhand accuracy (r=0.49; P=0.024). There was also a correlation between the handgrip strength on the dominant side and the speed of the fastest forehand (r=0.52, P=0.019).
CONCLUSIONS: We concluded that groundstroke performance in amateur tennis players depends on functional power generating capacity, but that it is not the principal contributing factor.

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Year:  2018        PMID: 30160085     DOI: 10.23736/S0022-4707.18.08518-3

Source DB:  PubMed          Journal:  J Sports Med Phys Fitness        ISSN: 0022-4707            Impact factor:   1.637


  3 in total

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2.  Fitness testing in tennis: Influence of anthropometric characteristics, physical performance, and functional test on serve velocity in professional players.

Authors:  Alejandro Sánchez-Pay; Jesús Ramón-Llin; Rafael Martínez-Gallego; David Sanz-Rivas; Bernardino Javier Sánchez-Alcaraz; Sergio Frutos
Journal:  PLoS One       Date:  2021-11-29       Impact factor: 3.240

3.  An Enhanced Joint Hilbert Embedding-Based Metric to Support Mocap Data Classification with Preserved Interpretability.

Authors:  Cristian Kaori Valencia-Marin; Juan Diego Pulgarin-Giraldo; Luisa Fernanda Velasquez-Martinez; Andres Marino Alvarez-Meza; German Castellanos-Dominguez
Journal:  Sensors (Basel)       Date:  2021-06-29       Impact factor: 3.576

  3 in total

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