Literature DB >> 34310496

Energy Expenditure of a Male and Female Tennis Player during Association of Tennis Professionals/Women's Tennis Association and Grand Slam Events Measured by Doubly Labeled Water.

Daniel G Ellis, John Speakman1, Catherine Hambly1, James P Morton2, Graeme L Close2, Dan Lewindon3, Timothy F Donovan2.   

Abstract

METHODS: Doubly labeled water assessed TEE during a 17-d period analyzed by days 1 to 7 (P1) and 7-17 (P2) which included a Women's Tennis Association/Association of Tennis Professionals tournament and culminated at the Wimbledon Championships. Daily training and match loads were assessed using a 10-point Borg scale multiplied by time. Match data were provided by video analysis and player tracking technology.
RESULTS: The TEE during P1 for the female player was 3383 kcal·d-1 (63.5 kcal·kg-1) fat-free mass (FFM) with 362 points played over 241 min in three matches covering a distance of 2569 m, with an additional 875 min training. During P2, TEE was 3824 kcal·d-1 (71.7 kcal·kg-1) FFM with 706 points played over 519 min during five matches, covering a distance of 7357 m with an additional 795 min training. The TEE during P1 for the male player was 3712 kcal·d-1 (56.3 kcal·kg-1) FFM with 133 points played over 88 min during one match covering 1125 m, with an additional 795 min training. During P2, TEE was 5520 kcal·d-1 (83.7 kcal·kg-1) FFM with 891 points played over 734 min during five matches, covering 10,043 m, with an additional 350 min training.
CONCLUSIONS: This novel data positions elite tennis, played at the highest level, as a highly energetic demanding sport, highlighting that nutritional strategies should ensure sufficient energy availability during competition schedules.
Copyright © 2021 by the American College of Sports Medicine.

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Year:  2021        PMID: 34310496     DOI: 10.1249/MSS.0000000000002745

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  1 in total

1.  Analytical Model of Action Fusion in Sports Tennis Teaching by Convolutional Neural Networks.

Authors:  Huiguang Li; Hanzhao Guo; Hong Huang
Journal:  Comput Intell Neurosci       Date:  2022-07-31
  1 in total

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