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Monitoring the Prescribed and Experienced Heart Rate-Derived Training Loads in Elite Field Hockey Players

  • Autores: Andrew S. Perrotta, Jack E. Taunton, Michael S. Koehle, Matthew D. White, Darren E. R. Warburton
  • Localización: Journal of strength and conditioning research: the research journal of the NSCA, ISSN 1064-8011, Vol. 33, Nº. 5, 2019, págs. 1394-1399
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • This study examined the congruence between the prescribed and experienced heart rate-derived training loads over a 5-week periodized mesocycle. Twenty-four elite female field hockey players training as part of a national team were monitored before an (FIH) Hockey World League tournament. Three on-field training sessions per week were prospectively designed focusing on technical, tactical, and physiologically oriented hockey drills. A training load value, modeling the periodized weekly loading scheme, was prescribed for each training session and was calculated using normative training load responses from performing on-field hockey drills. Magnitude-based inferences focusing on the effect size (ES) and a Pearson correlation coefficient (r) were used to examine the degree of difference and the strength of correlation between the prescribed and experienced training loads. A significant correlation was observed between the experienced and prescribed training loads over the 5-week mesocycle (r = 0.92, 90% confidence limit [CL] [0.84-0.96]). The percentage difference and the ES between the achieved and prescribed training loads were as follows: week 1 demonstrated a 2.0% difference (ES = 0.10, 90% CL [-0.22-0.41]), week 2 a -5.4% difference (ES = -0.41, 90% CL [-0.75 to -0.07]), week 3 a -1.5% difference (ES = -0.09, 90% CL [-0.37 to 0.20]), week 4 a 7.1% difference (ES = 0.46, 90% CL [0.14-0.78]), and week 5 a 3.5% difference (ES = 0.18, 90% CL [-0.17 to 0.53]). This investigation demonstrates the efficacy for coaches to prospectively design on-field training sessions using normative training load data to enhance the congruence between the prescribed and experienced training loads over a periodized mesocycle.


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