Purpose: Assessing the relationship between external load (EL) and internal load (IL) in youth male beach handball players. Methods: A total of 11 field players from the Lithuanian U17 beach handball team were monitored across 14 training sessions and 7 matches. The following EL variables were assessed by means of inertial movement units: PlayerLoadTM, accelerations. decelerations, changes of direction, and jumps and total of inertial movements. IL was assessed objectively and subjectively using the summated heart rate zones and training load calculated via session rating of perceived exertion, respectively. Spearman correlations (rho) were used to assess the relationship between EL and IL. The interindividual variability was investigated using linear mixed models with random intercepts with IL as dependent variable, PlayerLoad (TM) as the independent variable, and players as random effect. Results: The lowest significant (P < .05) relationship was for high jumps with objective (rho= .56) and subjective (rho = .49) IL. The strongest relationship was for PlayerLoad (TM) with objective (rho = .9) and subjective (rho = .84) IL. From the linear mixed model, the estimated SD of the random intercepts was 19.78 arbitrary units (95% confidence interval, 11.75-33.31); SE =5.26, and R-2 = .47 for the objective IL and 6.03 arbitrary units (95% confidence interval, 0.00-7330.6); SE = 21.87; and R-2 = .71 for the subjective IL. Conclusions: Objective and subjective IL measures can be used as a monitoring tool when EL monitoring is not possible. Coaches can predict IL based on a given EL by using the equations proposed in this study.

Relationship Between External and Internal Load Measures in Youth Beach Handball

Fusco, Andrea
Secondo
;
2022-01-01

Abstract

Purpose: Assessing the relationship between external load (EL) and internal load (IL) in youth male beach handball players. Methods: A total of 11 field players from the Lithuanian U17 beach handball team were monitored across 14 training sessions and 7 matches. The following EL variables were assessed by means of inertial movement units: PlayerLoadTM, accelerations. decelerations, changes of direction, and jumps and total of inertial movements. IL was assessed objectively and subjectively using the summated heart rate zones and training load calculated via session rating of perceived exertion, respectively. Spearman correlations (rho) were used to assess the relationship between EL and IL. The interindividual variability was investigated using linear mixed models with random intercepts with IL as dependent variable, PlayerLoad (TM) as the independent variable, and players as random effect. Results: The lowest significant (P < .05) relationship was for high jumps with objective (rho= .56) and subjective (rho = .49) IL. The strongest relationship was for PlayerLoad (TM) with objective (rho = .9) and subjective (rho = .84) IL. From the linear mixed model, the estimated SD of the random intercepts was 19.78 arbitrary units (95% confidence interval, 11.75-33.31); SE =5.26, and R-2 = .47 for the objective IL and 6.03 arbitrary units (95% confidence interval, 0.00-7330.6); SE = 21.87; and R-2 = .71 for the subjective IL. Conclusions: Objective and subjective IL measures can be used as a monitoring tool when EL monitoring is not possible. Coaches can predict IL based on a given EL by using the equations proposed in this study.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/842596
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