Abstract
Internal load can be objectively measured by heart rate-based models, such as Edwards’ summated heart rate zones, or subjectively by session rating of perceived exertion. The relationship between internal loads assessed via heart rate-based models and session rating of perceived exertion is usually studied through simple correlations, although the Linear Mixed Model could represent a more appropriate statistical procedure to deal with intrasubject variability. This study aimed to compare conventional correlations and the Linear Mixed Model to assess the relationships between objective and subjective measures of internal load in team sports. Thirteen male youth beach handball players (15.9 ± 0.3 years) were monitored (14 training sessions; 7 official matches). Correlation coefficients were used to correlate the objective and subjective internal load. The Linear Mixed Model was used to model the relationship between objective and subjective measures of internal load data by considering each player individual response as random effect. Random intercepts were used and then random slopes were added. The likelihood-ratio test was used to compare statistical models. The correlation coefficient for the overall relationship between the objective and subjective internal data was very large (r = 0.74; ρ = 0.78). The Linear Mixed Model using both random slopes and random intercepts better explained (p < 0.001) the relationship between internal load measures. Researchers are encouraged to apply the Linear Mixed Models rather than correlation to analyze internal load relationships in team sports since it allows for the consideration of the individuality of players.
Highlights
Monitoring athletes’ workload is an essential process to understand the level of adaptation to a given training program and it is useful in minimizing the risk of nonfunctional overreaching [1,2]
The workload can be either external and internal, where the external load represents an objective measure of the work performed by the athlete, while the internal load represents the psychophysiological response of the athlete to a given training stimulus [3]
Results showed that Linear Mixed Model (LMM) can give more powerful and appropriate information regarding the relationship between Summated Heart Rate Zone (SHRZ) and session Rating of Perceived Exertion (sRPE) workloads rather than the usual procedure using correlations and linear regression with only fixed effects
Summary
Monitoring athletes’ workload is an essential process to understand the level of adaptation to a given training program and it is useful in minimizing the risk of nonfunctional overreaching [1,2]. External load can be assessed by means of Global Positioning Systems (GPS), Inertial. Movement Units (IMU) [3], accelerometers [3], and Local Positioning Systems (LPS) [4]. These systems are widely used in team sports such as basketball [5,6,7], handball [8], and beach handball [9], they present several limitations, such as high cost, the need of high technical expertise, and the risk of technical errors leading to a loss of data [10]. Internal load indicates the functional outcome of a given external load and can be used as an inexpensive way of monitoring athletes [11].
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