Practical Considerations for Workload Measurement in Basketball

Abstract

The use of appropriate methods to quantify external workload, as well as objective and subjective internal workload, is recommended to understand the complete training and game demands encountered by basketball players. However, the cost, labour and expertise required for implementing different monitoring approaches may restrict the scope of metrics able to be measured in some basketball teams. Nevertheless, microsensors appear most popular to measure external workload in the current basketball literature, yielding valid and reliable metrics. In turn, the heart rate-based Summated-Heart-Rate-Zones model combined with the session-rating of perceived exertion model is frequently used and provides cost-effective and user-friendly methods to validly and reliably monitor internal workload in basketball. When monitoring player workloads, it is important to precisely quantify intensity and duration using suitable methods. While average workload intensity is frequently reported relative to session duration (m min−1) using different models, more research is needed to identify appropriate zone thresholds to demarcate different intensities, particularly using external metrics in basketball. When determining the duration of training or games, it is important to include all rest periods to avoid exaggerating the overall intensity of the session; however, samples may be trimmed during analyses if seeking to isolate the demands of specific drills or game periods. In addition to player workloads, measurement of well-being using perceptual measures might offer an additional practical means of assessing player responses, with further research recommended exploring the utility of various well-being parameters in basketball. After selecting appropriate monitoring approaches, basketball coaches and performance staff should quantify cyclic fluctuations in loading and well-being across the team, considering competition schedules and the playing time of individual players to optimally prescribe workloads during the season.