Contemporary research into training load in team sports primarily focusses on the physiological load demands, whereas the biomechanical load still remains largely unexplored. While the former refers to the work-energy relationship when the players move around the pitch, the latter refers to the external forces the players are exposed to from their movements around the pitch. Monitoring of the biomechanical load helps practitioners estimate the stresses on an athlete’s musculoskeletal structures as a consequence of the external forces acting on their body. Monitoring of the biomechanical load is currently restricted to laboratory settings, but the recent introduction of GPS devices with integrated accelerometers in team sports may enable practitioners to monitor whole-body biomechanical load during training sessions and match-play. The aim of this thesis was therefore to explore if body-worn accelerometry can be used for whole-body biomechanical load monitoring in team sports. The first study of this thesis showed that although a linear relationship exists between body-worn accelerometry (e.g. from GPS integrated accelerometers) and whole-body accelerations, the linear relationship based on Newton’s second law of motion is weak regardless of accelerometer location (trunk, pelvis or tibia). Body-worn accelerometry only measures the acceleration of the segment it is attached to and is therefore inadequate to measure the complex multi-segment dynamics of the whole body during team sports movements. The second study of this thesis did however offer a potential solution to that problem, and it was demonstrated that the complex multi-segment dynamics of the body and the associated ground reaction forces (GRF), a surrogate for whole-body biomechanical load, can be estimated with a mass-spring-damper model (MSD-model). Nonetheless, the MSD-model’s accuracy to estimate GRF slightly decreases for sharp changes of direction at high intensities, because the absorption of energy and generation of energy are decoupled. Finally, a novel approach to estimate GRF from the combination of trunk-mounted accelerometry and a MSD-model was introduced in this thesis. This approach showed that trunk accelerometry data has the potential to generate the eight model parameters required to estimate GRF from a MSD-model, though further work is required in particular towards improving the model’s ability to estimate GRF across a wide range of activities. The novel approach introduced in this thesis has the potential to give practitioners in team sports the opportunity to monitor whole-body biomechanical load due to player-ground interaction in the field, a necessity if they wish to predict the consequent musculoskeletal structural adaptations of training sessions and match-play
