The identification of optimum technique for maximal effort sporting tasks is one of the greatest challenges within sports biomechanics. A theoretical approach using forward-dynamics simulation allows individual parameters to be systematically perturbed independently of potentially confounding variables. Each study typically follows a four-stage process of model construction, parameter determination, model evaluation, and model optimization. This review critically evaluates forward-dynamics simulation models of maximal effort sporting movements using a dynamical systems theory framework. Organismic, environmental, and task constraints applied within such models are critically evaluated, and recommendations are made regarding future directions and best practices. The incorporation of self-organizational processes representing movement variability and “intrinsic dynamics” remains limited. In the future, forward-dynamics simulation models predicting individual-specific optimal techniques of sporting movements may be used as indicative rather than prescriptive tools within a coaching framework to aid applied practice and understanding, although researchers and practitioners should continue to consider concerns resulting from dynamical systems theory regarding the complexity of models and particularly regarding self-organization processes.

The aim of this study was to determine the inter-unit reliability of IMU Step biomechanical load monitoring metrics using IMeasureU Blue Trident inertial measurement units in tasks common to running-based team sports. Knowledge of variability between units is required before researchers and practitioners can make informed decisions on “true” differences between limbs. Sixteen male college soccer players performed five running-based tasks, generating 224 trials and 17,012 steps. Data were analysed for each task and for the whole session, investigating six IMU Step metrics: step count; impact load; bone stimulus; and low, medium and high intensity steps. Inter-unit reliability was excellent (ICC ≥ 0.90) for 21 out of 26 metrics, and good (0.83 ≤ ICC ≤ 0.86) for all other metrics except for Yo-Yo impact load (ICC = 0.79) which was acceptable. These findings confirm the inter-unit reliability of IMU Step metrics using IMeasureU Blue Trident inertial measurement units for running-based team sports. Now that inter-unit variability has been quantified, researchers and practitioners can use this information when interpreting inter-limb differences for monitoring external biomechanical training load.

The purpose of this study was to quantify the magnitude and frequency content of surface-measured accelerations at each major human body segment from foot to head during impact landings. Twelve males performed two single leg drop landings from each of 0.15 m, 0.30 m, and 0.45 m. Triaxial accelerometers (2000 Hz) were positioned over the: first metatarsophalangeal joint; distal anteromedial tibia; superior to the medial femoral condyle; L5 vertebra; and C6 vertebra. Analysis of acceleration signal power spectral densities revealed two distinct components, 2-14 Hz and 14-58 Hz, which were assumed to correspond to time domain signal joint rotations and elastic wave tissue deformation, respectively. Between each accelerometer position from the metatarsophalangeal joint to the L5 vertebra, signals exhibited decreased peak acceleration, increased time to peak acceleration, and decreased power spectral density integral of both the 2-14 Hz and 14-58 Hz components, with no further attenuation beyond the L5 vertebra. This resulted in peak accelerations close to vital organs of less than 10% of those at the foot. Following landings from greater heights, peak accelerations measured distally were greater, as was attenuation prior to the L5 position. Active and passive mechanisms within the lower limb therefore contribute to progressive attenuation of accelerations, preventing excessive accelerations from reaching the torso and head, even when distal accelerations are large.

A logarithmic curve fitting methodology for the calculation of badminton racket-shuttlecock impact locations from three-dimensional motion capture data was presented and validated. Median absolute differences between calculated and measured impact locations were 3.6 [IQR: 4.4] and 3.5 [IQR: 3.5] mm mediolaterally and longitudinally on the racket face, respectively. Three-dimensional kinematic data of racket and shuttlecock were recorded for 2386 smashes performed by 65 international badminton players, with racket-shuttlecock impact location assessed against instantaneous post-impact shuttlecock speed and direction. Mediolateral and longitudinal impact locations explained 26.2% (quadratic regression; 95% credible interval: 23.1%, 29.2%; BF10 = 1.3 × 10131, extreme; p < 0.001) of the variation in participant-specific shuttlecock speed. A meaningful (BF10 = ∞, extreme; p < 0.001) linear relationship was observed between mediolateral impact location and shuttlecock horizontal direction relative to a line normal to the racket face at impact. Impact locations within one standard deviation of the pooled mean impact location predict reductions in post-impact shuttlecock speeds of up to 5.3% of the player’s maximal speed and deviations in the horizontal direction of up to 2.9° relative to a line normal to the racket face. These results highlight the margin for error available to elite badminton players during the smash.

This study aimed to investigate the contributions of kinetic and kinematic parameters to inter-individual variation in countermovement jump (CMJ) performance. Two-dimensional kinematic data and ground reaction forces during a CMJ were recorded for 18 males of varying jumping experience. Ten kinetic and eight kinematic parameters were determined for each performance, describing peak lower-limb joint torques and powers, concentric knee extension rate of torque development and CMJ technique. Participants also completed a series of isometric knee extensions to measure the rate of torque development and peak torque. CMJ height ranged from 0.38 to 0.73 m (mean 0.55 ± 0.09 m). CMJ peak knee power, peak ankle power and take-off shoulder angle explained 74% of this observed variation. CMJ kinematic (58%) and CMJ kinetic (57%) parameters explained a much larger proportion of the jump height variation than the isometric parameters (18%), suggesting that coachable technique factors and the joint kinetics during the jump are important determinants of CMJ performance. Technique, specifically greater ankle plantar-flexion and shoulder flexion at take-off (together explaining 58% of the CMJ height variation), likely influences the extent to which maximal muscle capabilities can be utilised during the jump.