Stepwise regression analysis was also performed.įaster cutting performance was associated ( p ≤ 0.05) with greater centre of mass (COM) velocities at key instances of the cut ( r or ρ = 0.533–0.752), greater peak and mean propulsive forces ( r or ρ = 0.449–0.651), shorter FFC GCTs ( r or ρ = 0.569–0.581), greater FFC and PFC braking forces ( r = 0.430–0.551), smaller hip and knee flexion range of motion ( r or ρ = 0.406–0.670), greater knee flexion moments (KFMs) ( r = 0.482), and greater internal foot progression angles ( r = − 0.411). Pearson’s and Spearman’s correlations were used to explore the relationships between biomechanical variables and cutting performance and injury risk variables. 61 males from multidirectional sports performed six 90° pre-planned cutting trials, whereby lower-limb and trunk kinetics and kinematics were evaluated using three-dimensional (3D) motion and ground reaction force analysis over the penultimate (PFC) and final foot contact (FFC). Mixed, cross-sectional study following an associative design. The aim of this study was to investigate the relationship between cutting biomechanics and cutting performance (completion time, ground contact time, exit velocity) and surrogates of non-contact ACL injury risk (knee abduction and internal rotation moments) during 90° cutting. This is surprising because cutting is an important action linked to performance and non-contact anterior cruciate ligament (ACL) injuries. Most cutting biomechanical studies investigate performance and knee joint load determinants independently. With respect to the individual foot positioning, the maximum ankle inversion angle can be reduced by increasing exorotation and eversion of the foot while shifting towards forefoot landing. Regarding the intensity of a change-of-direction movement, cutting angle seems to have a higher influence on maximum ankle inversion angle than approach velocity. A change of the main predictors (foot rotation, cutting angle and initial ankle inversion) by 1 SD caused a reduction of the subsequent maximum ankle inversion angle by 2.6–4.4°. The model explained 62% of the variance of maximum ankle inversion angles. The prediction was made based on six predictors that describe change-of-direction intensity and foot placement as found to be relevant in the literature.

A linear mixed regression model was applied to predict the maximum ankle inversion angle during the first 100 ms of ground contact. The movement task consisted of an approach run, followed by a pre-planned cutting movement. We conducted a secondary data analysis and calculated kinematics of 1,400 cuttings performed by 46 male soccer athletes. The objective of this investigation was to identify parameters at initial contact that would predict the subsequent maximum ankle inversion angle during cutting movements.

Fasttasks 2 review