Inertial measurement units (IMUs) allow for measurements of kinematic movements outside the laboratory, persevering the athlete-environment relationship. To use IMUs in a sport-specific setting, it is necessary to validate sport-specific movements. The aim of this study was to assess the concurrent validity of the Xsens IMU system by comparing it to the Vicon optoelectronic motion system for lower-limb joint angle measurements during jump-landing and change-of-direction tasks. Ten recreational athletes performed four tasks; single-leg hop and landing, running double-leg vertical jump landing, single-leg deceleration and push off, and sidestep cut, while kinematics were recorded by 17 IMUs (Xsens Technologies B.V.) and eight motion capture cameras (Vicon Motion Systems, Ltd). Validity of lower-body joint kinematics was assessed using measures of agreement (cross-correlation: XCORR) and error (root mean square deviation and amplitude difference). Excellent agreement was found in the sagittal plane for all joints and tasks (XCORR > 0.92). Highly variable agreement was found for knee and ankle in transverse and frontal plane. Relatively high error rates were found in all joints. In conclusion, this study shows that the Xsens IMU system provides highly comparable waveforms of sagittal lower-body joint kinematics in sport-specific movements. Caution is advised interpreting frontal and transverse plane kinematics as between-system agreement highly varied.

Modifiable (biomechanical and neuromuscular) anterior cruciate ligament (ACL) injury risk factors have been identified in laboratory settings. These risk factors were subsequently used in ACL injury prevention measures. Due to the lack of ecological validity, the use of on‐field data in the ACL injury risk screening is increasingly advocated. Though, the kinematic differences between laboratory and on‐field settings have never been investigated. The aim of the present study was to investigate the lower‐limb kinematics of female footballers during agility movements performed both in laboratory and football field environments. Twenty‐eight healthy young female talented football (soccer) players (14.9 ± 0.9 years) participated. Lower‐limb joint kinematics was collected through wearable inertial sensors (Xsens Link) in three conditions: (1) laboratory setting during unanticipated sidestep cutting at 40‐50°; on the football pitch (2) football‐specific exercises (F‐EX) and (3) football games (F‐GAME). A hierarchical two‐level random effect model in Statistical Parametric Mapping was used to compare joint kinematics among the conditions. Waveform consistency was investigated through Pearson's correlation coefficient and standardized z‐score vector. In‐lab kinematics differed from the on‐field ones, while the latter were similar in overall shape and peaks. Lower sagittal plane range of motion, greater ankle eversion, and pelvic rotation were found for on‐field kinematics (p < 0.044). The largest differences were found during landing and weight acceptance. The biomechanical differences between lab and field settings suggest the application of context‐related adaptations in female footballers and have implications in ACL injury prevention strategies.Highlights Talented youth female football players showed kinematical differences between the lab condition and the on‐field ones, thus adopting a context‐related motor strategy. Lower sagittal plane range of motion, greater ankle eversion, and pelvic rotation were found on the field. Such differences pertain to the ACL injury mechanism and prevention strategies. Preventative training should support the adoption of non‐linear motor learning to stimulate greater self‐organization and adaptability. It is recommended to test football players in an ecological environment to improve subsequent primary ACL injury prevention programmes.

The aim of the present study was to investigate if the presence of anterior cruciate ligament (ACL) injury risk factors depicted in the laboratory would reflect at-risk patterns in football-specific field data. Twenty-four female footballers (14.9 ± 0.9 year) performed unanticipated cutting maneuvers in a laboratory setting and on the football pitch during football-specific exercises (F-EX) and games (F-GAME). Knee joint moments were collected in the laboratory and grouped using hierarchical agglomerative clustering. The clusters were used to investigate the kinematics collected on field through wearable sensors. Three clusters emerged: Cluster 1 presented the lowest knee moments; Cluster 2 presented high knee extension but low knee abduction and rotation moments; Cluster 3 presented the highest knee abduction, extension, and external rotation moments. In F-EX, greater knee abduction angles were found in Cluster 2 and 3 compared to Cluster 1 (p = 0.007). Cluster 2 showed the lowest knee and hip flexion angles (p < 0.013). Cluster 3 showed the greatest hip external rotation angles (p = 0.006). In F-GAME, Cluster 3 presented the greatest knee external rotation and lowest knee flexion angles (p = 0.003). Clinically relevant differences towards ACL injury identified in the laboratory reflected at-risk patterns only in part when cutting on the field: in the field, low-risk players exhibited similar kinematic patterns as the high-risk players. Therefore, in-lab injury risk screening may lack ecological validity.

Laboratory studies have limitations in screening for anterior cruciate ligament (ACL) injury risk due to their lack of ecological validity. Machine learning (ML) methods coupled with wearable sensors are state-of-art approaches for joint load estimation outside the laboratory in athletic tasks. The aim of this study was to investigate ML approaches in predicting knee joint loading during sport-specific agility tasks. We explored the possibility of predicting high and low knee abduction moments (KAMs) from kinematic data collected in a laboratory setting through wearable sensors and of predicting the actual KAM from kinematics. Xsens MVN Analyze and Vicon motion analysis, together with Bertec force plates, were used. Talented female football (soccer) players (n = 32, age 14.8 ± 1.0 y, height 167.9 ± 5.1 cm, mass 57.5 ± 8.0 kg) performed unanticipated sidestep cutting movements (number of trials analyzed = 1105). According to the findings of this technical note, classification models that aim to identify the players exhibiting high or low KAM are preferable to the ones that aim to predict the actual peak KAM magnitude. The possibility of classifying high versus low KAMs during agility with good approximation (AUC 0.81–0.85) represents a step towards testing in an ecologically valid environment.

Providing choices, i.e., autonomy, to athletes during practice increases intrinsic motivation and positively influences the motor learning process. The effects of autonomy on the timing of feedback (self-controlled timing of feedback) when optimizing the movement execution of sidestep cutting (SSC), a task that is highly related with ACL injury risk, are unknown. The aim of this study was to investigate the effect of self-controlled timing of video and EF-feedback on movement execution of SSC in team sport athletes. Thirty healthy ball team sport athletes (22.9 ± 1.7 years, 185.5 ± 7.2 cm, 79.3 ± 9.2 kg) were recruited from local sports clubs. Participants were alternately assigned to the self-control (SC) or the yoked (YK) group based on arrival and performed five anticipated and five unanticipated 45° SSC trials as pre-, immediate-post and one-week retention test. Movement execution was measured with the Cutting Movement Assessment Score (CMAS). Training consisted of three randomized 45° SSC conditions: one anticipated and two unanticipated conditions. All participants received expert video instructions and were instructed to 'try to do your best in copying the movement of the expert'. The SC group was allowed to request feedback whenever they wanted during training. The feedback consisted of 1) CMAS score, 2) posterior and sagittal videos of the last trial and 3) an external focus verbal cue on how to improve their execution. The participants were told to lower their score and they knew the lower the score, the better. The YK group received feedback after the same trial on which their matched participant in the SC group had requested feedback. Data of twenty-two participants (50% in SC group) was analyzed. Pre-test and training CMAS scores between groups were equal (p > 0.05). In the anticipated condition, the SC group (1.7 ± 0.9) had better CMAS scores than the YK group (2.4 ± 1.1) at the retention test (p < 0.001). Additionally, in the anticipated condition, the SC group showed improved movement execution during immediate-post (2.0 ± 1.1) compared to pre-test (3.0 ± 1.0), which was maintained during retention (p < 0.001). The YK group also improved in the anticipated condition during immediate-post (1.8 ± 1.1) compared to pre-test (2.6 ± 1.0) (p < 0.001) but showed decreased movement execution during retention compared to immediate-post test (p = 0.001). In conclusion, self-controlled timing of feedback resulted in better learning and greater improvements in movement execution compared to the control group in the anticipated condition. Self-controlled timing of feedback seems beneficial in optimizing movement execution in SSC and is advised to be implemented in ACL injury prevention programs.