Background Lower limb stability is pivotal to successful dynamic sporting movements, with poor stability during single leg tasks commonly associated with lower limb non-contact injuries.
Objective This study investigated stance leg frontal plane stability during a lateral bound task.
Design Players performed an infield clinical screening involving 10 alternating bounds from their left (LLEG) and right (RLEG) legs. Each bound comprised stabilisation (landing) and propulsion (lateral push off). 3D kinematic data for the stance leg (200 Hz) were captured using an automated system (CODAmotionTM) and a cluster marker set.
Setting Professional footballers currently performing in the English Football League System performed the screening.
Participants Five participants performed the screening.
Intervention/Assessment of risk factors The independent variables in this study were the players involved.
Main outcome measurements Absolute frontal plane sway (AFP-Sway) at the hip, knee and ankle were determined (Visual3DTM) and combined to provide a collective stance leg sway score (CSL-Sway) for each trial. Additionally, percentage contributions of AFP-Sway at each joint to CSL-Sway for all trials were determined and compared across players in each condition using one-way ANOVA.
Results There were CSL-Sway differences between players within each condition, accounted for by additional motions at all three lower limb joints under LLEG conditions and only hip and knee joints under RLEG conditions. Percentage individual joint contributions to CSL-Sway differed between players at the knee and ankle joints under LLEG and all joints under RLEG conditions. Both conditions revealed two distinct bounding strategies with hip or combination of hip and ankle motions contributing the most to CSL-Sway.
Conclusions Player differences in CSL-Sway, AFP-Sway and percentage joint contribution to CSL-Sway under both bounding conditions highlight the individualised nature of lateral bound strategies. Such objective assessment of stance leg stability may enable movement stability classification and ultimately aid injury risk identification.
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