Prospective measzures of high knee abduction moment (KAM) during landing have identified female athletes at increased risk for ACL injury. However, dedicated biomechanical laboratories, which require costly measurement tools and labor intensive data collection sessions, are necessary to ascertain the measurements. The purpose of this study was to develop and validate a clinic-based ACL injury risk prediction algorithm. The hypothesis was that clinically obtainable correlates derived from highly predictive 3D motion analysis models would demonstrate high accuracy for determination of high KAM status.
