In-Field Gait and Jump Analysis in Football Players with Wearable IMUS: A Real-World Validation Study

Wearable technologies are increasingly used in sports science to monitor performance, assess fatigue, and support injury prevention through real-time, in-field data collection. Among these, Inertial Measurement Units (IMUs) offer a portable alternative to laboratory-based systems. The present work proposes an in-field method for jump and gait analysis using IMUs, specifically the Muse 221e and Xsens systems, in a football setting. Data were collected from four under-18 players from Club Milano, a semi-professional Italian team (Serie D, group B). Jump analysis was performed using shank-mounted IMUs and validated with OpenCap, an open-source, markerless, portable camera-based Motion Capture solution. Gait analysis employed a novel protocol combining IMU data with OpenSim lower limb Inverse Kinematics (IK) to extract gait parameters. The results demonstrated the feasibility of the jump algorithm (mean errors in the range of 0.7 cm) and its reliability in recognizing this activity. Furthermore, gait analysis with IMU IK produced stride frequencies coherent with Hansen's model, making it a promising solution for an in-field reference methodology.