Martial arts, initially developed for self-defense, have evolved into highly competitive sports that demand precise physical control and rigorous training. Lower limb injuries can result from improper execution, which can harm both the attacker and the opponent. In this study, we present a methodology for evaluating lower-limb control during practitioners’ lateral kicks. Three participants, representing novice, intermediate, and expert skill levels in Karate practice, were recorded using a standard camera and an MPU6050 accelerometer during their daily practice. For the record, they execute the lateral kick three times at three different distances from the impact distance: 130 cm, 140 cm, and 150 cm. These specific distances (130 cm, 140 cm, and 150 cm) were selected based on common practice ranges in karate training and biomechanical considerations. The results show that novice Karate practitioners lacked proper control over the lateral kick’s execution, even if they successfully hit the target. In contrast, an expert karate practitioner demonstrated precise style posture, including the ability to control the raising of the lower limb, acceleration during the strike, and a well-maintained leg position during the descent phase. Additionally, this research emphasizes the importance of precise positioning during training which can be further enhanced by integrating machine learning algorithms. By analyzing accelerometer data through supervised machine learning algorithms, we first preprocess the raw accelerometer data to remove noise and standardize the signals. Next, the data is labeled to differentiate between correct and incorrect kick executions. Finally, the labeled data is used to train a convolutional neural network (CNN) capable of classifying movement patterns based on temporal sequences and sensor signals. As part of future work, this approach can be expanded to include a real-time feedback interface that classifies correct and incorrect lateral kick executions, providing practitioners with immediate guidance to refine their technique and reduce the risk of injury, further enhancing training outcomes.