In sports science, the automation of performance analysis and assessment is urgently required to increase the evaluation accuracy and decrease the performance analysis time of a subject. Existing methods of performance analysis and assessment are either performed manuallybased onhumanexperts’opinions orusingmotionanalysissoftware, i.e., biomechanical analysis software, to assess only one side of a subject. Terefore, we propose an automated system for performance analysis and assessment that can be used for any human movement. Te performance of any skill can be described by a curve depicting the joint angle over the time required to perform a skill. In this study, we focus on only 14 body joints, and each joint comprises three angles. Te proposed system comprises three main stages. In the frst stage, data are obtained using motion capture inertial measurement unit sensors from top professional fghters/players while they are performing a certain skill. In the second stage, the collected sensor data obtained are input to the biomechanical software to extract the player’s joint angle curve. Finally, each joint angle curve is processed using a continuous wavelet transform to extract the main curve points (i.e., peaks and valleys). Finally, after extracting the joint curves from several top players, we summarize the players’ curves based on fve statistical indicators, i.e., the minimum, maximum, mean, and mean ± standard deviation. Tese fve summarized curves are regarded as standard performance curves for the joint angle. When a player’s joint curve is surrounded by the fve summarized curves, the performance is considered acceptable. Otherwise, the performance is considered unsatisfactory. Te proposed system is evaluated based on four diferent karate skills. Te results of the proposed system are identical to the decisions of the expert panels and are thus suitable for real-time decisions.