Correction of systematic errors in electronic performance and tracking systems

Abstract Electronic performance and tracking systems are becoming a standard in many sports to automate data collection gather more profound insights into game dynamics. In large soccer clubs federations, the problem is that different electronic report kinematic parameters indicators, which should be same. Furthermore, drawback recent validation studies subdivision of speed acceleration zones validating systems, as we show interdependent. We propose new method classify multidimensional outputs with clustering approach. Additionally, offer data-driven strategy reduce errors between distinct when from compared method’s effectiveness collected study. This error reduction can applied correct no available.