Recently, the development of smart sports technologies has taken a new direction in the sports world. This advancement is achieved by fusing bioinformatics and Information Technologies (ITs) to present new opportunities for improving performance via smart training systems. This study aimed to present an innovative electronic training device through the design and implementation of an Internet of Things (IoT)-enabled intelligent biomechanical training system (IoT-ESBS), intended to improve three critical 3D kinematic variables of the forehand stroke in table tennis. Practically, there were three objectives for the study: developing a specialized tool for biomechanical improvement utilizing IOT sensors and real-time data processing, examining the statistical variations between pre-and post-test measurements within both experimental and control groups, and comparing the post-test results between the two groups regarding key 3D kinematic parameters to assess the precision of the proposed IT enhanced system. The experimental sample includes 14 right-handed male students who were randomly partitioned into n = 7 for both experimental and control groups. Six players were excluded based on non-compliance with training or left-handedness. The findings demonstrated that the custom-designed training device significantly contributed to the development of key biomechanical components of the forehand stroke. Notable statistical differences were observed between pre-and post-test results within the experimental group, all in favor of the post-test outcomes. Additionally, significant differences emerged in the post-test comparisons between the experimental and control groups, highlighting the efficacy of the device as a specialized training tool for performance enhancement in table tennis.