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The scope and precision of basketball skill development are sometimes restricted using subjective evaluation and manual observation in traditional training methods. The goal of this research is to develop a complete platform that combines data analytics, machine learning, and computer vision to precisely deliver feedback on players' movements, shooting mechanics, strength training regimens, and player progress. The Computer Vision-Based Interactive Basketball Training Platform - Point Guard will use the existing literature on sports technology and methods of basketball training to present a game-changing solution for basketball training. The body will be tracked by computer vision algorithms to get quantitative feedback on a player's agility, footwork, and body alignment to refine all training paradigms. Hoop Tracking allows players to practice their shooting skills while their shot mechanics and trajectory are analyzed with state-of-the-art computer vision techniques. Strength Training is a set of individual exercise programs designed based on user feedback that emphasizes muscle-building training and training for injury prevention. Progress Tracking, in conjunction with Performance Analytics, consolidates all data from other components and feeds them into a sophisticated analytical framework used to measure individual growth, consequently giving output on a personalized training recommendation. In the end, the proposed system aims to enable members to enjoy the maximum potential of playing the sport, from the novice to the professional. The proposition is really to create a platform that amalgamates advanced technology with customization of skills and analytics for valid data that will focus on improving basketball performances.
Weerasinghe et al. (Fri,) studied this question.