AI-Powered Basketball Shooting Trainer

AI & Machine Learning

Project Overview

The client wanted a smart basketball training system that could track shooting accuracy, analyze player actions, and provide real-time feedback. The goal was to build a mobile and web-based application similar to Home Court but with additional features. The app needed to detect makes and attempts, classify different shot types (jump shots, set shots, free throws, three-pointers, hook shots, bank shots, and contested shots), and provide probability-based analysis to help players and coaches refine their shooting techniques.

Our Contribution

🎯 Developed an AI-powered basketball tracking system for mobile and web. 🎯 Implemented shot detection technology to track makes and attempts in real-time. 🎯 Designed an action recognition system to classify different shot types like jump shots, free throws, and contested shots.

Our Contribution

🎯 Built a probability-based scoring system to analyze shot difficulty and accuracy. 🎯 Integrated a training feedback module to provide performance insights for players and coaches. 🎯 Optimized the system for fast processing and smooth user experience on both mobile and web platforms.

KEY FEATURES

  • Real Time Shot Detection & Classification

    Accurately tracks makes and misses while classifying shot types such as jump shots, free throws, and contested shots using AI and computer vision.

  • Probability-Based Shooting Analysis

    Analyzes shot difficulty and success rate with machine learning to give players actionable insights for improving accuracy and consistency.

Tool & Technologies

Customer Feedback

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John Doe

Codetic

Results

The app made basketball shooting training more advanced and data-driven, allowing players to track their performance, understand their shooting habits, and receive detailed feedback. With real-time shot tracking, action recognition, and probability-based analysis, coaches could now train players more effectively and refine their shooting techniques with AI-driven insights.

Deliverables

Shot Type Recognition Module

Implemented deep learning models to distinguish between various basketball shot styles automatically.

Scoring & Difficulty Analysis Engine

Built a statistical engine to evaluate shot quality and difficulty based on real-time data and probabilities.

AI Based Shot Tracking System

Developed for both mobile and web platforms to monitor shooting performance in real-time.

Training Feedback Dashboard

Provided players and coaches with detailed performance reports and personalized feedback for skill enhancement.

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