AthLead

Athlead is an AI-powered sports talent discovery & ranking platform built for SIH 2025 — Ministry of Youth Affairs & Sports, Government of India

The main goal of this project is to allow users (athletes or coaches) to register, log in securely, input performance data, and generate a performance score using a trained ML model. The generated scores are displayed visually on the Dashboard for better analysis.

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Architecture

LINK :- https://athlead-frontend.onrender.com/

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FEATURES

• AI Player Judging
• 📊 ML Score Dashboard
• 🏅 National Rankings
• 📅 Event Management
• 📰 Announcements - Ministry policy updates, news, and recruitment alerts
• 🔐 Auth System Role - based access for Athletes, Coaches, Scouts, and Admins
• 📱 Responsive UI

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🛠️ Tech Stack

Frontend

• React js (VITE)
• Tailwind css
• Lucide reacts
• Recharts
• Axios
• dayjs

Backend

• NODE JS & Express
• MongoDB & Mongoose
• JWT — Authentication & authorization
• Passport JS
• Cloudinary & Multer
• BCRYPT

ML / AI (planned integration)

• Python + FastAPI — ML inference microservice
• OpenCV + MediaPipe — Pose estimation & biomechanics
• TensorFlow / PyTorch — Performance scoring model

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📁 Project Structure

project-root/
├── frontend/
├── backend/
├── ml/
├── .env
├── README.md
└── vercel.json

frontend/
└── src/
    ├── pages/
    │   ├── Home.jsx
    │   ├── Events.jsx
    │   ├── Dashboard.jsx
    │   ├── Login.jsx
    │   └── Signup.jsx
    │
    ├── components/
    │
    ├── context/
    │   ├── AppProvider.jsx
    │   ├── IsLoggedIn.jsx
    │   └── ProtectedRoute.jsx
    │
    ├── api/ (API calls here)
    │
    ├── App.jsx
    └── main.jsx

backend/
├── config/
│   ├── db.js
│   └── passport-config.js
│
├── controllers/
│   ├── authController.js
│   ├── eventController.js
│   ├── newsController.js
│   └── scoreController.js
│
├── models/
│   ├── Users.js
│   ├── Event.js
│   └── Score.js
│
├── routes/
│   ├── userRoutes.js
│   └── eventRoutes.js
│
├── middleware/
│
├── utils/
│
├── uploads/
│
└── index.js

ml/
├── data/
├── models/
├── api.py
├── train_model.py
└── requirements.txt

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🤝 Contributing

This project was built for Smart India Hackathon 2025. Contributions, suggestions, and issue reports are welcome.

bash # Fork → clone → create branch → push → open PR git checkout -b feature/your-feature-name 

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Author

• Aarsh-HV
• ML model- Dev M

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