NBA IQ

NBA IQ is an NBA analytics and machine learning platform built with React, TypeScript, Flask, and Supabase.

Features

• Match prediction with backend ML inference
• MVP analysis and team comparison views
• Authenticated user flow with Supabase
• Responsive frontend built with Tailwind CSS

Tech Stack

Frontend

• React 19 + TypeScript
• Vite
• Tailwind CSS
• Axios

Backend

• Flask
• scikit-learn, XGBoost, pandas, numpy
• Supabase + Flask-CORS

Prerequisites

• Node.js 18+
• npm
• Python 3.8+
• pip
• Supabase project credentials

Setup

1) Clone

git clone https://github.com/albrthuynh/NBAIQ.git
cd NBAIQ

2) Environment variables

Create .env.local in the project root:

SUPABASE_URL=your_supabase_project_url
SUPABASE_ANON_KEY=your_supabase_anon_key
SUPABASE_SERVICE_ROLE=your_supabase_service_role_key

3) Backend

cd backend
pip install -r requirements.txt

4) Frontend

cd frontend
npm install

Run

Backend

cd backend
python app.py

Backend runs at http://localhost:5000.

Frontend

cd frontend
npm run dev

Frontend runs at http://localhost:5173 (or http://localhost:5174 if occupied).

API

POST /api/predict

Request body:

{
  "home_team": "Chicago Bulls",
  "home_season": 2025,
  "away_team": "Indiana Pacers",
  "away_season": 2025
}

Response body:

{
  "home_team": "Chicago Bulls",
  "home_season": 2025,
  "away_team": "Indiana Pacers",
  "away_season": 2025,
  "predicted_winner": "Chicago Bulls",
  "home_win_probability": 0.7,
  "away_win_probability": 0.3,
  "model": "RandomForestClassifier"
}

Testing

cd backend
python -m pytest test_api.py

If pytest is missing in your environment:

pip install pytest

Notes

• Backend CORS currently allows http://localhost:5173 and http://localhost:5174.
• Update allowed origins in backend/app.py if your frontend runs on a different port.