Project Overview
A comprehensive data analytics platform that combines natural language queries with football match statistics. Features AI-powered insights, player performance analysis, and predictive modeling using Supabase for real-time data processing.
This contest-winning project demonstrates advanced natural language to SQL conversion, real-time database integration, and sophisticated sports data visualization techniques to create an intuitive analytics platform for football enthusiasts.
Technical Stack
Database: Supabase (PostgreSQL), Real-time subscriptions
Frontend: React, TypeScript, D3.js visualizations
AI Integration: LangChain, OpenAI GPT-4, RAG pipeline
Deployment: Vercel, Edge Functions
Key Features
Natural Language Queries
Ask questions in plain English and get SQL results
Real-time Analytics
Live match data integration with instant updates
Player Performance
Comprehensive player statistics and analysis
Match Predictions
AI-powered match outcome predictions
Interactive Visualizations
Dynamic charts and graphs with D3.js
Fantasy Insights
Data-driven fantasy football recommendations
Project Screenshots
Implementation Highlights
Natural Language Processing
- •Advanced prompt engineering for SQL generation
- •Context-aware query understanding
- •Real-time semantic analysis of user intent
Database Architecture
- •Optimized PostgreSQL schema design
- •Supabase integration for real-time data
- •Efficient indexing for complex queries
AI Integration
- •LangChain framework for RAG implementation
- •Vector embeddings for semantic search
- •OpenAI GPT-4 for intelligent query generation
User Experience
- •Responsive design for all devices
- •Interactive data visualizations with D3.js
- •Real-time feedback and error handling