Live Betting Data Collection System

Live Betting Data Collection System

📊 Project Overview

A comprehensive real-time sports betting analytics platform built to capture, process, and analyze live betting data across multiple sports. This project demonstrates full-stack data engineering capabilities, combining web scraping, cloud infrastructure, and database management.

Duration: August 2020 - January 2022
Technologies: Python, Selenium, PostgreSQL, AWS (EC2, RDS, CloudWatch), Bash Scripting

🏗️ Architecture & Technical Implementation

Data Collection Pipeline

  • Real-time Scraping: Selenium WebDriver deployed on AWS EC2 for dynamic content extraction
  • Database Storage: PostgreSQL hosted on AWS RDS with optimized schema design
  • Cost Optimization: Automated EC2/RDS scheduling via AWS CloudWatch to minimize operational costs
  • Monitoring: Comprehensive logging system for error tracking and performance monitoring

Infrastructure Design

Live Sports Data → Selenium WebDriver (EC2) → Data Processing → PostgreSQL (RDS)
                                    ↓
                           Automated Scheduling & Monitoring

Key Technical Features

  • Automated Deployment: Complete CI/CD pipeline with bash scripts for server management
  • Fault Tolerance: Java server health checks and automatic restart capabilities
  • Data Integration: Pre-game and post-game data correlation for comprehensive analysis
  • Scalable Architecture: Designed for easy extension to additional sports and leagues

📈 Data Sample & Results

NBA Live Database Structure

The system captures comprehensive in-game metrics including:

NBA Database Sample

Data Points Collected:

  • Real-time odds movements
  • Game state information
  • Betting volume indicators
  • Historical performance metrics

🚀 Future Enhancements & Vision

Current Capabilities

  • Sports Coverage: NBA and NFL with extensible framework for additional leagues
  • Scalable Foundation: Architecture designed for easy integration of new sports and data sources

Strategic Roadmap

  • Financial Modeling: Applying quantitative finance techniques (arbitrage, options strategies) to betting markets
  • Algorithmic Trading: Developing systematic approaches to live betting opportunities
  • Market Analysis: Advanced statistical modeling of betting market inefficiencies

Business Applications

This system serves as a foundation for exploring data-driven approaches to sports betting, combining real-time analytics with financial modeling principles to identify market opportunities.

This project showcases end-to-end data engineering capabilities, from infrastructure design to real-time data processing, while demonstrating proficiency in cloud technologies and automated system management.