🎯 Saturday Tatts Lotto Scraper & Analyzer

A comprehensive bash-based tool for scraping Saturday Tatts Lotto results from Australia and providing statistical analysis for number recommendations.

Bash Statistics Australia Educational

📈 Live Lotto Stats

Up-to-date statistics from winning_numbers.csv and supplementary_numbers.csv

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Total Draws
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Date Range
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Most Frequent Winning Number
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Least Frequent Winning Number
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Most Frequent Supplementary
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Least Frequent Supplementary
Last updated: ...

🚀 Key Features

Discover what makes this tool powerful and unique for lottery analysis

Automated Scraping

Fetches historical Saturday Tatts Lotto results from 1986-2025 with smart updates that only process new draws and terminate early after 5 consecutive skips.

Auto Data Cleaning

Built-in CSV corruption detection and repair. Automatically removes corrupted data before analysis to ensure reliable results.

Statistical Analysis

Calculates odds and probabilities for each number using advanced frequency analysis and probability calculations.

Smart Recommendations

Generates 10 diverse number combinations based on historical frequency while ensuring diversity and avoiding past winners.

Cross-Platform

Works seamlessly on macOS, Linux, and other Unix systems with automatic dependency detection and installation.

Educational Focus

Designed for educational and research purposes to understand lottery number patterns and statistical concepts.

📊 Project Statistics

Key metrics and capabilities of the Saturday Tatts Lotto Scraper

6
Main Numbers
45
Number Range
2
Supplementary Numbers
10
Recommendations Generated
2000+
Historical Draws
4
Supported Platforms

💻 Interactive Demo

See the tool in action with a simulated terminal interface

Terminal Simulation

$ ./master_lotto.sh
Saturday Tatts Lotto Scraper & Analyzer ====================================== 1. Scrape Lotto Results 2. Parse Data & Recommend Entries (with auto-clean) 3. Check & Install Requirements 4. Exit Enter your choice: 1
🕷️ Starting Saturday Tatts Lotto scraper... 📊 Fetching data from au.lottonumbers.com ✅ Found 2026 draws (1986-2025) 💾 Saving to winning_numbers.csv 🎉 Scraping completed successfully!

⚙️ Installation

Get started in minutes with our simple installation process

# Clone the repository
git clone https://github.com/JDsnyke/saturday-tatts-lotto-scraper.git
cd saturday-tatts-lotto-scraper

# Make scripts executable
chmod +x *.sh

# Run the master script
./master_lotto.sh
View on GitHub Download ZIP

📖 Usage Guide

Learn how to effectively use the tool for lottery analysis

1. Scrape Lotto Results

Fetches historical data from au.lottonumbers.com, automatically skipping existing data to avoid duplicates.

2. Parse Data & Recommend

Analyzes the scraped data using frequency analysis and generates 10 diverse number combinations. Includes automatic CSV cleaning for data integrity.

3. Check Requirements

Ensures all dependencies (curl, pup, awk, grep) are installed on your system.

Recommended Entries (with odds and percentages):
===============================================
 1)  6 (1 in 28, 3.46%)  10 (1 in 42, 2.38%)  15 (1 in 36, 2.81%)  
     22 (1 in 46, 2.16%)  34 (1 in 46, 2.16%)  42 (1 in 27, 3.68%)
 2)  1 (1 in 30, 3.25%)   5 (1 in 38, 2.60%)  16 (1 in 42, 2.38%)  
     26 (1 in 51, 1.95%)  29 (1 in 35, 2.81%)  44 (1 in 42, 2.38%)

🏗️ Architecture

Understanding the project structure and components

Lotto/
├── master_lotto.sh          # Main menu interface
├── scrape_lotto_results.sh  # Web scraper for lotto results
├── parse_and_recommend.sh   # Statistical analysis & recommendations (with auto-clean)
├── clean_csv.sh            # Manual CSV cleaning utility
├── requirements.sh          # Dependency checker/installer
├── generate_stats.sh        # Generate statistics for website
├── winning_numbers.csv      # Scraped winning numbers
├── supplementary_numbers.csv # Scraped supplementary numbers
├── index.html              # GitHub Pages website
├── assets/
│   ├── lotto_stats.json    # Live statistics data
│   └── favicon.svg         # Website favicon
└── README.md               # Documentation