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EuroJackpot Analyzer & Predictor 2026

  • Writer: Sofia Herrmann
    Sofia Herrmann
  • Dec 3, 2025
  • 2 min read

Updated: Jan 7

Statistical analysis tool for lottery number patterns using historical data analysis, frequency tracking, and multiple prediction algorithms. Key Features: - Web scraping for data collection - 5 prediction methodologies - Interactive React dashboard - Frequency and pattern analysis


🎯 THE CHALLENGE This project started with curiosity and with inpiration of my father:

"Can data science find patterns in randomness?" While lottery outcomes are statistically random, I wanted to build a complete data pipeline - from collection to analysis to visualization - using real-world, unpredictable data.


💡 THE APPROACH I built a full-stack analytical system: - Web scraper collecting 25+ historical draws automatically - 5 statistical prediction algorithms (frequency analysis, pattern recognition, distribution modeling) - Interactive React dashboard with real-time visualizations - Confidence scoring for each methodology


🔍 THE DISCOVERY The technical insights were fascinating: On Randomness: Even in truly random data, human psychology creates patterns we think we see. Building this taught me to distinguish between statistical significance and cognitive bias.


On Methodology: My "hot numbers" approach showed 75% confidence - not because it predicts better, but because it reflects historical frequency. This demonstrates why domain knowledge matters in data science.


On Engineering: The real challenge wasn't the statistics - it was building a robust data pipeline that handles errors, validates inputs, and presents findings clearly.


💼 WHY IT MATTERS For data analysis: This project demonstrates the complete workflow - data collection (web scraping), processing (pandas), analysis (statistical methods), and presentation (React dashboard). For critical thinking: I learned to build systems that analyze data objectively while acknowledging their limitations. The disclaimer ("lottery is random") is as important as the analysis. This project proves I can build end-to-end data solutions, not just run someone else's code.


⚙️ TECHNICAL SKILLS: Python, Web Scraping, React, Statistical Analysis, Full-Stack Development


Made for only fun purposes



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