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Paul-olulana/README.md

👋 Hi there, I'm Paul-Olulana

Welcome to my GitHub profile — where data meets football and insights turn into actionable stories. I combine analytical rigor with a passion for the game to build projects that bridge sports analytics, data science, and storytelling.

💼 About Me

  • 🎓 Role: Data Analyst | Aspiring Football Data Scientist

  • 📍 Based in: France

  • ⚽ Specialty: Applying statistical models, machine learning, and data visualization to uncover performance trends in football

  • 🚀 Currently focused on:

    • Expanding my football analytics portfolio (e.g., Expected Goals modeling, match analysis pipelines)
    • Designing insightful dashboards for player, team, and match performance
    • Exploring how data science enhances decision-making in sports

🔍 Areas of Interest

  • Football Analytics — Expected Goals (xG), player performance metrics, tactical analysis
  • Data Science & Machine Learning — Predictive modeling, clustering, NLP in sports contexts
  • Cloud Computing — Azure, AWS for scalable sports data pipelines
  • Storytelling Dashboards — Power BI, Tableau, and Python-based visual reports

📚 Currently Learning

  • 🧠 Advanced machine learning techniques for sports data
  • 📈 Event data analysis (StatsBomb, Wyscout, FBref, Understat)
  • ☁️ Cloud tools for end-to-end analytics workflows (Azure, AWS)
  • 📊 Power BI dashboard optimization for performance analytics

🤝 Open to Collaborate On

  • Football data science & analytics projects
  • Open-source sports analytics initiatives
  • Visual dashboards for sports performance and scouting

📫 Let’s Connect

🏟 Featured Projects

  • Ligue 1 Expected Goals (xG) Model — Logistic regression with isotonic calibration, producing match and player-level xG reports.
  • [Coming Soon] Match Analysis Toolkit — Python-based analysis pipeline for team scouting and opposition reports.
  • [Coming Soon] Football Performance Dashboard — Interactive Power BI dashboard tracking team & player KPIs.

🎯 Fun Facts

  • 🎮 Big fan of FIFA, Fantasy Premier League & Football Manager — I turn virtual tactics into real-world analytics projects
  • ✈️ Traveling, gym sessions, and football are my reset buttons
  • 💬 Favorite quote: "Without data, you're just another person with an opinion." – W. Edwards Deming

Always analyzing. Always learning. Always creating value through football data. ⚽📊

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  1. Ligue1-xG-Model Ligue1-xG-Model Public

    Logistic regression-based Expected Goals (xG) model for football analytics using Ligue 1 data.

    Jupyter Notebook

  2. clinical-insight-dashboard clinical-insight-dashboard Public

    Power BI dashboard showcasing hospital performance insights, patient wait times, doctor allocation, and revenue analysis.

  3. customer-churn-dashboard customer-churn-dashboard Public

    Power BI project analyzing customer churn drivers, risk segments, and service impact with a clean star schema data model.

  4. Financial-dashboard-corevista Financial-dashboard-corevista Public

    Profit & Loss Dashboard in Power BI for a fictional company – CoreVista Group.

  5. Sportify-Playlist-Analysis Sportify-Playlist-Analysis Public

    A project analyzing Spotify playlists (2010–2023) using R. Includes scripts for data cleaning, exploration, and visualization, along with RMarkdown reports and a dynamic HTML dashboard showcasing t…

    HTML