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Football-analytics

Football-analytics

Open source Jupyter Notebook
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About Football-analytics

Exploring football and other sports through data. Includes analyses of match events, player performance, xG models, tactical visualizations, and predictive insights.

Platforms

Web Self-hosted

Languages

Jupyter Notebook

Links

⚽ Football Analytics

✍️ Medium: https://medium.com/@vickyfrissdekereki
πŸ’Ό LinkedIn: https://www.linkedin.com/in/victoria-friss-de-kereki/
πŸ“§ Email: [email protected]
πŸ”— Live App: https://football-league-simulator.streamlit.app/


This repository is a collection of projects where I explore sports through data. It brings together different analyses I’ve worked on β€” from understanding player performance to building predictive models β€” using a mix of statistics, data visualisation, and machine learning. The idea is simple: use data to better understand what's happening on the pitch.


πŸ“Š What you'll find here

Across the notebooks and code in this repo, I focus on:

  • Exploring sports datasets and identifying useful patterns
  • Analysing player and team performance
  • Working with metrics like expected goals (xG) and expected pass
  • Building models to predict match outcomes
  • Creating visualisations to make insights clearer

This is an evolving project as I continue experimenting and improving my approach.


πŸ› οΈ Tools & Libraries

Most of the work is done in Python, using:

  • pandas & numpy for data manipulation
  • matplotlib & seaborn for visualisation
  • scikit-learn for modelling
  • Jupyter notebooks for exploration

πŸ“‚ Project Structure

Football-analytics/
β”‚
β”œβ”€β”€ # Notebooks, analysis, experiments
β”œβ”€β”€ Datasets/ # datasets (raw and processed)
β”œβ”€β”€ Images and others/ # plots and figures
└── README.md


🎯 Why this project

I enjoy working at the intersection of sports and data. This repo is a way for me to apply data science to something I genuinely care about, while building a portfolio in sports analytics and continuing to develop my technical and analytical skills.


πŸ‘€ About Me

Hi, I'm Victoria Friss de Kereki - an applied data scientist focused on sports analytics, performance modelling, and simulation in sport.

I work on projects that combine sports data, machine learning, and context-driven analysis to better understand performance and decision-making in sport. Alongside this, I have experience working with data across fintech, healthcare, and e-commerce, which has shaped how I approach real-world problems.

Outside of data science, I'm a competitive athlete - a World Champion U57 Natural Strongwoman and weightlifter - which gives me a practical perspective on performance beyond the data.

I also write about sports analytics and data science on Medium, where I share insights, ideas, and projects I’m working on.

I’m currently building my portfolio in sports analytics and am particularly interested in opportunities in this space.


⭐

If you find this interesting, feel free to star the repo or get in touch.