vickyfriss/Football-analytics
vickyfriss/Football-analytics has 46 GitHub stars and 5 forks. Star changes are not measured yet. Last checked 2026-11-14 02:46 UTC. Last push 2026-11-03.
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Exploring football and other sports through data. Includes analyses of match events, player performance, xG models, tactical visualizations, and predictive insights.
DatosREADME.md
Original⚽ Football Analytics
✍️ Medium: https://medium.com/@vickyfrissdekereki
💼 LinkedIn: https://www.linkedin.com/in/victoria-friss-de-kereki/
📧 Email: [email protected]
🔗 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 — from understanding player performance to building predictive models — 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.
📊 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.
🛠️ 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
📂 Project Structure
Football-analytics/
│
├── # Notebooks, analysis, experiments
├── Datasets/ # datasets (raw and processed)
├── 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.
👤 About Me
Hi, I'm Victoria Friss de Kereki - a Football Data Analyst turning football data into data-driven insights, with a growing focus on probabilistic 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.
This repo remains my space for personal projects and continued learning in football analytics.
⭐
If you find this interesting, feel free to star the repo or get in touch.
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