Football Data Scientist @ Leicester City Football Club β½π.
Expertise in:
- Football Analytics
- Data Science and Machine Learning
- Python
- R
- SQL
- Tableau
I have been working in business and data analysis for both first team football and commercial industries for six years, where I currently work as the First Team Lead Data Scientist @ Leicester City Football Club, previously Analytics FC and the LEGO Group. I enjoy exploring and working in the fields of data science, machine learning, statistics, data engineering, data visualisation, and football analytics, for which this GitHub profile includes much of my publicly available work around these topics.
Please see my football_analytics
repository for a collection of football analytics projects, data, and analysis that I have created, with links to publicly available resources in the football analytics community.
For more information, see the following...
Although a little out of date now (with code I would dearly like to refactor), the code in my football_analytics
GitHub repository can be found in the notebooks subfolder, of which the workflow is divided into the following:
- Webscraping;
- Data Parsing;
- Data Engineering;
- Data Unification; and
- Data Analysis - projects include working with Tracking data, constructing VAEP models (as introduced by SciSports), building xG models using Logistic Regression, Random Forests and Gradient Boosted Decision Tree algorithms such as XGBoost and CatBoost, and analysing player similarity using PCA and K-Means clustering).
For Tableau dashboards produced, please see my Tableau Public profile: public.tableau.com/profile/edd.webster.
Examples dashboards:
I am comfortable working with the following languages and software:
Python:
Other Data Science languages and tools:
Star tracker for the football_analytics
repository of open-source football analysis projects and resources.
For more information, I am available through all the following channels: