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Hi, I'm Edd

Edd Webster

Football Data Scientist ⚽📊.

Expertise in:

  • Football Analytics
  • Data Science and Machine Learning
  • Python
  • R
  • SQL
  • Tableau

👋 About Me

I am an experienced Data Science and Football Analytics professional with 5+ years of professional experience, currently working in my third season in elite sport with Ludonautics. Previously I was the First Team Lead Data Scientist at Leicester City Football Club, and Data Scientist for 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:

CV Badge EddWebster.com Badge LinkedIn Badge GitHub Badge HackerRank Badge Coder Rank Badge Tableau Badge


📚 Code

Although a little out of date now (with code I would dearly like to refactor), the code in my football_analytics GitHub repository can be found in the notebooks subfolder, of which the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:

  1. Webscraping
  2. Data Parsing
  3. Data Engineering
  4. Data Unification
  5. Data Analysis

📊 Data Visualisation and Tableau

For Tableau dashboards produced, please see my Tableau Public profile: public.tableau.com/profile/edd.webster.

Examples dashboards:


⚒️ Tech Stack

I am comfortable working with the following languages and software:

Python:


Python
Jupyter Notebooks
pandas
NumPy
Scikit Learn
matplotlib
PySpark

Other Data Science languages and tools:


R
R Studio
Tidyverse
Tableau
Power BI
Databricks
Airflow
AWS
Docker

📰 Articles


🧑‍🎓 Courses


📈 GitHub Stats

Edd's Github Stats


⭐ Football Analytics GitHub Stars History

Star tracker for the football_analytics repository of open-source football analysis projects and resources.

Football Analytics GitHub Stars History


📫 Contact

For more information, I am available through all the following channels:

EddWebster.com Badge Email Badge LinkedIn Badge Twitter Badge Linktree Badge About.me Badge

Edd Webster's Projects

playerdetection icon playerdetection

Player detection and ball detection in football matches using image processing(opencv).

reinforcement-learning icon reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

scraperfc icon scraperfc

Python package for scraping soccer data from a variety of sources

soccer_analytics icon soccer_analytics

Python project trying to facilitate and being a starting point for soccer analytics projects.

soccer_xg icon soccer_xg

A Python package for training and analyzing expected goals (xG) models in soccer.

socceraction icon socceraction

Convert existing soccer event stream data to SPADL and value player actions

soccerdata icon soccerdata

⛏⚽ Scrape soccer data from Club Elo, ESPN, FBref, FiveThirtyEight, Football-Data.co.uk, SoFIFA and WhoScored.

soccermaticsforpython icon soccermaticsforpython

This repo is dedicated for people getting started with Python using the concepts derived from the book Soccermatics (Sumpter 2016)

soccermix icon soccermix

SoccerMix is a soft clustering technique based on mixture models that decomposes event stream data into a number of prototypical actions of a specific type, location, and direction.

soccerplots icon soccerplots

A Python package for data visualisation for football analytics.

soccertrackingdata3 icon soccertrackingdata3

python 3 version of TrackingData, written by Laurie Shaw at Harvard Data Science Initiative. Re-written and updated by Jeff Balkanski

spam-detector icon spam-detector

Developing a Python-based spam detector using the Naive Bayes approach.

spatialsocceranalysis icon spatialsocceranalysis

This is a series of projects slowly building of StatsBomb's datasets. I am attempting to apply spatial analytic techniques and libraries to the problem of analyzing soccer information. This is entirely python based

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