Edd Webster Football Analytics

®️ R

General R data science libraries:

• tidyverse

• ggsoccer by Ben Torvaney - a soccer visualisation library in R
• ggshakeR by Abhishek Mishra - an analysis and visualisation R package that works with publicly available soccer data. See the following documentation [link]
• StatsBombR - an R package to easily stream StatsBomb data from the API using your log in credentials or from the Open Data GitHub repository cost free into R
• soccermatics by Joe Gallagher - an R package for the visualisation and analysis of soccer tracking and event data
• worldfootballR by Jason Zivkovic - a R package for extracting world football (soccer) data from FBref, TransferMarkt, Understat and fotmob (see guide on how to use this package [link])

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🌵 Repository Structure

The contents of this GitHub repository is organised as follows:

📂 eddwebster/football_analytics/ ➡️ central repository of code and analysis by Edd Webster 📍⚽ │ ├── 📂 dashboards/ ➡️ store of Tableau dashboards used for analysis 📊🔍 │ ├── 📂 data/ ➡️ a selection of raw and processed data extracts by various providers 💾🔍 │ ├── 📂 capology │ ├── 📂 davies │ ├── 📂 elo │ ├── 📂 fbref │ ├── 📂 fifa │ ├── 📂 guardian │ ├── 📂 metrica-sports │ ├── 📂 opta │ ├── 📂 reference │ ├── 📂 sb │ ├── 📂 shots │ ├── 📂 stats-perform │ ├── 📂 stratabet │ ├── 📂 tm │ ├── 📂 touchline-analytics │ ├── 📂 twenty-first-group │ ├── 📂 understat │ └── 📂 wyscout │ ├── 📂 docs/ ➡️ store of documentation for different vendors 📄📚 │ ├── 📂 centre-circle │ ├── 📂 metrica-sports │ ├── 📂 opta │ ├── 📂 sb │ ├── 📂 shots │ ├── 📂 stratabet │ └── 📂 wyscout │ ├── 📂 fonts/ ➡️ store of custom and externally acquired fonts used for data visualisation ✍️📄 │ ├── 📄 .gitignore ➡️ ignore unnecessary files for version control with Git 🚫📤 │ ├── 📂 img/ ➡️ store of images used for analysis including club badges, vendor logos and official media images 📷💾 │ ├── 📂 club_badges/ # badges for football clubs │ ├── 📂 edd_webster/ # images related to Edd Werbster │ ├── 📂 fig/ # generated figures derived from analysis and reports in this repository │ ├── 📂 gif/ # GIF images │ ├── 📂 memes/ # memes │ ├── 📂 pitches/ # images of football pitches and goals used mostly for Tableau visualisation │ ├── 📂 players/ # images of football players │ ├── 📂 vendors/ # logos for data vendors e.g. StatsBomb │ ├── 📂 vizpiration/ # high-quality visualisations and analysis from renowned members of the football analytics community │ └── 📂 websites-blogs/ # logos for data analysis websites and blogs e.g. Club Elo │ ├── 📂 scripts/ ➡️ store of libraries and Python and open source code 📙🛠 │ ├── 📂 notebooks/ ➡️ Jupyter notebooks for exploration and visualisation │ ├── 📄 README.md ➡️ project description and setup guide for better structure and collaboration 📖🤝 │ ├── 📂 research/ ➡️ central repository of research and publicly available resources in football analytics 📙⚽ │ ├── 📂 documents/ # documents │ ├── 📂 papers/ # published academic papers and literature │ └── 📂 slides/ # PowerPoint slides for published research │ └── 📂 video/ ➡️ store of videos used or generated for analysis 🎥💾

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📚 Source Code and Notebooks

The code in this repository is mostly written in Jupyter notebooks or Python scripts, organised in the following workflow:

• Webscraping
• Data Parsing
• Data Engineering
• Data Unification
• 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 Booested Decision Tree algorithms such as XGBoost, and analysing player similarity using PCA and K-Means clustering.

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:bookmark_tabs: Resources

:bookmark: Other Football Analytics Resources Guides

Credit to the following resources that were all used to plug gaps in this resources guide once it was published:

• analytics-handbook GitHub repo by Devin Pleuler- a GitHub repo for getting started in soccer analytics
• awesome-football by football.db (Gerald Bauer) - a collection of awesome football datasets
• awesome-football-analytics by Diego Pastor
• awesome-soccer-analytics by Matias Mascioto
• guideR by Dom Samangy - a Google spreadsheet with 200+ R resources, 100+ Python tutorials, 30+ packages, 25+ accounts to follow, 10 cheatsheets, and several free books & blogs. GitHub repo [link]
• Jan Van Haaren's Soccer Analytics Reviews:

• soccer-analytics-resources Github repo by Jan Van Haaren

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:runner: Getting Started with Football Analytics

Good resources for those new for the use of data in football:

• Articles and blog posts:

• GitHub repositories:

• Twitter threads:

• LinkedIn Posts:

• Videos:

• Glossaries:

• Podcasts:

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💾 Data

:information_source: Data Sources

Publicly available data sources and datasets relating to football, from Tracking data, Event data, aggregated player performance data, detailed match statistics, injury records and transfer values, and more.

Data sources that have been used in the code and analysis in this repository can be found in the data subfolder of this repository or in Google Drive (due to GitHub's 100mb file limit) [link]. All code however in this repository should enable you to scrape, parse, and engineer the datasets as per the output used for analysis and visualisations featured.

To learn more about the different types of data available, such as Event and Tracking data, see the "Where can I get data?" section of Devin Pleuler's socceranalyticshandbook [link].

For a quick primer of the free football data resources available, see the following Twitter thread by James Nalton [link].

Event data

Event Data is labelled data for each on-the-ball event that takes place during a game. The data is manually collected from television footage. To learn more about the data collection, see the following video [link].

Each match of event data has around 2-3 thousand individual events (rows), depending on the provider.

The main providers of this data are StatsBomb, Stats Perform (formally Opta), and Wyscout.

| Name | Comments | Source / method(s) to get the data | | ----- | -------- | ----------------------------- | | StatsBomb Open Data |