Analytics 101xG
Expected goals (xG), explained without the hype
xG is the most quoted number in football analytics — and the most misunderstood. Here is what the model actually measures, where it breaks, and how to use it responsibly.
· 6 min read
Football · data · code
Football data, decoded.
Football data analytics: long-form articles, YouTube walkthroughs and open code. Learn the numbers behind the game — and build with them.
- Articles
- 3
Analysis you can read
Long-form pieces on xG, datasets and modelling decisions — process over hot takes, with the code that backs them up.
Browse the blog →Walkthroughs you can watch
Step-by-step videos: data pipelines, notebooks and match analysis you can follow along and reuse in your own work.
Watch on YouTube →Code you can run
Notebooks and small tools, open on GitHub. Clone them, run them, break them and adapt them to your club or project.
See the code →Blog
View all 3 articles →Latest analysis
Deep dives into football data: methods, sources and decisions — written to be useful, not just readable.
PythonStatsBomb
Build your first football data pipeline with StatsBomb open data
Open data is the fastest way to start. This walkthrough goes from raw JSON events to a shot map in a handful of steps — the same pipeline pattern you will reuse with every public dataset.
· 7 min read
DatasetsPython
Five public football data sources you can use today
You do not need a paid provider to start learning football analytics. These five free sources cover events, results, xG, odds and historical tables — with honest notes on the trade-offs of each.
· 5 min read
YouTube
Walkthroughs
Pipelines, notebooks and match-analysis sessions — recorded as we build.
The first walkthroughs are on the way
Subscribe on YouTube and you will catch the first pipeline build as soon as it lands.
Subscribe on YouTubeCode
GitHub profile →Open notebooks & tools
Everything we build for the videos ends up here: pipelines, feature code and small utilities you can reuse.
Code drops soon
The first notebooks from the walkthroughs will be published on GitHub. Follow the profile to get them the day they land.
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What should we look at?
A dataset, a model you want to validate, a video idea, or a project for your club or company — tell us and we will get back to you within 48 hours.
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