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# Penalty Blog
<div align="center">
<a href="">[](https://pypi.org/project/penaltyblog/)</a>
<a href="https://codecov.io/github/martineastwood/penaltyblog" >
<img src="https://codecov.io/github/martineastwood/penaltyblog/branch/master/graph/badge.svg?token=P0WDHRGIG2"/>
</a>
<a href="">[](https://pypi.org/project/penaltyblog/)</a>
<a href="">[](https://pepy.tech/project/penaltyblog)</a>
<a href="">[](https://opensource.org/licenses/MIT)</a>
<a href="">[](https://github.com/psf/black)</a>
<a href="">[](https://github.com/pre-commit/pre-commit)</a>
</div>
<div align="center">
<img src="logo.png" alt="Penalty Blog Logo" width="200">
</div>
# penaltyblog: Football Data & Modelling Made Easy
**penaltyblog** is a production-ready Python package designed for football (soccer) analytics, providing powerful tools from [pena.lt/y/blog](https://pena.lt/y/blog) for data analysis, outcome modelling, and betting insights. Optimized with Cython, **penaltyblog** delivers high-performance modelling to power faster, efficient predictions.
## Features
- 🔄 **Streamline JSON Workflows with MatchFlow:** Process nested football data using a lazy, streaming pipeline built for JSON. Filter, select, flatten, join, group, and summarize large datasets without loading everything into memory.
- 📊 **Model Matches Efficiently:** High-performance implementations of Poisson, Bivariate Poisson, Dixon-Coles, and other advanced statistical models, optimized with Cython for rapid analysis.
- ⚽ **Scrape Data:** Collect match statistics from sources like FBRef, Understat, Club Elo, and Fantasy Premier League.
- 💰 **Bet Smarter:** Precisely estimate probabilities for Asian handicaps, over/under totals, match outcomes, and more.
- 🏆 **Rank Teams:** Evaluate team strengths with sophisticated methods including Elo, Massey, Colley, and Pi ratings.
- 📈 **Decode Bookmaker Odds:** Accurately extract implied probabilities by removing bookmaker margins (overrounds).
- 🎯 **Fantasy Football Optimisation:** Mathematically optimize your fantasy football squad to maximize performance.
- 🎨 **Visualize with Style:** Create publication-ready pitch visualizations and data flow diagrams with customizable themes, supporting multiple data providers and flexible layouts.
Take your football analytics and betting strategy to the next level with **penaltyblog** 🚀
## Installation
```bash
pip install penaltyblog
```
## 🚀 Quick Start - Try it Now!
Run these examples directly in your browser (no installation required):
| Example | Description | Colab |
|---------|-------------|-------|
| **Predict Soccer Match Results** | Build a match prediction model from scratch | [](https://colab.research.google.com/drive/1GjrDG_iq_9_lxEQK_aBmr-jCCCnFt0v7?usp=sharing) |
| **Process Soccer Data the Easy Way** | Lazy processing of football data using Matchflow | [](https://colab.research.google.com/drive/1rRJV8mNOTLTXmn5cOGT4faxIwIP44pC-?usp=sharing) |
| **Calculate Massey Ratings** | Calculate teams' attack and defense strengths | [](https://colab.research.google.com/drive/1d_WPJwQgrogeSI9oIO9fY8s18CPPZ8nL?usp=sharing) |
| **Use Pi Ratings** | Like Elo ratings, but better | [](https://colab.research.google.com/drive/12qEDCNYG-FFHOJ_kURe0cm80sScandyh?usp=sharing) |
| **Create Interactive Charts** | Create your own interactive football vizualisations | [](https://colab.research.google.com/drive/1xFfIdvmbFcjHlS_2eHEu3NxD-xLNrbpY?usp=sharing) |
| **Work Directly With Statsbomb Data** | Connect directly to Statsbomb's API, including their free open data sets | [](https://colab.research.google.com/drive/1xFfIdvmbFcjHlS_2eHEu3NxD-xLNrbpY?usp=sharing) |
| **Calculate Implied Probabilities** | Calculate implied probabilities from bookmaker's odds | [](https://colab.research.google.com/drive/1o-tOetyWmSY_1WczN8WhWsl62Uz5T65F?usp=sharing) |
## Documentation
Learn more about how to utilize `penaltyblog` by exploring the [official documentation](https://penaltyblog.readthedocs.io/en/latest/) and detailed examples:
- [Processing football event data with MatchFlow](https://penaltyblog.readthedocs.io/en/latest/matchflow/index.html)
- [Scraping football data](https://penaltyblog.readthedocs.io/en/latest/scrapers/index.html)
- [Predicting football matches and betting markets](https://penaltyblog.readthedocs.io/en/latest/models/index.html)
- [Estimating implied odds from bookmaker prices](https://penaltyblog.readthedocs.io/en/latest/implied/index.html)
- [Calculating Massey, Colley, Pi, and Elo ratings](https://penaltyblog.readthedocs.io/en/latest/ratings/index.html)
- [Calculating metrics such as Ranked Probability Scores](https://penaltyblog.readthedocs.io/en/latest/metrics/index.html)
## Why Penaltyblog?
Unlike many football analytics resources that are academic, one-off, or hard to scale, `penaltyblog` is designed from the ground up to be **production-ready**, **performance-optimized**, and **practically useful**.
It combines advanced statistical models, efficient implementations (via **Cython**), and real-world workflows, from scraping public data to modelling outcomes and optimising fantasy teams.
Built by [Martin Eastwood](https://pena.lt/y/about), who has worked with football clubs, governing bodies, player agencies and betting syndicates worldwide, `penaltyblog` is the foundation for football analytics.
Whether you're a club analyst, independent researcher, or just data-curious, `penaltyblog` gives you the tools to go from data to insight - fast, flexibly, and with confidence.
## Support & Collaboration
If you're working at a football club, agency, or organisation and want help applying these tools to your own data or workflows, I'm open to:
- 📂 Integration support
- 🔧 Custom model development
- 🧠 Technical collaboration on football analytics projects
➡️ Get in touch [here](https://pena.lt/y/contact)
Raw data
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Optimized with Cython, **penaltyblog** delivers high-performance modelling to power faster, efficient predictions.\n\n## Features\n\n- \ud83d\udd04 **Streamline JSON Workflows with MatchFlow:** Process nested football data using a lazy, streaming pipeline built for JSON. Filter, select, flatten, join, group, and summarize large datasets without loading everything into memory.\n- \ud83d\udcca **Model Matches Efficiently:** High-performance implementations of Poisson, Bivariate Poisson, Dixon-Coles, and other advanced statistical models, optimized with Cython for rapid analysis.\n- \u26bd **Scrape Data:** Collect match statistics from sources like FBRef, Understat, Club Elo, and Fantasy Premier League.\n- \ud83d\udcb0 **Bet Smarter:** Precisely estimate probabilities for Asian handicaps, over/under totals, match outcomes, and more.\n- \ud83c\udfc6 **Rank Teams:** Evaluate team strengths with sophisticated methods including Elo, Massey, Colley, and Pi ratings.\n- \ud83d\udcc8 **Decode Bookmaker Odds:** Accurately extract implied probabilities by removing bookmaker margins (overrounds).\n- \ud83c\udfaf **Fantasy Football Optimisation:** Mathematically optimize your fantasy football squad to maximize performance.\n- \ud83c\udfa8 **Visualize with Style:** Create publication-ready pitch visualizations and data flow diagrams with customizable themes, supporting multiple data providers and flexible layouts.\n\nTake your football analytics and betting strategy to the next level with **penaltyblog** \ud83d\ude80\n\n## Installation\n\n```bash\npip install penaltyblog\n```\n\n## \ud83d\ude80 Quick Start - Try it Now!\n\nRun these examples directly in your browser (no installation required):\n\n| Example | Description | Colab |\n|---------|-------------|-------|\n| **Predict Soccer Match Results** | Build a match prediction model from scratch | [](https://colab.research.google.com/drive/1GjrDG_iq_9_lxEQK_aBmr-jCCCnFt0v7?usp=sharing) |\n| **Process Soccer Data the Easy Way** | Lazy processing of football data using Matchflow | [](https://colab.research.google.com/drive/1rRJV8mNOTLTXmn5cOGT4faxIwIP44pC-?usp=sharing) |\n| **Calculate Massey Ratings** | Calculate teams' attack and defense strengths | [](https://colab.research.google.com/drive/1d_WPJwQgrogeSI9oIO9fY8s18CPPZ8nL?usp=sharing) |\n| **Use Pi Ratings** | Like Elo ratings, but better | [](https://colab.research.google.com/drive/12qEDCNYG-FFHOJ_kURe0cm80sScandyh?usp=sharing) |\n| **Create Interactive Charts** | Create your own interactive football vizualisations | [](https://colab.research.google.com/drive/1xFfIdvmbFcjHlS_2eHEu3NxD-xLNrbpY?usp=sharing) |\n| **Work Directly With Statsbomb Data** | Connect directly to Statsbomb's API, including their free open data sets | [](https://colab.research.google.com/drive/1xFfIdvmbFcjHlS_2eHEu3NxD-xLNrbpY?usp=sharing) |\n| **Calculate Implied Probabilities** | Calculate implied probabilities from bookmaker's odds | [](https://colab.research.google.com/drive/1o-tOetyWmSY_1WczN8WhWsl62Uz5T65F?usp=sharing) |\n\n\n## Documentation\n\nLearn more about how to utilize `penaltyblog` by exploring the [official documentation](https://penaltyblog.readthedocs.io/en/latest/) and detailed examples:\n\n- [Processing football event data with MatchFlow](https://penaltyblog.readthedocs.io/en/latest/matchflow/index.html)\n- [Scraping football data](https://penaltyblog.readthedocs.io/en/latest/scrapers/index.html)\n- [Predicting football matches and betting markets](https://penaltyblog.readthedocs.io/en/latest/models/index.html)\n- [Estimating implied odds from bookmaker prices](https://penaltyblog.readthedocs.io/en/latest/implied/index.html)\n- [Calculating Massey, Colley, Pi, and Elo ratings](https://penaltyblog.readthedocs.io/en/latest/ratings/index.html)\n- [Calculating metrics such as Ranked Probability Scores](https://penaltyblog.readthedocs.io/en/latest/metrics/index.html)\n\n## Why Penaltyblog?\n\nUnlike many football analytics resources that are academic, one-off, or hard to scale, `penaltyblog` is designed from the ground up to be **production-ready**, **performance-optimized**, and **practically useful**.\n\nIt combines advanced statistical models, efficient implementations (via **Cython**), and real-world workflows, from scraping public data to modelling outcomes and optimising fantasy teams.\n\nBuilt by [Martin Eastwood](https://pena.lt/y/about), who has worked with football clubs, governing bodies, player agencies and betting syndicates worldwide, `penaltyblog` is the foundation for football analytics.\n\nWhether you're a club analyst, independent researcher, or just data-curious, `penaltyblog` gives you the tools to go from data to insight - fast, flexibly, and with confidence.\n\n## Support & Collaboration\n\nIf you're working at a football club, agency, or organisation and want help applying these tools to your own data or workflows, I'm open to:\n\n- \ud83d\udcc2 Integration support\n- \ud83d\udd27 Custom model development\n- \ud83e\udde0 Technical collaboration on football analytics projects\n\n\u27a1\ufe0f Get in touch [here](https://pena.lt/y/contact)\n",
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