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Methodology

Practical implementations and approachable write-ups covering data, models, and market concepts.

Getting Started
Foundational concepts for football analytics and betting
Intro to Football Data
Data6 min read
What football data looks like, common sources, and how to ingest it for analysis.
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Intro to Football Betting
Betting6 min read
Foundations of market odds, value, and basic risk management for betting experiments.
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Spatiotemporal Graph Neural Networks
Deep learning architectures for modeling player interactions and match dynamics
Literature Review: STGNNs
Theory25 min read
A comprehensive academic review of Spatiotemporal Graph Neural Networks - from foundational neural networks to state-of-the-art architectures.
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More articles coming soon

Implementation guides, experiments & results

Miscellaneous
Standalone guides and technical deep-dives
Entity Matching
Data Engineering10 min read
Solving the challenge of linking players and teams across data sources with fuzzy matching, embeddings, and metadata.
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More articles coming soon

Data pipelines, tooling & utilities

Implementation Overview
How we apply theoretical concepts to real match data

The methodology section focuses on practical, reproducible approaches. Each article explains a specific topic, shows how data is collected and cleaned, and outlines simple code or SQL patterns to reproduce the steps. Articles are intentionally concise and actionable.