Open-Source Intelligence (OSINT) has traditionally been used in cybersecurity and financial markets. However, the application of OSINT in football is an emerging frontier.
What is OSINT in Football?
Every day, thousands of public data points are generated around football clubs. These range from official financial disclosures and injury reports to local news articles and fan sentiment on social media.
By aggregating and analyzing this unstructured data, FootINet builds a comprehensive picture of a team's true state, far beyond simple league tables and xG (Expected Goals).
Key Factors We Analyze
- Financial Health: Tracking stock prices of publicly traded clubs (e.g., Manchester United, Juventus).
- Squad Fatigue: Analyzing travel distances, fixture congestion, and environmental factors like stadium weather.
- Sentiment & Morale: Scanning global RSS feeds to detect boardroom instability, managerial pressure, or dressing room unrest.
The Prediction Engine
Our prediction engine doesn't just look at past results. By factoring in these external OSINT data points, we can adjust probabilities for match outcomes with unprecedented accuracy.
When a team is facing financial difficulties or their manager is under severe media pressure, their on-pitch performance often dips. FootINet captures this before the bookmakers adjust their odds.
"The game is no longer just played on the pitch. It's played in the boardroom, in the media, and in the data."
Stay tuned as we continue to refine our algorithms and expand our data sources for the 2026/2027 season.