AI Football Analytics. Sharper Decisions for Every Club.
AI football analytics for decision-makers. Game-Intuit turns match data into measurable game intelligence, helping you sharpen match decisions and de-risk recruitment.
Innovation Partner & Client
Our Edge
Analysis. Clarity. Speed.
Game-Intuit is built on three principles: AI that reads the game, insights coaches can act on immediately, and analysis delivered less than a hour — not days.
01
GI ANALYSIS
GI Analysis Model
Our AI models read match footage and surface the patterns that matter, tactical trends, spatial behaviour, players decision-making. Not raw numbers. Measurable game intelligence that tells coaches what's happening and why.
02
EXECUTION & USABILITY
Clarity Over Volume
Most platforms give you more stats. We give you better answers. Our AI maps the relationships between variables to surface the logic behind each passage of play. Every screen, report, and recommendation is designed so coaches and analysts can act on what they see, not just what happened, but why.
03
AT SPEED & SCALE
Fast Analysis. Built to Scale
We deliver frame-by-frame match analysis in under 60 minutes, not days. By combining deep game context with high-speed AI, we offer a cost-effective alternative to manual video processing, whether you're reviewing one fixture or scouting across a league, the analysis keeps pace with your schedule.
1hr
Frame-by-Frame match analysis under 1 hr
Data.
Analysis
Complete
Research-proven AI. Built for sharper football decisions.
From scouting to post-match analysis, Game-Intuit gives coaches and analysts sharper answers, faster. Our AI is grounded in published research, developed with leading sports scientists at Loughborough University.
MIT Sloan Sports Analytics - March, 2024
Player Pressure Map - A Novel Representation of Pressure in Soccer for Evaluating Player Performance in Different Game Contexts
Knowledge-Based Systems - January, 2024
A Machine Learning Framework for Quantifying In-Game Space-Control Efficiency in Football
IEEE - July, 2023
Embedding Contextual Information through Reward Shaping in Multi-Agent Learning: A Case Study from Google Football
MDPI - Sports - October, 2018
Player Tracking Data Analytics as a Tool for Physical Performance Management in Football: A Case Study from Chelsea Football Club Academy
Get started with GI analysis.
Turn your thousands of data, stats and metrics into one clear view, so every football decision lands with confidence.