AI Quantification for Every Player Decision.

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

LUinc.

LUinc.

Our Edge

AI Analysis, Execution and Speed

AI football analytics for decision-making and game intelligence. Game-Intuit turns match data into coach-ready insights, fast, so you can make better decisions that win matches and de-risk recruitment.

01

GI ANALYSIS

GI Analysis Model

Turning match data into measurable game intelligence. Our proprietary AI model quantifies how players scan, create and exploit space, and make fast decisions under pressure.

02

EXECUTION & USABILITY

Actionable Clarity Over Data and Insight Volume

Most platforms bury you in raw stats. Game-Intuit does the opposite. Our AI maps the hidden relationships between variables, to reveal the underlying logic of every play. We organise data into actions you can use, with the “why” behind each recommendation.

03

AT SPEED & SCALE

Fast Analysis. Built to Scale

We deliver frame-by-frame match analysis in under 60 minutes. We combine deep game context with high-speed AI to provide a cost-effective alternative to manual processing.

1hr

Frame-by-Frame match analysis under 1 hr

Data.

Analysis

Complete

Our AI analysis is custom-built to match your team’s needs, so you get insights that fit how you work.

Our AI analysis is custom-built to match your team’s needs, so you get insights that fit how you work.

Research proven AI,
built for match-day decisions.

Research-led AI, built for match-day decisions.

Game-Intuit is built by researchers and football data specialists. Our AI algorithms are 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.