Video is rich but unstructured
Match footage contains the real football evidence, but most of it cannot be searched, compared or reused.
Ask a football question. Get an answer you can verify from the match. FIW connects the answer to the relevant events, phases and video clips.
Football has more video, data and statistics than ever. What remains missing is a shared structure that connects match evidence, context, football understanding and football applications.
Match footage contains the real football evidence, but most of it cannot be searched, compared or reused.
Passes, shots and pressures matter, but isolated events do not fully explain game state, intent, control, rhythm or why a phase changed.
Coaching, analysis, scouting, research and media often interpret the same match separately, without a shared and reusable football intelligence layer.
Useful football applications require structured evidence, domain definitions, context and verified football knowledge they can reason from.
Football Intelligence Workflow (FIW) is the working environment and controlled workflow that brings match video, football questions, AI analysis and football professionals together.
AI helps review the relevant evidence and prepare an answer. A football-informed human checks what is accepted. Every verified result remains connected to the original match video.
Import a match or selected clips.
Begin with a concrete football question.
Review the relevant video evidence with AI-supported football analysis.
A football-informed human checks the observations and answer.
Return a concise answer with the supporting clips.
FIW shortens the path from a specific football question to a concise, evidence-backed answer. The result remains connected to the events, phases and original match video behind it.
Begin with a concrete question from match review, game planning or player feedback.
Identify the Football Events and phases that are relevant to the question.
Check every accepted observation against the original match video and its context.
Deliver a concise explanation, the relevant clips and a traceable connection to the match evidence.
The first practical FIW workflow focuses on helping coaches and analysts move from football questions to verified answers and relevant match clips.
Move from a match question to the events, phases and clips that explain what happened.
Analyse specific football concepts through expert questions and verified match evidence.
Build concise, evidence-backed understanding from relevant opponent and team situations.
Connect explanations directly to the moments and sequences visible in the match.
Provide coaches and analysts with concise outputs rather than longer reports or more disconnected data.
Keep every accepted observation traceable to the original video, event and match context.
Scouting, sporting direction, academies, research, media, APIs and integrations remain future FOS application areas. The shared FOS Core can grow across football, while each organisation's Team Intelligence, data, priorities and applications remain private.
Football Operating System (FOS) is a layered architecture that transforms match video into structured, reusable football intelligence.
Applications can share the same football intelligence foundation instead of building football understanding from scratch.
FOS is an independent football intelligence architecture with its own domain logic, event structures, verification process and evolving knowledge base. Different AI models can serve as analytical engines without FOS being dependent on any single model.
FIW is the operational workflow connecting match evidence, verification and Football Intelligence across this architecture. Applications, APIs and integrations are future application areas built on this shared foundation.
The architecture begins with match video. Human-guided event inputs form Football Events. Verification and learning connect those events to Football Intelligence through definitions, expert questions and football reasoning. Optional team inputs can form Team Intelligence before intelligence supports applications, APIs and integrations.
Football Operating System learns only from observations that can be verified against the match evidence.
A human verifies whether an observation is clearly visible. Visible observations are described precisely and recorded as verified learning. Observations that are not visible are removed. Root cause analysis reviews football knowledge, input and visibility, and AI instructions. Improvements are then returned to a repeated review cycle.
FIW is being developed and tested with real match footage and football professionals.
We are interested in working with coaches, analysts, clubs and academies who want to test the workflow using their own match footage and football questions.
A pilot combines AI-supported analysis with human verification and returns concise answers with the supporting video clips. Tell us briefly about your footage, your role and the questions you want to explore.
Your message has been sent successfully.
I will get back to you as soon as possible.