Sports Intelligence Institution

We interrogate the analytical foundations of football's most consequential decisions — and build the systems that act on what we find.

The research is public. The infrastructure behind it is operational. Both are growing.


Every layer of a modern recruitment operation — the data provider, the model, the shortlist, the recommendation — inherits the blind spots of the layer below it. A metric that structurally miscounts what happened on the pitch produces a model that systematically misprices players. The model produces a shortlist that excludes candidates the data never saw.

From STATSWING Research SW-R-2026-001

The industry-standard metric for aerial ability — the "aerial duel" — records a contest only when both players leave the ground. Situations where a player wins the ball without jumping, where positioning resolves the contest before contact, where the ball is claimed unchallenged because the opponent declined to compete — none of these register in the data.

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These gaps are structural — embedded in the measurement conventions the field takes for granted. They cannot be detected from inside the system that produced them.

One acquisition informed by a single unexamined metric costs eight figures. Independent intelligence that would have caught it costs a fraction of one per cent of the transfer fee.

For clubs, agents, analysts, journalists, and investors in professional football.

01

Intelligence Briefs

Structured analytical assessments tailored to a specific decision. Each brief applies proprietary frameworks to produce intelligence that existing tools and data providers structurally cannot generate. Output varies by decision context — the same analytical pipeline produces different emphasis, framing, and recommendation architecture depending on who is consuming it and what is at stake.

Player Assessment Team Assessment Market Timing

Confidential to the purchasing party. Scope, timeline, and pricing per engagement.

02

Decision Architecture

How confidence is generated across analytical layers. How measurement gaps propagate through composite models. How to structure the decision process itself. The question is not whether your data is good — it is whether your data warrants what you are asking it to do.

Demonstrated publicly in SW-R-2026-002: Epistemic Certainty in Recruitment.

03

Audit & Red-Team

Independent examination of recruitment decision processes, data provider outputs, analytical pipelines, and AI scouting tools.

Epistemic Disclosure Framework
What is this claim conditioned on?
What would change the assessment?
What can this tool not see?
Where does this layer inherit from another?
What is the appropriate confidence for this decision?
Does this organisation's decision culture support acting on warranted conclusions — even when they conflict with existing preferences?
04

Infrastructure Advisory

Analytics architecture consulting. What to build, what to buy, how to maintain pipeline integrity within organisations.

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