Faced with this, clubs have historically had four sensible options. Each solves part of the problem and creates a new one.
Buy generic data from a traditional vendor. Fast, affordable, reliable. But it's the same data everyone else has – zero competitive edge, and the off-the-ball world stays dark.
Hire a human analytics consultancy. Firms in this space deliver genuinely sophisticated, bespoke analysis. The catch is that humans do most of the work, so the cost per insight is high and it scales linearly – more analysis always means more hours and more invoices. Worse, the methodology is their product, so the real capability stays with the consultancy, not inside your club.
Partner with a technology firm. Now you're sharing your tactical "success recipes" with a third party – and quite possibly the same third party your rivals use. That creates an unhealthy dependency on an external vendor for something that should be your most guarded IP.
Build it in-house. The dream of full ownership, but football clubs aren't tech companies. These projects routinely take three to five years to produce meaningful results, frequently stall, and depend on recruiting and retaining data scientists who can also speak fluent football – a rare and expensive combination – while keeping pace with AI that moves faster than any single team can.
None of these are mistakes. They were the rational choice given the tools that existed. But look at them together and a pattern emerges: every option forces a trade-off between customisation and scale. You could have analysis built around your identity, or analysis that runs automatically at scale – never both, and rarely with the IP staying in your building.
