The market
How the AI and Data Market in Sport Actually Behaves.
Sizing, growth rates and hiring-competition context. The version we share when a hiring exec or a board asks: how serious is this, really?
A Growing Pitch. Not Enough Players.
Demand for AI, ML and data talent in sport has accelerated past anything we've seen in fifteen years of technical recruitment. The market has crossed from speculative interest into operational investment - and the supply of qualified candidates has not kept up.
Sport is also distinct from other AI-hiring markets in one important way: domain literacy matters as much as the technical stack. The best ML engineer in fintech is rarely the right hire for a Premier League scouting function. The combination of technical depth and genuine sport understanding is rare - and that's the dynamic shaping every search at this level.
That's what makes specialism worth the premium - and why generalist recruiters quietly struggle here.
Three Structural Shifts Driving Every Search.
Decisioning has moved. Five years ago analytics teams produced reports for someone else to act on. Today the analytics function is in the room when decisions are made. The candidates worth hiring need the technical depth to build the system and the communication to operate inside it.
The talent pool is small and contested. Sport is competing for the same engineers and scientists that finance, big tech and consultancies want. The strongest candidates in sport rarely reach an active job market.
Hiring speed wins more than ever. Where a process takes weeks, the candidate is gone. Most of our successful searches close because we run a faster, more informed process than the rest of the market.
Hiring Inside This Market?
Tell us what you're building. We'll come back with an honest read on whether we can help - and if we can't, who might.
