Ask where the trading team sits in a sportsbook org chart and you can usually predict how the business performs.
Where trading reports into operations, it gets measured on efficiency: cost per market, markets per trader, uptime. Where it reports into commercial, it gets measured on margin quality, competitiveness and risk outcomes. Those are different jobs, and only one of them produces an edge.
Efficiency metrics reward the wrong behaviour
A trader measured on markets covered and suspension time will optimise for exactly those things. That means wider prices, faster suspensions, more conservative limits. Each is locally sensible and collectively expensive: the book becomes less competitive, the sharp customers leave for someone else, and the recreational customers who remain make the margin look fine right up until they do not.
The damage is invisible in the short term because the margin percentage holds. What has actually happened is that margin quality has fallen — the same number now depends on customer weakness rather than pricing skill. It is the same distinction that matters in due diligence, and it matters here for the same reason: one is durable and the other is a moment.
Automation is about consistency, not headcount
Automation in trading is routinely pitched as a cost programme, which both undersells it and makes it politically difficult inside the trading team.
The real argument is consistency. A human trader managing forty in-play markets across three matches is making decisions at variable quality depending on load, time of day and how the last hour went. Sharp customers are extremely good at finding the moments when quality drops. Automation does not price better than a good trader on a good day. It prices the same at three in the morning as at kick-off, which is where the money is.
The right target is not a headcount number. It is:
- Tier one competitions: near-fully automated, with human oversight on exceptions.
- Tier two and below: automated pricing with tighter limits and human review triggers.
- Long tail and novelty: manual, with limits that reflect the pricing uncertainty.
Traders then spend their time on model tuning, exception handling and the markets where judgement genuinely adds value — which is also a considerably better job than watching a screen.
Risk appetite is set whether or not you define it
Many operators have no written risk appetite. They still have one. It is set implicitly by whoever is on shift, by the limits inherited from a previous head of trading, and by how nervous the business was the last time it took a bad result.
An explicit risk appetite answers a small number of questions and answers them at board level rather than at desk level:
- What maximum liability is acceptable, by competition and by market type?
- Which customers get restricted, at what threshold, and who signs it off?
- How much variance is the business willing to accept in exchange for competitiveness?
- What is the tolerance for a losing month, and what happens if it arrives?
Without this, restriction policy becomes the default risk management tool. Restriction works, but it is a blunt instrument that steadily narrows the customer base and creates a reputational problem that is expensive to unwind.
Competitiveness needs to be measured, not asserted
Very few operators can state where they sit against the market on price, by competition and market type, with data. Most rely on impression, or on complaints, or on a quarterly benchmark someone runs manually.
Continuous price comparison against a defined competitive set is not difficult to build and changes the conversation entirely. It turns "are we competitive?" from an opinion into a measurement, and it makes it possible to be deliberately uncompetitive in places where that is the right commercial choice — which is a legitimate strategy that only works if you know you are doing it.
What good looks like
A trading function treated as a commercial capability tends to share a few features. It reports into commercial rather than operations. It is measured on margin quality and competitiveness alongside efficiency. It has a written risk appetite that somebody senior signed. Its automation level is a deliberate figure by tier rather than an accident of history. And it can tell you, with data, where the book sits against the market this morning.
None of that is exotic. It is simply a different set of choices about where trading sits and what it is for.