How clubs should prepare their analysis department for automation

In most clubs, the conversation around automation starts with the tool.

What can be tagged automatically. What can be clipped faster. What can be retrieved without an analyst manually working through a full match. Those are valid questions, and they matter. But they are not the first questions a club should be asking.

The more important question is whether the analysis environment is actually ready for automation in the first place.

Because automation does not enter a vacuum. It enters a process, a department, and a club context that already exists. If that environment is clear, automation saves time and increases consistency. If that environment is unclear, automation usually creates more output without improving decision-making.

That distinction is going to matter more and more over the next few years.

Automation will increase output very quickly

One of the easiest mistakes clubs can make is to assume that faster production automatically leads to better analysis.

In reality, automation mostly changes how quickly material can be produced and processed. That matters, especially in environments where time is scarce. But output and clarity are not the same thing.

A club can very easily end up with:

• more clips
• more tagged moments
• more dashboards
• more pattern recognition
• more weekly reports

…while still having the same conversations in staff meetings, the same disagreements over definitions, and the same uncertainty about what actually matters.

That is why automation should be seen as an amplifier, not a solution on its own.

If the club already has shared logic, automation strengthens it. If the club does not, automation scales the confusion that is already there.

The real issue is not access, it is structure

Soon, most professional clubs will have access to similar automation capabilities. Some will get there earlier than others, but the barrier to entry is clearly falling. Over time, access alone will stop being a meaningful advantage.

What will matter is what the technology enters.

If a club’s analysis function is heavily dependent on one individual, poorly documented, or inconsistent across staff, automation will not fix those weaknesses. It will work on top of them.

That usually shows up in familiar ways. One analyst defines a pressing trigger one way, another defines it differently. The first team and academy use different language for similar moments. The game model exists in principle, but not in a form that guides coding, review, or reporting. Reports are produced every week, but the logic behind them is personal rather than shared.

In that kind of environment, automation speeds things up, but it does not make the work more aligned.

So before clubs ask how much they can automate, they should ask a more basic question:

Do we actually have a shared analysis structure for automation to sit on?

Four things need to be in place first

A club does not need a perfect environment before it can benefit from automation. But it does need a clear enough one.

In practice, there are four foundations that matter most.

1. A game model that is operational, not just conceptual

Most clubs can describe how they want to play in broad terms. Fewer clubs have turned that identity into something that consistently shapes analysis.

That difference is crucial.

If the game model is only a coaching concept, it stays too abstract. If it is operationalized, it starts to influence what gets coded, what gets reviewed, what gets highlighted, and what gets ignored.

Automation becomes useful when the club already knows what it is looking for.

Without that, the club risks collecting large amounts of tagged material without a clear link to its own playing identity.

2. Standardized analytical definitions

This is one of the biggest pressure points in performance departments.

What counts as a line-breaking pass? What qualifies as a high regain? What do we mean when we say a goal kick was “played short successfully”? What exactly is being measured when someone reports progression?

These questions sound technical, but they shape everything. If the definitions are inconsistent, the outputs will be inconsistent too, no matter how advanced the automation becomes.

Clubs do not need hundreds of perfect definitions before moving forward. But they do need agreement on the definitions that matter most in their weekly analysis cycle.

Otherwise, automation simply produces faster disagreement.

3. Documented workflows

A lot of analysis environments still run on habit rather than process.

One person knows how the opposition workflow works. One person knows how clips are named. One person knows how certain moments are tagged. One person knows which report goes to which coach and in what format.

That may function day to day, but it is fragile.

Documented workflows do not need to be complicated. They just need to be clear enough that the logic survives beyond the individual currently running it.

When workflows are documented, automation improves consistency. When they are not, automation often makes one person faster without making the department more robust.

4. Institutional ownership of the logic

This is probably the most important point.

A club can buy tools. It can hire analysts. It can build dashboards. But if the underlying logic of the analysis function still lives mainly in one person’s files, naming habits, and interpretation style, then the club does not really own its analytical intelligence.

That becomes a problem even without automation. With automation, it becomes more visible.

Because once production gets easier, the quality of the club’s internal logic becomes easier to judge. If the structure is sound, automation strengthens it. If the logic is fragmented, automation exposes that fragmentation more quickly.

The clubs that will benefit most are the ones where methodology belongs to the club, not just to the current analyst.

Where clubs usually overestimate readiness

Many clubs assume they are more ready than they really are because they already produce a lot.

They have reports. They have clips. They have dashboards. They may even have strong analysts doing very good work. But production is not the same thing as structure.

A good test of readiness is whether a new analyst could understand the club’s logic quickly, and whether the same definitions would still hold up across different staff members. If the answer is no, the priority is not more automation yet. The priority is building the environment that makes automation useful.‍

Closing thoughts

The next few years will not belong to the clubs with the most outputs. They will belong to the clubs with the clearest structures.

For leadership, the practical takeaway is simple: structure has to come before scale. Before thinking about automation as a multiplier, clubs need clarity on their game model, their key analytical definitions, and the workflow the analysis function is built around. These are not technical questions. They are organizational ones.