Tennis is in need of more analysis, not more data

If you spend enough time around tennis today, you'll hear the same message repeated: data is the future. Most players and coaches want it. Parents ask for it. Technology companies are racing to provide it. The assumption seems to be that more data automatically leads to better decisions.

Unfortunately, that's often not the case.

The biggest problem in tennis isn't a lack of data. It's a lack of scrutiny around the data we produce.

During a recent interview on The First Serve, I referenced the television show CSI. The lead investigator, Gil Grissom, was famous for constantly reminding his team to "follow the evidence". Rather than coming up with a theory and then trying to find evidence to support it, his philosophy was to gather the evidence first and allow it to lead you to the answer.

Tennis player and match analysis should work exactly the same way.

Too often, however, tennis operates in reverse. Coaches, players and parents begin with assumptions. A player serves too many first serves wide to Deuce. A player makes too many errors. A player needs a higher first serve percentage. Once the assumption has been made, the search begins for numbers to support it.

That isn't analysis. It's confirmation bias.

The purpose of analysis is not to prove that we are right. It is to discover what is true. That distinction may sound subtle, but it changes everything. Once the goal shifts from confirming a belief to uncovering reality, the way we collect, interpret and communicate information changes as well.

One of the biggest issues in tennis is that statistics are often accepted simply because they have existed for a long time. Very few people stop to ask a basic question: Does this statistic actually measure what we think it measures?

Some tennis statistics are easy to collect, easy to report and easy to understand, but they provide very little insight into performance or development. Others are fundamentally flawed because the definitions underlying them don't accurately describe what is happening on the court, and many lack the context needed to make meaningful coaching decisions.

Lazy Data

Take one of the most commonly quoted statistics in tennis: percentage won on first serve.

At first glance, it appears valuable. If a player wins 72 per cent of points when their first serve is in, that's useful information. But what exactly have we learned?

Did the serve create the pattern to win the point? Did the returner miss a put-away on shot six? Was the point won immediately or after a 12-shot rally?

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The statistic tells us the outcome, but it tells us very little about the process that created the outcome. Yet coaches, players and parents routinely make decisions based on these types of numbers.

Imagine a doctor telling a patient they are unhealthy based solely on their weight, without considering age, height, body composition, lifestyle or medical history. Most people would immediately recognise the limitation of the diagnosis. In tennis, however, we often accept equally incomplete conclusions simply because they are presented as statistics.

Lack of Definition

The problem becomes even greater when the underlying definitions are flawed.

Consider the statistic 'points won at net'. Most people assume this measures the effectiveness of a player's net game. In reality, depending on how the statistic is defined, it could be measuring something entirely different.

A player may hit a forehand winner from inside the service line without ever transitioning further forward. Another player may put a ball away after an ineffective drop shot from their opponent. Both situations can end up contributing to the same statistic. The number appears precise, but the definition behind it is vague.

When fundamentally different situations are grouped under a single label, the resulting statistic becomes difficult to trust. The data may be accurate according to the definition, but the problem is that the definition itself is poor. Yet these types of measures continue to be repeated throughout tennis because they sound analytical, even when they fail to provide genuine insight.

Lack of Context

Then there is context, arguably the most neglected element of modern tennis analysis.

Take first serve percentage. A player serves at 62 per cent. Is that good or bad? The honest answer is that nobody knows without additional information. To which side and part of the service box are they serving? Is the player missing predominantly net, wide or long? How aggressive is the first serve? What are the player's tactical intentions?

It actually ignores three of the most important aspects of playing tennis: Who is my opponent? What is the score? What are the conditions (surface, weather, etc.)?

Without context, the statistic tells us almost nothing. Yet tennis has developed a habit of treating isolated numbers as if they are self-explanatory. They're not. Numbers don't create understanding. Context creates understanding.

The Analyst

This is where the role of the analyst becomes particularly important, because analysis itself is one of the most misunderstood aspects of tennis player development at all levels. Most people don't associate an analyst with being part of a player's team; pro, college or junior.

Tennis has reached a point where almost everyone seems to think they are an analyst. The logic appears to be simple: if you can collect data, you can analyse it.

No other industry works this way.

In business, medicine, engineering and consulting, analysis is recognised as a specialised discipline. Collecting information is only the beginning. The real skill lies in developing sound methodology, creating meaningful definitions, interpreting evidence objectively and communicating findings in a way that leads to better decisions.

Yet in tennis, we regularly confuse access to data with analytical expertise. Producing statistics is not analysis.

Analysis is the disciplined process of converting evidence into understanding and understanding into action. It is the difference between reporting what happened and understanding why it happened, whether it matters and what should be done next.

Perhaps most importantly, analysis is about communication. The best insight in the world is worthless if it can't influence behaviour. An analyst's responsibility is not simply to identify patterns. It is to determine which patterns and shot sequences matter, which data sets are noise, and how those findings should be communicated to a player, coach or parent.

That requires judgement. It requires objectivity. It requires experience. It also requires the willingness to challenge assumptions, including your own.

The strongest analysts are often the people who prove themselves wrong most frequently because they are willing to follow evidence wherever it leads.

Back to CSI’s Gil Grissom

When his investigators arrived at a crime scene, they were not expected to prove a theory. They are expected to collect evidence.

Tennis analysis should start the same way. It is then the goal of the analyst to

uncover what is actually true, not to confirm what we already think.

Tennis doesn't need more data.

Instead, it needs better questions. Better methodology. Better definitions. Better context.

It also needs better analysts.

Just as Grissom taught his investigators, the job is not to follow the theory. The job is to follow the evidence.

Nicholas Scott is the co-founder of 135 Tennis Intelligence. Nick works with junior

players, college teams and professional players globally, using the 135 framework

for player development.

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