“Better data simply means better football.” These words from Poland international Jan Bednarek capture not only the direction in which modern football is moving, but also the growing awareness among players themselves. Over the past two decades, data has travelled a long way: from a curiosity in the back rooms of baseball analysts to a strategic asset managed at the level of club boards, federations and investors.

Today, it is no longer enough simply to “have data”. What matters is who controls it — organisationally, technologically and legally. It is no accident that Laurie Shaw, a former adviser to the UK Treasury, joined Manchester City as a data scientist. Nor is it a curiosity that Leatherhead F.C., a semi-professional club in the English lower leagues, has used IBM Watson tools to analyse opponents. Football, at every level, is becoming a contest for insights — not only on the pitch, but also in code, algorithms and decision-making processes.

From my perspective, the most interesting questions are no longer whether data matters, but how we understand it, how we use it and whether it truly belongs to us. Because in a world where everything can be measured, the greatest advantage lies not with those who know more, but with those who listen better.

Today’s matches generate almost unimaginable quantities of information. In Spain’s La Liga, a single game now produces more than 3.5m data points, collected by a system of 16 cameras tracking the movement of players. By comparison, the English Premier League records around 1.5m data points per match at 25 frames per second. At the World Cup, the scale is larger still: during the 2022 tournament, every match tracked the movement of the ball and 29 points on each player’s body at a frequency of 50Hz, while the official ball, fitted with a sensor, transmitted data 500 times a second. It is a genuine digital tsunami.

Paradoxically, the sheer volume of information does not guarantee success. Millions of measurements are useless without the ability to extract meaning from them. Every match is a flood of numbers, but the advantage belongs to those who can turn information into practical insight rather than drown in it. Modern technology creates new possibilities, but also poses a challenge: how can clubs draw useful knowledge from an ocean of statistics and translate it into better tactics and training? It is the depth of analysis — the ability to detect hidden patterns and trends — that creates the real edge, and the real magic, of data in sport.

Crucially, technology is becoming more accessible to smaller clubs as well. Not long ago, only the richest could afford large analytics teams and advanced systems. That is changing. In 2020, for example, the Premier League launched a centralised Insight Feed, giving all clubs access to synchronised tracking and event data — such as shot speed or defensive line breaks — thereby levelling access to advanced statistics.

Similar solutions operate in Poland through systems such as TRACAB and Panoris. New innovations are also emerging, including the Polish start-up ReSpo.Vision, which uses artificial intelligence to produce full 3D match data from a single camera, eliminating the need for expensive infrastructure. ReSpo.Vision has also received FIFA certification for its accuracy and is already used by the Polish Football Association for advanced analysis.

Such technologies are democratising football data, allowing even lower-budget clubs to use forms of analysis that were once the preserve of the giants. The message is clear: nobody wants to be left behind in the race for a data advantage. Innovation means that even David now has a slingshot fitted with a digital sight.

The question of data ownership sits at the intersection of law and economics. Should information about us — our transactions, habits and sporting performance — belong to us like property, to be used or disposed of as we choose?

Classical law and economics teaches that clear property rights support efficiency: when ownership is known, goods can be traded more easily and investment in their development becomes more likely. But data is a peculiar asset. Richard Posner, the former judge and influential economist, observed as early as the 1980s that privacy protection — and therefore, in practice, restricting access to personal data — can be economically inefficient. In his view, much of the information we hide is concealed not for the common good, but for private advantage, which in economic terms can lead to waste and the shifting of costs on to others.

On the other hand, granting full property rights over personal data is hardly a simple recipe for success. Property rights work well for physical goods: if I sell a car, I stop using it, and the new owner has exclusive control. Information does not work like that. I can share it and still possess it. If every click or training metric had to be the subject of an individual transaction, we would sink into a sea of bureaucracy and transaction costs. Researchers point out that creating a system of “micropayments” for the mass use of data would be either impossible or uneconomic, even if advocates of blockchain and Web3.0 take a different view. In any case, an individual data point about one person is worth only a tiny fraction of a large dataset. So even if individuals “owned” their data, they would have weak bargaining power. The result? Giants holding vast quantities of information would still dictate the terms, while ordinary people would gain little beyond an illusory sense of control.

This does not mean, however, that we are condemned to choose between two extremes: total privacy, blocking the flow of information, or full commercialisation of data with little regard for individual rights. The solutions differ on the two sides of the Atlantic. In Europe, the approach is more regulatory: personal data is protected almost as a human right, as reflected in the GDPR, which gives individuals, among other things, the right to transfer or erase their data. In the United States, the approach is more market-based: there is no single comprehensive federal statute, but rather sector-specific rules and an emphasis on not stifling innovation. The American assumption is that freedom also includes the freedom of business to use data, provided it does not cause harm. Privacy issues are often dealt with after the fact, through the activity of the Federal Trade Commission, which has brought hundreds of cases against companies misusing data. Interestingly, in the United States, treating data as property also faces constitutional obstacles: restricting the circulation of information may be seen as a restriction on free speech. As a result, the balance between privacy protection and economic freedom differs sharply from country to country.

When we talk about football data, a fundamental question arises: who owns it? Is information about a player’s performance — his sprints, heart rate or distance covered — the property of the club that employs him? The league that organises the competition? Or the athlete himself? This dilemma is not merely theoretical. Players are increasingly asserting claims over their data. In 2022, FIFPRO, the global players’ union, published a Player Data Rights Charter, stressing that the player should decide who has access to information about his own body. In other words, the athlete, too, is increasingly seen as the owner of his biological and performance data — a challenge to established practice.

Different stakeholders approach this question in different ways.

Clubs. Clubs employ and pay players, remunerating them not only for their presence and performance on the pitch, but also for their image on and around it. They create training conditions, invest in data collection — whether through GPS vests or camera systems — and seek to treat data as a resource that provides both sporting and business advantage. Training and match data form part of a club’s knowledge base, much like tactics or the expertise of the coaching staff.

Players. Players argue that data about their bodies and their game is an extension of the self, and that they should therefore have control over it. They fear abuse — for example, the use of sensitive health data against them in contract negotiations — and demand transparency and consent for the commercial use of their performance information.

Leagues and federations. Competition organisers claim rights over match data as part of the entertainment product. They create central databases for entire leagues, believing this raises the level of competition: a rising tide lifts all boats when insights are shared with all clubs. League data is also a source of revenue, sold to broadcasters, sponsors and betting companies.

Platforms and technology providers. Companies that collect and analyse data — GPS-tracker suppliers, analytics software providers and services such as Opta — often become the de facto custodians of the information. They turn raw numbers into valuable statistics and frequently monetise them, selling analysis to the media, supplying fantasy-football products or feeding the sports-betting industry. This raises another question: whose interests should prevail — those of commercial platforms, or those of the clubs and players who generate the data?

Even the most advanced technology is useless if a club fails to build the right analytical culture. The point is for data to permeate the daily life of the organisation — from the president’s office to the coaching staff and the players themselves. The world’s best clubs invest not only in hardware and software, but also in the people and processes that turn statistics into decisions.

Chelsea offers a good example. There, data has become part of the training routine. When players enter the dressing room after a match, they see their statistics on monitors — distance covered, number of sprints, maximum speed. Similar practices, perhaps with a slight delay and in a different scope, are now part of daily life in other leagues and clubs, including in Poland. Such transparency, and the element of competition it introduces, encourages players to engage with analysis.

On the training pitch, an analyst with a laptop accompanies the coaching staff, providing live performance reports on every player. Within an hour of the session, coaches receive statistical summaries and detailed charts that immediately shape the plan for the following day. This is not a gadget. It is an integral part of the team’s work. Numbers are instantly translated into decisions: who needs a lighter session, who should work on speed, how workloads should be adjusted.

The attitude of leaders is crucial. When Jürgen Klopp took over Liverpool FC, the analytics team was finally able to spread its wings. The manager fully integrated them into the decision-making process, creating a shared strategy for data-driven recruitment and tactics. Although the club had hired the respected scientist Dr Ian Graham as early as 2012, the real breakthrough came only when the vision of the coach and the work of the data team aligned. This shows that even in elite organisations, analytical culture begins with openness among executives and coaching staff to knowledge derived from numbers.

Interestingly, a strong data culture can offset some financial disadvantages. Brentford and Brighton — smaller clubs in the English game — have used analytics to identify undervalued players who later made a major impact. With budgets limited in comparison with the league’s elite, they have consistently achieved above-average results, punching above their financial weight. Similar stories are familiar from the past: money does not always beat smart strategy. Moneyball showed this in baseball, while Leicester City’s 2016 triumph in football was attributed in part to an analytical approach to squad building. The lesson is clear. Numbers can give the underdog a weapon against the giants — provided the club creates an environment in which analytics is understood and accepted by everyone, from the boardroom to the dressing room.

From the perspective of a football club’s finances, data is also a matter of investment and return. The biggest clubs now spend considerable sums on analytics — often six- or even seven-figure amounts each year — and expect tangible results. What does investing in data deliver? First, the optimisation of sporting performance: better coaching decisions can translate into victories, prize money and higher player valuations. Second, deeper fan engagement: today’s supporters watch matches armed with apps and graphics, while interactive statistics increase viewing appeal and the value of competitions to sponsors. Third, data becomes a product in itself. Clubs and leagues sell access to it to the media through visualisations and infographics, offer it to sponsors as part of marketing packages — “Fastest Player of the Match, presented by Company X” — and supply betting companies with rapid statistical feeds to set odds. In other words, every data point is a potential story, or a potential commodity.

Yet, as with any investment, there are challenges. The first is diminishing returns. Another expensive platform or wholesale dataset may deliver ever smaller improvements if the club lacks the capacity to use it intelligently. It is easy to fall into the trap of analysis paralysis, where too much information makes decisions harder rather than easier. From a financial and investment perspective, data projects should be treated like any other venture: they should be assessed against return-on-investment metrics. If a club buys a new system or hires an analyst, it should be clear what problem that decision solves. Will it help the coach win more matches? Will the marketing department attract more fans? Will injury costs be reduced through better workload monitoring? And if so, can that effect be measured in money or points in the table? Such an approach would protect clubs from spending on impressive gadgets that do not translate into results. In many cases, however, this discipline remains more theory than daily practice in football.

Regulatory risks are also on the horizon. As awareness of data privacy grows, legal changes may limit the free use of information about players. In many cases, a player’s consent to various forms of commercial use of GPS results or health parameters is built into his professional football contract, which complicates the business model of sports analytics outside the club environment. On the other hand, the industry may develop its own solutions before regulators step in. One idea is to give players greater control and a share in the value of their data, for example through data wallets in contracts: secure portals where a player could view all his data and decide whom to share it with.

There is also talk of co-operative models for data-sharing, under which all parties — from the club to the player — participate in the profits generated by the information they jointly create. These concepts may sound futuristic, but they indicate the direction of travel. Finding a balance between innovation and individual rights will become essential. Investors and managers must therefore consider not only the profit potential of data, but also the cost of possible regulation and the need for a fairer distribution of benefits in the future.

As this shows, the real advantage does not come from the sheer mass of numbers, but from the wisdom with which they are used.

As a CFO and a sports enthusiast, I see data as a compass. It points the way, but it is the leaders on and off the pitch who must decide where to go. Even the most impressive statistical databases and the sharpest algorithms will not win a match without a human being capable of drawing the right conclusions from them. In football, victory does not belong to those who collect the most charts, but to those who turn them into better tactics, better training and better personnel decisions.

We live in an age in which information is like an ocean: some drown in it, while others learn to swim.

The latter, combining cool analysis with vision and football intuition, can bring about genuine transformation. Technology woven together with human judgment becomes football’s magic: it allows the weaker to challenge the stronger, and the strong to reach for excellence. Data is the fuel of this transformation, the spark that can ignite the flame of innovation. But the spark alone is not enough. Everything depends on whether we can turn knowledge from data into concrete action on the pitch and in the business of the club.

So will the future belong to those who collect the most numbers, or to those who look at those numbers and see what others have missed? The final answer lies with us. Data will give an advantage only to those who ask the right questions and draw the right lessons. Can we make it our compass on the road to success? That is the question I would leave with every leader, coach and supporter.