When the Data Cells Are Empty: Football and the Limits of Every Analytical Framework

When the Data Cells Are Empty: Football and the Limits of Every Analytical Framework

I received the report at eleven o'clock at night, when the traffic outside my apartment in São Paulo still refused to quiet down. It was a nine-dimension analysis, following the strict procedure my newsroom has applied for years: every framework must carry evidence, every conclusion must be anchored to a specific information point, every judgment must come with a confidence level. I opened the file and scrolled down. Dimension one, tactics and technique. Empty. Dimension two, club finance and the transfer market. Empty. Dimension three, results and the public-opinion cycle. Empty. Nine dimensions, nine times the same exhausted refrain: "Insufficient information to assess."

I sat still for a long while in front of the glowing screen. Because I had just realized something my profession had spent years refusing to look at directly: data does not generate meaning on its own. However meticulous a framework may be, however finely sliced, it remains an empty mould until a human being stuffs a fact, a fragment of a life, a sigh into it.

I closed the laptop. Outside, a few hours earlier, a domestic Brazilian league match had just ended. The stands had emptied, but a small group still lingered near the gate, smoking, arguing about a corner kick in the eighty-ninth minute. None of them held a data sheet. None of them knew the home side's xG. Yet all of them knew exactly what had happened, and why it hurt the way it did.

That emptiness is not a failure of technology; it is the nature of memory - we do not recall a match through numbers, we recall it through the position of a face in the stands.

Context: an industry that sold its soul to a spreadsheet

Over the past fifteen years, the way the world talks about football has changed at the root. If my generation of commentators grew up alongside live match reports and the scream of a reporter when the ball hits the net, the current generation grows up alongside dashboards. Elite football is now an ecosystem in which every decision - from a seventieth-minute substitution to spending one hundred million euros on a twenty-three-year-old centre-back - must pass through a data filter.

I want to tell you a small story. In 2026, when I was still green and just entering the profession, my editor at a student sports outlet sent back a draft I had written about Brazil's defeat to Belgium in Kazan. He said the piece lacked professionalism, contained not a single number, no tactical diagram, no analysis of why Belgium's coach had read Brazil's back-three system. "Are you writing sports journalism or short fiction?" he asked.

I remember staying silent. Because the only thing I had in that piece was a middle-aged man who sat quietly for twenty minutes after the final whistle, eyes red, hands clutching the national team's scarf. He said one sentence to me that I copied into my notebook without adding or removing anything: "This team grew up with me, and now a part of it has just died."

The piece was called unprofessional, yet it was shared more than two thousand times. Not because it was better than the others, but because it touched the one thing no analytical table on earth can measure: collective grief.

Today, nearly a decade later, the newsroom lights are still on and I am still here, still receiving those nine-dimension reports with confidence levels attached. I do not dismiss them. I use them every day. I am only asking myself: have we traded something important for a professionalism that is too complete?

During that period, new metrics were born and sanctified. xG - expected goals - became the measure of chance quality. PPDA - passes allowed per defensive action - became the measure of pressing intensity. UEFA's FFP and then the Premier League's PSR became financial barriers. Every league now has its own data room; every major club has an analytics department with dozens of staff. Football has become an industry capable of quantifying almost everything.

But what that empty report showed me that night was not the limit of data. It was the misalignment between an industry building skyscrapers on the assumption that everything is measurable, and a sport born out of things that are not.

Core: seven territories that data passes through but never touches

Over the years, I have prepared reports for hundreds of matches. I have sat in the data rooms of clubs in Brazil, in Europe, at international tournaments. I have watched analysts use fifteen different metrics to explain why a striker is in decline, and I have watched that same striker score three goals the next match after his wife gave birth.

That is the first gap. Metrics cannot capture the human factor: a divorce, a pregnancy, a death.

I remember being in Qatar in 2026 to cover the World Cup final. I sat in the mixed zone after the final between Argentina and France at Lusail Stadium - a match that ended three-three after one hundred and twenty minutes, with Argentina winning four-two on penalties. Beside me, colleagues were pounding their keyboards, citing xG, pass counts, average running distance. I, meanwhile, was stuck on a different image: an elderly Argentine woman in row fourteen, her hands trembling as they stroked a scarf, telling me in Spanish laced with the Italian of a second-generation immigrant: "I waited thirty-six years to see him smile like that."

Thirty-six years. Metrics have no unit for thirty-six years. There is no xG for patience, no PPDA for a nation's waiting.

That was the truth I learned on arriving in Qatar: analytical tables tell you how a match unfolded, but they do not tell you why millions of people wept at home. And it is precisely that gap between "how it unfolded" and "why people wept" that houses a football that all data forgets.

Three years later, when I began writing in depth about Brazilian football, I recognized the second gap. No financial model can value a contract in units of loyalty.

This statement may sound poetic, and I must be wary of my own guiding principle. But I stand by it with a concrete example. When a twenty-seven-year-old South American player is about to move to a European club for a transfer fee of eighteen million euros, most experts' models will calculate value based on goal production, age, remaining mileage, pass completion, comparable transfer precedents. That is all fine. But no model accounts for one variable: after he leaves, the player will leave behind for the hometown fans a loop - a loop of waiting for next season, a loop of hoping his son will one day wear the old club's shirt.

I said this to one of my editors last year, and I hold to it still: what is more toxic than transfer fees in today's market is the signing fee paid to free agents. Because a transfer fee passes through multiple layers of bookkeeping scrutiny, while a signing fee circumvents the core oversight of FFP by turning a major investment into an off-the-books transaction. This is a stance I will not compromise on, regardless of who calls it "football modernized".

The third gap is where analytics departments most often break down. The goalkeeping ability on the ball has been sanctified to the point that the position's core reflexes are being systematically devalued.

I know this sounds paradoxical. In an era when goalkeepers are expected to play with the ball like midfielders, saying this borders on heresy. But I have spent many hours reviewing matches and spotted a pattern: the world's most expensive goalkeepers today are usually those who excel at distribution and are only average at pure shot-stopping. Meanwhile, a generation of keepers who excel only at reflexes - the ones I call "classical gatekeepers" - is being steadily pushed to the market's margins, accepting lower wages, accepting smaller clubs, even though their shot-stopping ranks among the continent's best.

In a recent report I prepared for a club in Rio Grande do Sul, I recommended they sign a thirty-three-year-old goalkeeper who had just conceded a lot of goals because his team played an overly risky defensive game. The xG metrics said this keeper had negative efficiency. But watching the video back, I counted at least seventeen crucial saves over the season made without any system to protect him. He was still considered "a goalkeeper of the past". That is a mistake data is directly causing.

The fourth gap - and the most painful for the writing profession - is that data cannot capture transformation. A defeat does not become a victory in a spreadsheet; it becomes a victory inside a person, years later, in another place, under another name.

I went to Maracanã in the summer of 2026, when the pandemic left the stadium's seventy-eight thousand eight hundred and thirty-eight seats empty. Only an old security guard was sweeping leaves. I sat down beside him, and he told me about Zico's debut in 2026, about the 2026 defeat to Uruguay, about final nights when he could not remember the score but remembered exactly the feeling of the whole stand singing together. I wrote a piece about that conversation, with no data analysis in it. It remains the most-read piece of my career to this day.

Transformation in football happens slowly. It does not happen in seventy minutes. It happens across seasons, across generations. A club losing a quarter-final can lead a ten-year-old in a small town to never choose football again. Or conversely, it can lead him to choose football again and become a hero fifteen years later. No chart can predict the percentage probability of those two outcomes.

The fifth gap I want to name is the "marginal shadow zones". Any analytical framework that attends only to players and coaches is omitting ninety percent of the people who make football what it is.

We all know that when a match is cancelled for rain, ticket offices, street vendors, motorbike drivers, freelance photographers, stadium security all lose a day's income. But no metric folds that into "the economic impact of the match". Football is sponsored by television, sponsored by corporations, sponsored by investment funds - but it is fed by the people standing outside the frame. Any analytical framework that ignores them is producing a distorted image of football, like photographing a building only from the roof and calling it the whole building.

The sixth gap is memory. Football is one of the few sports in which a result matters only when placed beside a memory that came before it. When Brazil lost to Uruguay in 2026 at Maracanã, that defeat was not just a defeat. It became the Maracanazo - a word capitalized in every history book. It would be meaningless for anyone to analyse that match with xG, because xG would not tell us why an entire Brazilian generation had to live through that humiliation. Football has not only the laws of the match but the laws of a community of memory.

I learned this on the night in Kazan - and later, on the night in Lusail, when I realized I was standing amid three loops stacked on top of each other: the loop of a nation waiting for its first title in thirty-six years, the loop of a player playing the last match of his career, and the loop of a young reporter like me witnessing something he had only read about in history books. The loop does not exist for us to endure, but for us to catch sight of ourselves in time.

And the seventh gap, perhaps the largest, is the difference between a player and a person. Modern football builds an entire industry around turning players into valuable assets. But anyone who has met a retired player at thirty-four knows that beneath the shirt is a person with insecurities, wounds, abandoned dreams. When Lamine Yamal scored from outside the box in the Euro 2026 semi-final on the nineteenth of July, two thousand twenty-four - he was sixteen years and three hundred sixty-two days old - analytical tables immediately found metrics: shot velocity, shot position, shot difficulty. But no table said that behind that boy was an immigrant family, a poor neighbourhood, a generation of Spaniards who had never seen their national team win a major trophy in years. That day, a Spanish fan told me amid the roar: "This kid never lived through our era of winning everything, yet he's teaching us to hope again."

That very moment made me rewrite the entire first chapter of a book I have been incubating.

Contrarian angle: sanctifying the spreadsheet is making football poorer, not richer

There is a popular view I once held, and no longer hold: that the growth of data analytics will make football more transparent, more scientific, more stable. It sounds very reasonable, does it not? It is repeated at sports conferences, in analytics experts' presentations, in the work of a new generation of journalists.

I believe the opposite is true. The sanctification of data does not make football richer in experience. It is steadily choking the regions of football that need to be viewed with a different eye.

Take the transfer market. Last summer, European clubs spent at record levels, with many deals priced by algorithm-driven models. The result is that clubs are becoming increasingly homogenized: they buy players with the same metrics, the same age, the same statistical profile. Football is losing diversity. A striker with an unusual style, average metrics, but a perfect fit for a specific system will be overlooked; a striker with superb metrics but a fit for nobody will be bought at a high price.

That is a structural distortion. And I believe it is leading clubs to pay dearly for the very "unquantifiable" regions they thought they had eliminated.

But there is another truth I want to state, and it may be hard to hear: precisely because data can never capture football's full truth, analytical tables risk becoming a weapon for manipulating public opinion. Once a metrics framework is accepted as objective, whoever controls those metrics can shape how a community sees a player, a coach, a club. This is happening, and it is happening quietly. Analytics departments today do not merely offer sporting recommendations; they participate in shaping the image of an entire generation of players.

This does not mean we should throw the spreadsheet away. It means we should hold it with more vigilance, recognizing that any metric is a contract: to measure one thing, we must give up measuring another. And when we forget that, we begin to believe we have seen the whole picture.

But we have not. We never will.

Takeaway: an open question for young writers

At twenty-six, I write about sport to understand why people stay together. I have passed through three great loops in my working life: the night in Kazan, when I learned how a nation holds its collective wound; the empty summer at Maracanã, when I learned that football exists even when no one is watching; and the night in Lusail, when I realized memory is not a data table but a living body, always changing with each generation.

That empty report taught me one final lesson, which I want to hand to young writers trying to break into this profession: a beautiful analytical framework will never replace a person who has been listened to. You can spend hundreds of hours building the world's most beautiful template, but if you never meet a man weeping after the final whistle, you are only talking about a match you do not understand.

Because a match takes place on the pitch, but its meaning lives in the people outside it. And whenever we forget that, we are no longer writing about football at all.

I am still wondering, at twenty-six, whether I have enough time to write about football the way I believe is right. Perhaps not. But I will try.