The Empty Analysis Factory of Modern Football

I was sitting next to a young analyst in the press box at Groupama Stadium, on the afternoon the Lyon–Marseille match was postponed by rain. He opened his laptop and showed me a twelve-page file: nine sections, sixty tables, vertical axes, horizontal axes, red-and-blue heat scales. Then he scrolled to the bottom.

In the conclusion box of the first section, the second, all the way to the ninth, the same line: "Insufficient information to analyse."

Twelve pages. Not one line of data. He laughed: "The framework is still correct, it's just missing input."

I sat quietly for a while, and what I realised had nothing to do with him. That framework is running all over football today. It is just that most of my colleagues do not leave the box empty. They fill it in. With belief, with headlines, with their readers' fear.

People call me a contrarian. I call them the crowd.

For about fifteen years now, European football has operated like a measurement industry. Every Ligue 1 match generates thousands of data points: passes, touches, distance covered, heat maps, expected goals, pressures after every duel. A single French top-flight match can generate more data than a provincial election campaign.

The industry consensus is tidy: datafication is progress. A club without an analysis department is a backward club. A journalist who cannot quote a metric is an amateur. A fan who does not read heat maps is a bumpkin. And because that consensus is so pretty, nobody bothers to ask a simple question: if the input is empty, what is the output?

Thirty-four years of watching football, from local radio broadcasts to press rooms in Moscow, Doha and Lyon, have taken me through three revolutions: pay television, social media, then data. All three promised to bring the truth closer to the audience. All three ended up producing more opinions and less truth.

In Vietnam, people still call a good match by one word: spirit. In France, they call it structure. Both are ways of avoiding the detail. I stand between two worlds: one that is dying, one that refuses to be born.

The 2026 World Cup final in Moscow, France beat Croatia 4-2. The whole world looked at the stat sheet and saw Croatia with more possession, more passes, more shots. I remember something else. France scored four goals from situations the numbers cannot name: a direct free kick, a penalty after a video review, a long-range strike, a late goal. Didier Deschamps' team did not play to keep the ball. They played to end the match. Possession is the most deceptive metric in modern football, because it measures time on the ball, not danger.

That night I went on air and declared it the highest-scoring final in history. I was wrong. The 2026 final in Stockholm, Brazil 5-2 Sweden, had seven goals. The 2026 final had six — the most in fifty-two years, but never the record. A viewer corrected me on social media within twenty minutes. I remember the feeling: saying something very loud while the data sat in my coat pocket.

Four years later, in Lusail, I stood inside the stadium with nearly ninety thousand people. Argentina drew 3-3 with France after extra time, won the shootout 4-2, Kylian Mbappé scored a hat-trick, Lionel Messi scored twice. The whole world wrote about Messi. I wrote about Mbappé. Not for the sake of going against the grain, but because I stood close enough to see what the numbers cannot: after every goal conceded the French ran less, after every equaliser the Argentinians ran more. There was a shift of rhythm in extra time that anyone in the stands could feel, and no metric recorded it.

Back to the twelve-page file. The analyst wrote in the right language, used the right terminology, invented no figure at all. He simply presented a complete framework for a match with no data. And the framework still stands. Football analysis does not collapse at the output. It collapses at the input.

In May 2026, the Bundesliga returned after the pandemic. Dortmund played Schalke in an empty stadium. The entire analysis industry had its script ready: football without crowds would be slower, duller, soulless. The ball rolled, Dortmund won 4-0, players hurled themselves at each other as if eighty thousand people were roaring. Every model was wrong, because every model was missing one variable. A stadium without spectators, as I once said, is a car park painted the colour of grass. But players are not cars.

In August 2026, Paris Saint-Germain paid 222 million euros for Neymar, breaking the world record. At the same time, in Monaco, an eighteen-year-old had just scored fifteen Ligue 1 goals. I wrote a piece that got me mocked by hundreds of accounts: that kid is worth more than the 222-million man. A few weeks later, PSG put 180 million euros on the table for Kylian Mbappé. I was called a madman for three weeks, then a visionary for the next thirty years. What I never told anyone: I had no data at all. I had two eyes and an irritation with the crowd.

A team paid on time has excellent fighting spirit. A team three months behind on wages does not. That sounds crude, but it explains more matches than every speech about identity.

The real error of the analysis industry lies elsewhere: treating data as ritual. When a club buys a striker because his expected-goals number was high in another league, that is ritual. When a broadcaster opens its bulletin with a chart nobody explains, that is ritual. When an expert uses the phrase "high press" to describe a team he has never watched, that is ritual. Ritual can be beautiful. It just answers no question.

On 1 July 2026, at Luzhniki, Spain made more than a thousand passes and held the ball for about seventy-four percent of the time. Russia made about two hundred. Spain lost on penalties. Read only the stat sheet and you conclude football is an unfair game. Watch the match and you conclude that a thousand sideways passes do not create a single real chance.

So I still tell young people in this trade: When the whole world speaks in unison, my ears start ringing with the echo of error. An analysis department where twenty people look at the same table is not twenty analysts. It is one analyst and nineteen copyists.

I need to be clear here before I am misread, which happens a few times a year. Data is useful. A decade ago I believed in data. Now I believe my eyes. But left on its own, that sentence reads as an endorsement of intellectual laziness, and that is not what I want.

The uncomfortable part: I have also written twelve-page files. In 2026 I claimed the Moscow final was the highest-scoring in history without reopening a book. I did not invent it. I simply did not check. In this trade, not checking is a subtler form of invention.

I may also be wrong elsewhere. In ten years, machine-learning models may read things I cannot see from the stands: the breathing rhythm of a full-back in the eightieth minute, the half-second hesitation before a decisive pass. Then I will be the relic standing in the middle of the pitch with my eyes, while a computer at home already knows the score. I do not rule that out.

What I attack is not the computer, and not the analysts, who are the colleagues I respect most in the newsroom. What I attack is a habit of an entire industry: filling the empty box with anything at all, as long as the box gets filled. An empty box sells no advertising. A piece ending with "insufficient information to analyse" gets no shares. Nine full sections, hollow as they are, are always safer than one true sentence.

I do not write to be loved. I write to be read.

From next season I will ask myself before every piece: am I analysing a match, or decorating an empty box? If it is the second, I will leave the box empty and tell the reader the driest truth, that I do not know anything yet.

And so you have something to check, here is one specific prediction that could be wrong: in the coming matchday, in a game I watch live, the team with more possession will not win. Write it down, then compare. That is the only way a contrarian pays for his contrariness.