The Discipline of an Empty Data Frame

The VAR operations room sits deep beneath the San Siro stands, with no windows, so I only knew night had fallen from the hurried footsteps on the concrete floor. On 26 November 2026, matchday 12 of Serie A, Milan hosted Juventus. In the 56th minute, on my main screen, Gonzalo Higuaín put the ball in the net to make it 2-0 for the visitors. In the right-hand corner, the offside line drew a thin line: the Argentine striker stood 0.2 metres beyond Milan's last defender.

I had forty seconds. Forty seconds to decide whether to recommend that the referee review the play. I hesitated. I was afraid of being wrong, of a decision being overturned in front of tens of thousands of spectators, of misreading a single frame. I stayed silent. Milan lost 0-2.

After the match, the referee supervisor called me up and criticised me in front of the whole team. He did not say “you were wrong.” He said: “You had the data, but you didn't dare trust it.”

That sentence stayed with me for a month. I re-watched 47 similar plays, noted every frame, and built a 37-criteria checklist to standardise every decision. That checklist did not make me faster. It made me more honest.

Modern football has become a data industry. Every Serie A match generates millions of data points: passes, distance covered, expected goals, pressures. Clubs hire entire analytics departments, broadcasters build real-time graphics, and writers like me are forced to read numbers that nobody measured ten years ago.

In this profession, the hardest thing is not reading a number. The hardest thing is admitting when there is no number to read.

In October 2026, when Serie A returned in stadiums emptied by COVID-19, Milan went seven matches without a win. Public opinion blamed the attack, and the club's sale of André Silva to Monaco for 35 million euros. I did not believe that conclusion. I reopened the transition data from the last 14 matches and found a different pattern: Milan's defence lost 42% of its counter-attacking capacity without the crowd noise that drives pressing. The problem was not the striker. The problem was the operating system behind him.

I wrote a 30-page report for the editor of La Gazzetta dello Sport, proposing a three-phase recovery plan. It was published in full. But what I remember most is not the article. What I remember most is the time before writing it: the days I sat in front of an incomplete dataset and asked myself whether I was seeing something real, or merely painting over a gap.

The VAR trade taught me one thing. An empty data frame is not an invitation to invent an answer. It is a reminder that the most honest verdict is sometimes: not enough information.

In football analysis, writers meet three kinds of gaps, and each demands a different response.

The first is a technical gap: the data exists but was not captured properly. A tracking system fails, an angle is blocked, a statistics table is truncated. Here the answer is to return to the source and re-run the process, not to speculate. In the VAR room, when the offside feed breaks, we are not allowed to “estimate roughly.” We call the technician.

The second is a methodological gap: the data exists but does not measure what people think it measures. A high expected-goals figure does not automatically mean a team attacks well; it may only mean the team shot often from favourable positions in a match the opponent had already conceded. A good analyst always asks: what does this metric measure, and what does it leave out?

The third is a cognitive gap: the data is complete, but the reader does not want to believe it, because it contradicts what their eyes see or what they want to see. This is the most dangerous kind, and it is the kind I fell into at San Siro in 2026.

My 37-criteria checklist is not a list to be followed mechanically. It is a way of forcing myself to slow down. When a passage of play lasts two seconds, instinct urges an immediate conclusion. The checklist pulls me back to a basic question: have I seen enough? Does this angle hide something? Is there another angle I have not watched?

And I have also learned that the pressure of the stands does not vanish when you leave the pitch. It only changes place. On social media, every analysis is read, shared and judged within minutes. The writer is tempted to produce fast, decisive, controversial conclusions, because decisiveness generates engagement. But decisiveness is not the same as being right.

In June 2026, at the World Cup in Russia, Sky Sport Italia invited me to work as a VAR commentator for France against Argentina in the round of 16. Before the match, I used data from Kylian Mbappé's last 14 matches in Ligue 1 and the Champions League: his sprint speed reached 36.5 km/h, 2.8 km/h above the average Argentina defender. I wrote a 1,200-word analysis showing that Argentina's defensive structure would break when Mbappé accelerated around the 60th to 70th minute. Mbappé won a penalty and scored twice. France won 4-3. The piece was shared more than 5,000 times.

But that prediction was no miracle. It was the result of having enough data to speak, and enough discipline not to say more than the data allowed. If I had lacked the data on Mbappé's speed that day, the correct answer would have been an acknowledged gap, not an inflated forecast.

Here I must say something many colleagues dislike hearing. Football has an honesty crisis, and it does not come from liars. It comes from people who say too much.

Every day, thousands of analyses are written from samples that are too small, metrics that are misunderstood, and conclusions delivered with a confidence the evidence does not permit. A player who scores three goals in four matches is called “explosive.” A team that wins two games is called “resurrected.” A manager who loses three is called a “lost dressing room.” Few check whether the sample is large enough to say anything at all.

Most conclusions in contemporary football are built on thinner foundations than people assume. A decisive goal may be the product of a low-probability shot, an individual error, or simple luck. But the public needs a story, and the story is always ready to be told, whether or not the data supports it.

The same disease appears in the transfer market. Every summer, the giants run a brand arms race, paying enormous sums for names whose value the media has already confirmed. But the real value of a deal often lies at smaller clubs, where a young player is bought cheaply and matures inside a patient system. Those deals are rarely mentioned, because they do not produce headlines. They only produce football.

I see the same thing in youth development. Many former stars open academies with lavish launch events, but most of it is commercial theatre. Meanwhile, investment in systematically training grassroots coaches — the people who teach a ten-year-old how to hold the right position — is neglected. There, the data is unglamorous, and so it is not funded.

I have observed one thing over many years: analytics departments are moving deeper into dressing rooms, but their rhythm often drifts from the rhythm of the match. A model can say that player X should shoot more from position Y, but it cannot feel that the player has just played his third match in seven days, that his knee hurts, that his confidence is wobbling after a mistake the previous week.

Data is a layer of verification, not a judge. When people turn it into a judge, they begin issuing verdicts the data itself never gave.

Based on my experience watching matches, I believe the good football analyst is not the one with the most data, but the one who knows where his data ends. In a match, a good assistant referee is not the one who raises his flag most, but the one who knows when not to raise it. Our trade is the same.

I have spent most of my career learning how to look again. Since 2026, when I hosted “Đêm bóng đá” and worked as a producer, I realised that audiences do not need an expert who is always right. They need an expert willing to say “I am not sure.” Trust is not built from perfection. It is built from transparency.

Before I blow the whistle, I review myself. That is the ritual I have kept through 44 years of watching this industry, from my first days writing for Báo Bóng đá in 2026 to the evenings in the VAR room in Milan. Every verdict needs a review, including the verdict of data. And when the data is empty, the most honest verdict is to admit that we do not yet know.

I do not trust my eyes; I trust the slow-motion replay. But the slow-motion replay can also be empty. When it is, the good analyst is not the one who fills it with imagination, but the one who dares to tell the reader: here, I have nothing to conclude yet.

Football is a game of errors. The winner is not the one who never errs, but the one who knows which error is worth making — and knows when to stop rather than guess.