The Empty VAR Room: When Football Learns to Say 'Insufficient Data'

In November 2026, at San Siro, the screen in my VAR room turned grey in the 56th minute. The feed from the camera behind the goal cut out for an instant, at the exact moment Gonzalo Higuaín put the ball into Milan's net. In my earpiece, the referee was waiting for my confirmation. In my head, a question bigger than the incident itself: when there is no image, what do you blow the whistle on?

I hesitated, and I did not recommend a review. Milan lost 0-2. After the match, the referee supervisor criticised me in front of the whole team for missing an offside. But what kept me awake for many nights was not the goal. It was the moment I realised I had almost drawn a conclusion from a void. Had I dared to say "offside" with no footage to cross-check, I would have betrayed the very profession that raised me.

Before I blow the whistle, I review myself. That sentence now hangs framed on the wall of my office in Milan.

Modern football lives inside a paradox few people name. There has never been so much data. Every Serie A match generates millions of positional data points; every phase is broken down into xG, xA, PPDA and pass-completion rates. VAR lets us watch one incident from ten angles. Yet at the same time, there has never been so much conclusion-drawing from empty space. People argue about a team on the basis of three matches. People judge a player on the basis of one moment. People write a three-thousand-word analysis from a blank spreadsheet.

I once sat in the VAR room. I know the feeling of waiting for something that never arrives. In the world of analysis, the greatest temptation is not to invent a wrong number. The greatest temptation is to fill the void with emotion, with touchline intuition, with what people fondly call a "professional eye." A wrong number can be caught. A good story cannot.

I learned this the hardest way. After that night at San Siro, I locked myself in a room and re-watched 47 similar phases over a month. From there, I built a 37-point checklist to standardise every decision. Not to make football mechanical, but so that when the signal dies, I still have a system instead of a hunch. Every ruling needs a second look, including the ruling of data.

In June 2026, at the World Cup in Russia, I sat in the Sky Sport Italia studio before France met Argentina in the round of 16. 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 Argentine defender. I wrote a 1,200-word analysis arguing that Argentina's defensive structure would break when Mbappé accelerated between the 60th and 70th minutes. The result: Mbappé won a penalty and scored twice, and France won 4-3.

I tell that story not to boast. I tell it to show the opposite. Precisely because I predicted correctly from data, I understand clearly that data is not a judge. It is a layer of verification. And when that layer is empty, the only honest thing is to say: "I do not have enough information."

Many people ask me why, in more than a few articles, I devote a whole paragraph to what I do not know. The answer lies in a test I call the "blank sheet." Before every judgment, I ask myself: if I erase all the numbers, what remains? If the answer is a feeling, I do not write. If the answer is a trend confirmed across many matches, I write.

In October 2026, when Serie A returned to empty stadiums because of COVID-19, Milan went through a run of seven matches without a win. The board blamed the attack after selling André Silva to Monaco for 35 million euros. I did not believe it. I analysed transition data over the last 14 matches and found that Milan's defence lost 42% of its counter-attacking protection when the noise of the crowd was no longer driving the press. The problem was not the striker. It was a system running in silence.

I wrote a 30-page report to the editors of La Gazzetta dello Sport, proposing a three-phase recovery plan. It was published in full. From then on, I shifted entirely to systemic diagnosis: before criticising an individual, I dig into the operating mechanism of the whole collective.

There is a popular view I consider methodologically mistaken. People say technology and data are killing football, that VAR turns moments of transcendence into meetings. Technology does not kill football; it kills blind faith. The problem is not the screen. The problem is the person in front of the screen, willing to fill a broken feed with a pre-built story.

This is the biggest blind spot of an entire analysis industry. When a data system collapses at the very first stage, when the spreadsheet is empty, the default reaction of the crowd is not silence. The default reaction is invention. People write, people comment, people build an entire model out of nothing, because in football a void is taken as a sign of ignorance, while confidence is always rewarded.

More dangerous than a wrong model is a right model applied to a dataset that does not exist. I have seen transfer reports written from a single source, player evaluations built on three minutes of highlights. Those are VAR checks with no footage.

The point I want to leave behind is not whether VAR is right or wrong. The question is: in a football that grows hungrier for data and hungrier for conclusions, who will be the one to dare say "I do not have enough information"? I believe the next generation of analysts will be judged not by the number of conclusions they deliver, but by the number of times they dare to stop. For football is a game of errors, but the winner is the one who knows which error is worth making. And the most worthwhile error of all is sometimes admitting that you have seen nothing at all.