When Data Goes Silent: Modern Football and the Trap of Empty Reports

3 a.m. in Liverpool, and I open a twelve-page document a colleague has sent over. The cover page says it plainly: "Stage-2 Deep Professional Analysis — Football Domain." I turn the pages. Nine major sections. Tactics and technique. Club finance and the transfer market. Results and the opinion cycle. League landscape. Rules and governance. Management and the dressing room. Risk profile. Media and expectation. Industry transmission. Every one of them empty. Not a single player's name. Not a single club. Not a single number. Each slot carries the same line: "N/A — insufficient information to assess."

I sit still in front of the screen for a long time. Not out of anger, but because I realise something: in modern football, empty reports are appearing more and more often. The only difference is that most of them are disguised behind numbers that look thoroughly convincing. That is the frightening part.

People call me reckless, but numbers have never learned to lie. The problem is that people have.

A game that lives on data

Over the past two decades, European football has changed its operating foundations. If in the 1990s a manager could pick a player on instinct and a few videotapes, then by the 2026-26 season almost every major decision in the Premier League has to pass through a data pipeline.

Liverpool are the clearest example. Under sporting director Michael Edwards and research director Ian Graham, the club built an entire data-science department. That department stood behind the signings of Mohamed Salah, Sadio Mané and Roberto Firmino. Brentford, owned by Matthew Benham — a former betting analyst — climbed from the Championship to the Premier League in 2026 on a recruitment model built on metrics. Tony Bloom's Brighton have followed the same road, turning high-value player sales into a steady revenue stream.

I saw something in them before the world turned its head. In 2026, at the age of 56, I published a prediction on my personal blog that was mocked: the trio of Salah, Firmino and Mané would score at least 84 goals in all competitions for Liverpool. By the end of the 2026-18 season they had scored 91 — Salah 44, Firmino 27, Mané 20. The number 91 is not a lucky number; it is the destination of a plan.

That achievement is real. But it creates a consequence few are willing to discuss: when the whole industry puts its faith in data, empty data or wrong data becomes a bigger threat than having no data at all.

Data has also crept into how matches are run. VAR and semi-automated offside technology are now part of the Premier League. I have always held that the review times are too long and are tearing the rhythm of the game into shreds — two minutes of waiting is enough to cool a goal. But that is a story for another piece.

Three break points in the data pipeline

Based on my experience watching matches across nearly half a century, I see a clear rule: data only has value when it is collected, checked and passed on correctly. There are three common break points.

The first is input failure. A Stage-2 analysis can be flawless in its skeleton, but if the Stage-1 decoding is empty — no team names, no players, no events — then all nine sections behind it are nothing but a body without a soul. In football, this is the equivalent of a scout filing a report that says "player scores 8/10 for passing" without ever having watched him play a single minute.

The second is interpretation failure. Expected goals, or xG, is a wonderful tool, but it does not tell you why a high-xG shot was missed. If a club looks only at xG and ignores context — a congested fixture list, injuries, a player's state of mind — it will buy the wrong man. I have watched more than a few failed transfers happen for exactly this reason.

The third is pressure failure. When a board needs an answer immediately, the analyst is easily pushed into filling the gap with guesswork. And guesswork, once presented in a handsome table, becomes truth in the meeting room. That is the moment data stops serving the facts and starts serving power.

Take one concrete example. In the summer transfer window, clubs routinely run models to price players on minutes played, progression metrics and age. If the input data comes only from a small league with a thin sample, the model still produces a number that looks entirely professional. Nobody asks how many matches that number was built from. That is how an empty report in the costume of a spreadsheet slips into the transfer meeting.

What is worth noting is that these break points do not exclude one another. They compound. A small input failure, passing through an interpretation failure, then amplified by time pressure, produces a completely wrong decision. And in football, a wrong decision usually means real money burned, a manager's seat lost, or a season wasted.

Data does not kill emotion. It gives emotion a frame. But an empty frame holds nothing up.

An empty report once saved me

I was wrong about the 2026 World Cup. And that was the most expensive lesson I have.

In the round of 16, for Croatia against Denmark, I mispronounced the name of midfielder Ivan Rakitić three times in a row on live broadcast. For the whole month that followed, I sat rewatching the footage and logging the passing numbers of the Croatian midfield. Luka Modrić, Ivan Rakitić and Marcelo Brozović posted an 89% pass-completion rate in the knockout rounds. I wrote a piece arguing against myself, analysing why Croatia reached the final.

The lesson was not that I was wrong. The lesson was that I had to go back to raw data instead of clinging to the conclusion already sitting in my head. An empty report, read the right way, is a warning bell: do not conclude when you have nothing to conclude from.

But there is every chance I am wrong

I have to be honest with the reader. There is another way to read that empty document, and it is not naive.

Perhaps what I call a data disaster is actually a sign of maturity. An analytical machine that dares to print the words "insufficient information" instead of inventing a conclusion — that is an act of honesty rare in an industry that rewards overconfidence. Seen that way, the empty report is the sign of an immune system doing its job.

It is also possible that I am overrating the role of data. Football remains a sport of moments that cannot be measured: a chest control, a glance between two teammates, a referee's decision in a split second. At 65, I have lived through too many eras to believe that emotion can be fully replaced by a spreadsheet.

I may be wrong in another way too: I write this piece as a data sceptic, while I built my own career on data. A 65-year-old man in Liverpool, half a life with a pen in hand, sometimes has to ask himself whether he is defending data or defending his own point of view.

And perhaps the most dangerous thing is not the empty data. It is a game full of data but short of people willing to say: "I don't know yet."

What I will be watching

I do not apologise for writing this piece from an empty document. I write it because I believe something that can be verified: within the next three years, at least one Premier League club will sack a manager or sign a major contract by mistake because it acted on an analysis report with no underlying data. When that happens, do not blame the algorithm. Look at whoever signed off on it.

Football waits for no one. It only waits for those who dare to ask questions.