Empty Data: When Football Makes Decisions Without Evidence

The screen in the Darul Aman press room flickered on, then went dark. Not a single number appeared — no possession, no pass count, no heat map. Only rain hammering the tin roof and the 4-3 scoreline in Kedah's favour, still frozen on the electronic board. Forty-seven journalists held accreditation that night; three of them were women. A veteran reporter beside me closed his notebook and smiled: "No numbers — so what do you write?" I wrote about the coach's twisted face as the rain turned the penalty area into a bog. That piece contained not one line of statistics. Years later I still think about his question, because it was the right question asked in the wrong place. The problem with modern football is not a shortage of data. The problem is that we do not know what to do when the data is empty. Context: an industry that lives on information Picture the scale of that flow. A single match in a European top division generates thousands of data points per minute: the coordinates of every player, running speed, shot angle, goal probability. Data companies resell those numbers to clubs, bookmakers, broadcasters and supporters who simply want to know who ran the most. Behind the scenes sits another layer: scouting reports, medical files, contract negotiation minutes, psychological assessments. A Premier League club can spend millions of pounds a year purely to collect and process data. But that system has a blind spot. When the feed drops, when the tracking camera fails, when the scouting report comes back with every field blank — what happens? The honest answer is that almost nobody is willing to say "I don't know". Instead, the gap is filled with guesswork, and guesswork is presented as fact. Analysis: three gaps, three ways of filling them The first gap sits on the pitch. On 27 June 2026, at Kazan Arena, Germany lost 0-2 to South Korea and left a World Cup at the group stage for the first time in eighty years. This was a team with abundant data — the largest analysis department at the tournament, the best facilities. And still they collapsed. "At two in the morning in Moscow, I heard an entire football empire break apart into a sigh." The striking thing is that the data was not empty. What was empty was the capacity to read meaning out of it. The second gap sits in the transfer market. Every summer, thousands of rumours are published, and most of them cannot be traced to a verifiable source. A midfielder can be valued, negotiated over and pushed onto front pages on the strength of a post nobody can trace. Transfer value is built on expectation, and expectation is usually built on a gap. I once followed a deal that dragged on for four months. In the end the player stayed. Nobody apologised, nobody issued a correction. The next day's reporting simply moved on to a different name. The third gap sits in the VAR room. Video technology was introduced to reduce error, but it also created a new form of ambiguity: an obstructed frame, a missing camera angle, a hand-drawn line on a screen. The referee must reach a conclusion about an incident on incomplete evidence. And in those moments, the pressure to give a decisive answer is usually stronger than the need to be right. The contrarian view: empty does not mean worthless This is where I want to pause. In my trade, the default assumption is that an empty dataset is a worthless dataset — that it has nothing to say. I think that assumption is wrong, and dangerously so. An empty dataset is usually the sign of an upstream failure. It does not say "this question does not matter". It says "the system dropped something on the way". Confusing the two is the most expensive mistake football makes. A second, subtler danger follows: once we grow used to seeing empty datasets, we gradually equate them with "no value". In an automated archiving system, those blank records get filed under "low score" — and history will remember them as unremarkable matches, when in truth they were never read at all. A third danger sits on the opposite side: when the data is complete, we believe we understand. Germany in 2026 is the proof. Data did not save them, because what they lacked was not numbers but honesty towards numbers. Finally, "the groundskeeper of the 87,000-seat stadium has never once watched a match from the VIP seats." In 2026, mid-pandemic, I went to Bukit Jalil with the stands utterly empty. A 52-year-old groundsman was still trimming the grass centimetre by centimetre inside the penalty area. He told me: "The grass doesn't know whether anyone is watching. The grass only knows it has to be green." Inside a system where every input read zero, that man still did the work correctly. That is a lesson in integrity no spreadsheet can ever teach. The way forward Football will keep producing more data, more cameras, more forecasting models. But when a field is left blank, the professional response is not to invent a substitute number. The response is to state clearly that it is blank, state clearly why it is blank, and trace back to where the data fell. "There is a kind of football that happens after the stadium lights go out." It happens in records nobody re-checks, in scouting reports nobody ever opens, in the gaps we rush to fill with guesswork. If the next generation of Vietnamese football analysis learns one thing, I hope it is this: the silence of data is itself data, and the honest writer is the one who knows how to leave it intact.