N/A Is Not an Answer: When Football Analysis Becomes Fabrication

A Tuesday morning in Valencia. I opened the 47-page document that had just arrived. Flawless formatting. Tight structure. Nine analytical dimensions. A risk matrix with six rows. A glossary of technical terms. A data requirements checklist. Everything met the standard, matched the structure, fulfilled the expectations of a professional research product.

And at the end, every analytical cell contained the same three characters: N/A.

In 33 years of observing this industry, I have read countless reports. From the handwritten pieces of colleagues in 1990s Madrid to the internal data dashboards La Liga clubs now circulate among themselves. But this was the first time I received a "complete" report about... nothing. The person who sent it - a young analyst - did the right thing. They refused to invent a story. But the system they were operating within demanded a report that looked "complete". And that is the real problem.

What caught my attention was not the emptiness. It was how it was presented. If an empty report is presented as an empty report, that is honesty. But if an empty report is presented with full structure, forms, and terminology - that is a trap. A skimming reader sees a finished product. Only a careful reader notices there is nothing beneath the surface.

Modern football operates in a paradox. We have never had more data. Opta records thousands of events per match. StatsBomb tracks every stride of every player. Optical tracking systems in La Liga provide the coordinates of 22 players every second, generating roughly 1.4 million data points for a 90-minute match. Yet at the same time, content-production pressure has never been greater.

Each match must now yield dozens of analytical pieces. Each transfer must come with a story. Each sacked manager must have a "tactical cause" behind it. Newsrooms measure KPIs by volume published, not by quality verified. Social platforms reward speed, not accuracy. And in that vortex, a dangerous habit forms: filling the blank with something that merely looks plausible.

I have witnessed this from the inside. In 2026, when I began building an independent data set on Levante UD, an editor asked why I did not just write "from match feel" instead of spending three weeks reviewing footage. I replied that match feel cannot measure the distance between two centre-backs on a corner kick. He did not understand. Three months later, when my prediction about Levante's movement patterns proved correct, he began to.

In the 2026-17 season, 68% of Levante UD's goals conceded came from the left flank. That number did not surface on its own. I had to review 47 matches, log every set piece, draw 214 attacking diagrams, and spend 31 hours of footage isolating the opponent's movement pattern. When I published this finding, the first response was: "How can you be sure?" Nobody asked, "Will that movement pattern repeat over the next three matches?" - the only question that truly mattered.

Data does not lie, but it does not tell stories on its own. The 68% figure is only raw material. The real story lies in Levante losing 9 points to corners exploited by a single recurring movement pattern. That is the difference between having data and understanding data.

The same thing happened on a larger scale at the 2026 World Cup. Spain's defeat to Russia in the round of 16 remains the greatest lesson in "illusory possession". Spain completed 1,029 passes across 120 minutes. 74% possession. Yet only 8 shots on target. I redrew their 47 attacking sequences and found that 82% of passes were lateral circulation in front of the penalty area. No breakthrough angle. No through-ball splitting Russia's defensive line. Just a mass of ball movement to keep the ball.

When I presented this argument live before 2 million viewers, the response came not from data but from prejudice: "Women don't understand tactics." I did not argue. I waited. Three weeks later, other analysts published the same conclusions. We once believed in possession, until the ball was no longer at our feet. From that moment, I learned that prejudice cannot be defeated by statistics - it can only be broken by patient verification.

The ball is only a variable; the way it moves is the message. In Spain's case, the message was not in 1,029 passes but in the fact that only 8 led to a shot on target. Pass volume is an index of control, not of attacking quality. Confusing the two is the most common error in modern football analysis.

When the pandemic forced La Liga to return to empty stadiums, I had a golden opportunity: a natural experiment. I reviewed 63 post-lockdown matches and compared them with 63 pre-pandemic matches. The results shocked anyone who believed in the "law of home advantage". Successful pressing dropped 12%. Counter-attack goals rose 18%. The average defensive line height of home teams fell by 4 metres.

Empty stadiums do not erase the match, they strip away the excuses. The 40,000 spectators were said to create psychological pressure on opposing players. In reality, they created pressure on referees. Without crowds, home advantage nearly vanished - not because home players performed worse, but because referees were no longer swayed by the roar from the stands.

I published a 12-page report. Three weeks later, a La Liga assistant coach cited it in an official press conference. That was the moment I understood that good data is not only for writing articles - it can change how this industry operates.

But at the same time, I understood something else. If I had chosen to fill that report with plausible-sounding speculation - for instance, "empty stadiums reduce player motivation" - I would have had a faster, more engaging, and entirely wrong piece. The appeal of fabrication lies in speed. The persuasiveness of data lies in patience.

Those three stories - Levante 2026, World Cup 2026, empty stadiums 2026 - share one thing. In all three cases, the data ran counter to the easiest story to tell. Levante did not concede because of "poor spirit" but because of a specific, measurable movement pattern. Spain did not lose because of "bad luck" but because an attacking structure generated no breakthrough angle. Home advantage did not vanish because "players lost motivation" but because referees lost the crowd's pressure.

The second shared feature: in all three cases, an easier explanation already existed. And that explanation was always accepted faster. That is why fabrication in football analysis does not come from laziness - it comes from incentive. The system rewards answers that are fast, clean, and confident. And when the reward is large enough, people learn to produce answers before sufficient data exists to verify them.

And here is the most worrying part: fabrication does not only exist in internal analytical reports. It exists across the entire football information ecosystem. When a club prepares to sell a player, a selectively chosen xG figure can push the price up by 20%. When a manager needs time, a crafted pressing table can buy three more matches. When a young player needs attention, a comparison with a star can generate millions of views - and create expectations he cannot meet.

Recall the rule I set myself after Levante 2026: every conclusion must stand on a number. But over time, I realised that rule was not enough. A conclusion can stand on a number and still be wrong - if that number was selected to serve the conclusion. What I truly need is: "every number must answer the question - if I am wrong, what would prove it?"

That is the hardest standard. And it is the standard that separates analysis from fabrication.

A system that functions when the opponent is in chaos is what truly needs coaching. That holds for a team, and it holds for an analyst. When everything is clear - when data is complete, when conclusions are obvious, when the story tells itself - anyone can write. But when data is empty, when the answer does not yet exist, when pressure demands a finished product - that is when the method is truly tested.

Here is the counter-intuitive point: in football analysis, "N/A" is sometimes the most honest answer. But it is also the most expensive answer.

An empty report generates no engagement. A line reading "insufficient data to conclude" produces no headline. An analyst who refuses to speculate will be judged as lacking passion. The system most sports platforms operate within does not reward caution - it rewards confidence. And confidence can be fabricated.

The most dangerous thing is that fabrication never looks like fabrication. It looks like a 47-page report with clean layout, clear tables, precise terminology. It looks like what executives want to read. But underneath, it is an empty structure - and any decision built on it stands on nothing.

Good data does not answer questions, it teaches us to ask better ones. An honest report with three lines reading "insufficient data" is worth more than a fabricated report with 47 pages of conclusions. Because at least it tells you what you are missing.

Tactics are not a diagram; they are how a team responds to chaos. Analytical work is the same - not a filled-in table, but a continuous process of asking and verifying. When that process is cut short by production pressure, we are no longer analysing football. We are writing fiction dressed in sporting terminology.

The problem is not technology. We have enough data. The problem is culture: an industry that has learned to reward completeness over honesty.

The young analyst who sent me that N/A report did not fail. They were the only person in the chain who did it right. Because in football, as in any other field, the first question is not "What can we say?" but "What do we actually know?"

The next match begins in a few days. And the question I will ask myself before writing any line: am I analysing, or filling in a blank?