Seven Pages and a Single N/A: When Football Analysis Has Not One Data Point

At three in the morning in Valencia, I opened a seven-page report. The first page had a title. The remaining six repeated one sentence in every box: insufficient information. No team name, no player name, no date, not a single figure on passes, shots or successful presses. The report delivered the only verdict it was able to deliver, namely that it had nothing to say.

What kept me sitting there for two more hours was not the emptiness. The honesty was the striking part. A product willing to write “insufficient information” across all nine categories, from tactics and finances to the dressing room and regulatory risk, is a rarity in my trade. Most football analysis readers consume each week is not honest in that way. It is thicker, longer, more confident, and just as hollow, only coated with a layer of adjectives.

I have covered professional football since 2026, when I graduated and took a posting as a staff reporter in Madrid. Thirty years later I still sit in front of a screen at hours like this one, rewinding footage, counting the running rhythms of two full-backs and taking notes in a notebook with a bent spine. Eight World Cups, eight Olympic Games, several editions of the Giro d’Italia and the Tour de France have passed through that period. What I carried out of all those trips is a habit that makes me an awkward conversation partner: before I hear a judgement, I want to know what it stands on.

That seven-page report stood on nothing, and it said so outright. That is why I consider it a more worthwhile document than many analyses drifting around out there, written in a language so smooth that nobody bothers to ask whether the author watched the match at all.

In a sports newsroom, analytical work runs through two stages. The first is deconstruction: establishing the title, the source, the information points and the core viewpoints. The second is interpretation: placing facts inside a tactical system, comparing them with the opponent, inferring risk and trend. It sounds obvious. Yet most analyses I have read over the past decade skipped straight to the second stage, because the first consumes time and nobody sees the credit in it.

When the first stage is empty, the writer faces three options. Stay silent and lose the slot. Invent facts and lose credibility if checked. Or write sentences that cannot be wrong.

The industry picks the third option almost by default. A sentence that cannot be wrong has a very recognisable shape: the team needs to improve its conversion of chances. No result refutes it. Three straight wins, and it still holds. Six defeats, and it still holds.

Deconstruction is not administrative paperwork. It is where the dataset is built. In my experience, a dataset only has value when every entry passes three tests.

The first test is traceability: the entry is tied to whom, when, where. The second is verifiability: there is a source to cross-check, footage to rewind, a match record to compare. The third is reusability: the entry can be placed beside another to generate a comparison.

A sentence such as “Levante defends the left flank poorly” fails all three. It has no specific subject, no time frame, nothing to cross-check, and it cannot be set beside anything. A sentence such as “68% of Levante’s goals conceded in the 2026-17 season came down the left channel” passes all three. I know the subject, the season, how to recount, and that it can be compared with the equivalent figure from the previous season.

The entire value of analytical work lies in whether a judgement can be proven wrong. The second sentence can be wrong. If I miscounted, if the movement pattern does not repeat, if the real share is 41% rather than 68%, I lose credibility and have to correct it. The first sentence cannot be wrong, and therefore has no value beyond filling a blank space on a page.

In 2026 I left my assistant-coach seat to work as an independent analyst. The first thing I did was not writing. I watched 47 Levante UD matches, rewound 31 hours of footage, drew 214 attacking diagrams and logged every set piece on the same template. The dataset exposed a blind spot nobody had raised in coaching meetings: 68% of goals conceded came down the left channel, and nine points were dropped to corners exploited through one repeated movement pattern.

I did not find that because I am smarter than other people. I found it because I was willing to sit long enough to count. When my debut piece correctly predicted three of the next four matches, the editor called back to ask which software I used. I used a notebook and an old tablet.

The rule I took from that season still follows me: every conclusion must stand on a figure, and the figure must be recorded before the conclusion forms in the mind. Do it the other way round and the writer automatically hunts for data to defend what he already believed.

In the summer of 2026 a television channel invited me to work as a tactical commentator at the World Cup in Russia. Spain against Russia in the round of sixteen is the case I remember best, and the one that drew the most criticism.

Spain completed 1,029 passes and held 74% possession. Looking at the post-match statistics, almost every bulletin described them as the team controlling the game. When I mapped their 47 attacking sequences, the picture was different: 82% of passes were lateral circulation in front of the box, and shots on target numbered eight. A high possession share created no breakthrough angle.

I presented that argument live to roughly two million viewers. The response arrived quickly and was not gentle. Someone said plainly that women do not understand tactics. Three weeks later, a La Liga assistant coach cited my report in an official press conference.

Data does not lie, but it does not tell stories on its own either. From the same set of figures about that match, two opposing articles can be written and both will look plausible. The analyst’s job is to choose the telling that is faithful to the structure of the game, then accept being challenged.

I keep a habit of reviewing old matches in fifteen-minute blocks. For each block I record three things: the average position of the defensive line, successful presses in the opponent’s half, and line-breaking passes. After a few hundred matches those three indicators form a baseline for comparison. The baseline matters more than any judgement, because it tells me where a match deviates from normal.

In 2026, when the pandemic forced football back into empty stadiums, that baseline paid off. I reviewed 63 post-lockdown La Liga matches against 63 pre-pandemic ones. Successful pressing fell 12%. Goals from fast counter-attacks rose 18%. The average high line of home teams dropped four metres.

Four metres sounds small until you recall that it approximates the distance between a high defensive line and a deep one, meaning the whole initiative in controlling the space behind the opponent. Home advantage, long treated as a law of football, all but vanished without forty thousand spectators pressuring the referee. An empty stadium does not erase the match; it strips away the excuses.

What matters is that I only saw that shift because I had a comparison sample. Someone watching 63 post-lockdown matches with no reference point would conclude football was unchanged. Analysis without a baseline is only description, and description does not generate discovery.

In Vietnam, where I was born and still follow football weekly, the problem has its own shape. Domestic competitions lack publicly available data at the level of detail required: line-breaking passes, line height, successful presses are largely unpublished. Analysts there must either build their own datasets or write by eye. I know that feeling. Thirty years ago I had only my eyes and a notebook, and it took me two seasons to understand that the eye remembers repeated patterns very badly.

Back to those seven pages that night. The report awarded one star in all four value categories, from sporting value to reference value, and stated clearly that no conclusion at the analytical stage could be reached. To a hurried reader that signals uselessness. To me it signals discipline.

It separates two things sports media habitually conflates: judging the subject and judging the input. An analysis with no facts about a given club cannot say anything about that club. Assigning it a low competence score is a logical error, not a conclusion. I have seen far too many analyses scoring high on confidence and low on foundation. That kind of content is more dangerous than an empty report, because it leaves no blank space for the reader to doubt. Good data does not answer questions; it teaches us to ask better ones.

Vague content is cheaper than accurate content. It needs no reporter on site, no purchased data, no rewound footage. One writer can produce ten pieces a day across ten leagues by swapping team names and keeping the sentence structure. Distribution platforms reward volume, speed and emotion, not verifiability. That flow runs from newsrooms into discussion groups, from discussion groups into unattributed aggregation, then back into newsrooms as “opinion is said to hold”. After a few loops, an unverified sentence becomes the foundation for another commentary decision. I call it the transmission chain of vagueness, and it is why I always ask for the source before quoting anything.

Most debate in the industry centres on analysis that is wrong. The greater danger lies in analysis that cannot be proven wrong. A wrong judgement gets corrected when the result arrives. A vague judgement lives forever, and the more it is repeated the more it resembles truth.

Tactics are not a diagram; they are how a team responds to chaos. A diagram can be drawn on a whiteboard, whereas a response only shows itself in the last ten minutes of the second half, when a team is a goal down and the full-back can no longer run. Analysing a response requires data on running rhythms and positions. Avoiding unverifiable claims requires accepting that some matches do not give you enough to conclude.

The pressure to fill blank space peaks exactly when the risk is highest: derby day, a six-pointer at the end of the season, transfer deadline day. That is also when a sentence that cannot be wrong does the most damage, because it shapes the expectations of the crowd before a ball is kicked.

Conversely, a report made entirely of N/A can become a shield. If everything is “insufficient information”, the analyst never carries responsibility for any judgement. I separate the two cases with a simple test: did the author put in the work to find the facts, or simply wait for facts to arrive? Honesty only has value when it results from effort, not from laziness presented politely.

The ball is only a variable; how it travels is the message. Next time, before reading a pre-match analysis, try to extract three figures that would collapse its conclusion if they pointed the other way. If you cannot extract a single one, the author did not watch that match closely enough. As for me, those seven blank pages from that night will stay in the drawer, beside the notebook with the bent spine, as a reminder that silence at the right moment is also part of the job.