The Empty Spreadsheet and the Scariest Thing in a Football Analysis Room

2:07 AM in Guangzhou

I opened the file, and for the first three seconds it was beautiful. Headings correctly bolded, nine numbered sections neatly ordered, each with its own table, each table with an "Assessment" column, a "Risk" column, a "Comparison" column. Not a single cell broken. Not a single question mark hovering in the margin. A ten-page document that looked as though it had just been sent over by the analytics department of a top-division club.

Then I read the content.

Every cell said the same thing: insufficient information, cannot be assessed. The tactics section had no team. The finance section had no club. The league section had no league. The personnel section had no names. The risk section had all six rows — sporting risk, financial risk, personnel risk, regulatory risk, reputational risk, systemic risk — and all six rows were empty.

I sat still for a while in an apartment overlooking a street that had already gone dark. What I was holding was not a wrong analysis. It was an analysis that did not exist, packaged so carefully that it could have passed every editorial checkpoint at a newsroom racing a deadline.

And that is the scariest thing in this trade.

Not a fabricated number. Not a false transfer story. But a structure that looks valid, clean, professional, and is hollow inside — and nobody catches it, because nobody is paid to catch it.

The market wants answers, not emptiness

We are in the annual season. There is no final for the whole world to sit down and watch, no major event forcing anyone to stop and verify. Just a steady current: one matchday after another, a table shifting by a few points, a handful of refereeing arguments, a handful of injuries, and an enormous volume of content that must be produced every day.

That very steadiness creates the pressure. In a final, a writer has three days to prepare and the whole world is waiting. In the annual season, a writer has forty matches a week and nobody is waiting at all.

When nobody is waiting, speed replaces accuracy. And when speed replaces accuracy, the first thing sacrificed is the anchor.

What is an anchor? A team. A player. A date. A source. A fact so specific it cannot be argued with. Every conclusion in football — tactical, financial, dressing-room, relegation-risk — only stands if there is at least one such anchor underneath it.

I read data, and data whispers a name nobody has picked. But if the data has no name to whisper, what I am reading is not data. It is a table with enough chairs and no guests.

That night's report was exactly that empty table. And what kept me awake was not its content. It was its format.

Anatomy of an empty report: nine drawers with nothing inside

Picture the modern professional football analysis framework as a cabinet with nine drawers. Drawer one: tactics and technique. Drawer two: club finance and the transfer market. Drawer three: results and the opinion cycle. Drawer four: league landscape and team positioning. Drawer five: rules and compliance. Drawer six: management and dressing room. Drawer seven: risk profile. Drawer eight: media narrative and expectations. Drawer nine: industry-wide transmission.

A serious analysis opens all nine drawers and places something verifiable in each. A bad analysis opens all nine drawers and places a confident-sounding claim in each.

The report in my hand was the third kind, the most dangerous kind: it opened all nine drawers, built the framework for each, and left them empty. And it described its own behaviour with a term I think every sports editor in Vietnam should memorise: fail-open.

Fail-open means the system hits an error but still emits a result that looks valid, instead of stopping and raising an alarm. A fail-open data pipeline hands you a complete table with blank cells. A fail-closed pipeline throws an error and blocks the whole workflow until someone fixes it.

In software, fail-open is a design choice. In sports journalism, it is a catastrophe, because nobody throws an error. They just publish.

The anchor: team, player, date

In football, the most obvious thing is usually the least verified.

Everyone knows tactical analysis needs data. Everyone knows financial analysis needs a balance sheet. But very few people apply the simplest test: if you strip all the adjectives out of an article, how many facts remain?

I have a bad habit when reading younger colleagues' drafts. I underline every proper noun, every number, every date. If the page is still covered in ink when I finish, the piece has a skeleton. If the page is clean, the piece has a voice.

A voice is not a crime. A voice is a craft. But a voice standing alone is just a sound in a closed room.

Take the tactics drawer. To talk about a team you need to know its shape, who is covering for whom, how many fractions of a second its back line is late when the ball is played behind it. To talk about a player you need to know how many sprints he made, in which zones, in which minutes. To compare two teams you need at least one measurable defensive or pressing metric.

Without those, you do not have a tactics drawer. You have a drawer painted to look like wood.

And when a report names no team, no coach, no player, no date, the question is no longer "is this conclusion right or wrong". The question becomes: what is this conclusion about?

People look at the table; I look at the gaps between the numbers. But before I look at the gaps, I have to be sure there is a table to look at.

43% and the season without crowds

In 2026, when every league stopped, I was a first-year student with too much time and a spreadsheet. I sat down and collected data from 110 Bundesliga matches played in empty stadiums, then laid it against the previous season.

The result made me stop in the middle of the afternoon: home advantage fell by roughly 43%. Home teams still won more often than away teams, but the gap narrowed sharply. Something invisible in the stands had evaporated, and it had been contributing a substantial share of on-pitch outcomes.

43% is not a probability. It is a verdict on the complacent.

Who does that verdict convict? The people who still call the crowd "the twelfth man" as a cliché used to fill space. Because when the crowd disappears, the number surfaces, and it forces us to admit something much of the analysis industry quietly ignores: many of the things we call "character" or "spirit" are simply metrics that have not been named yet.

I put the finding on my own podcast and argued that possession-dominant teams were affected less, because they do not need a crowd to sustain their structure. A few people pushed back. A few others did not know what they were pushing back against.

What I learned was not "empty stadiums change football". What I learned was that good data can exist without anyone believing it, and bad data can live a long time if it is attractive enough.

27 sprints and 0.4 seconds

In 2026 I was seventeen and wrote a 900-word piece on a local football forum. I predicted France would beat Argentina 4-3 in the World Cup round of sixteen. I remember the first reaction: a few jokes, some silence, and nobody asking where my numbers came from.

I got the numbers by sitting and watching Argentina's matches again, and counting. I counted 27 sprints from Kylian Mbappé across the relevant period, and I measured Argentina's back line reacting roughly 0.4 seconds late whenever it had to drop deep. On paper, 0.4 seconds sounds meaninglessly small. At match speed, 0.4 seconds is the distance between touching the ball and touching air.

The scoreline matched exactly. The piece reached around 120,000 views. I am not recounting this to boast. I am recounting it because it taught me a mechanism every football writer should understand clearly: people remember the result, but they believe the method.

If I had only said "France will win 4-3", I would have been a provocateur. Because I said "France will win 4-3 because Argentina's back line is 0.4 seconds late", I was a provocateur with evidence. The difference between those two versions is not the opinion. It is that one version has an anchor and the other does not.

58% and a night at Wembley

On 11 July 2026 I streamed the Euro final between Italy and England at Wembley. On air I said Italy would win at Wembley, and my basis was a dataset from Italy's previous 27 matches: in roughly 58% of situations they dropped deep after taking the lead.

I added a line that many in the comments disliked: "They will drop deep, but they are not defending in the passive sense. They drop to pull England out of position."

Dropping deep is not cowardice. It is how intelligent people wait for fools to charge.

The match unfolded along exactly that grain. Italy equalised, then withdrew, then absorbed pressure by letting their opponents push themselves into harmless areas. The match ended in a penalty shootout — a method of resolution I did not predict, and I will not pretend otherwise. But my call about Italy controlling the tempo after scoring drew more than 15,000 viewers and generated a long argument.

Two lessons. First: timing a contrarian view matters as much as its content — speak when the world is leaning one way. Second, and more important: I was right about the process and wrong about the outcome, and I can prove it using the very data I used.

Every prediction can be wrong. Being wrong with honest data is worth more than being right by luck.

PPDA, distance covered, and the trap of effort metrics

Here I have to say something I know will annoy a few people.

There are three kinds of football metrics. The first describes chance quality, such as expected goals. The second describes collective behaviour, such as passes allowed per defensive action — the lower the number, the more aggressively a team presses. The third describes volume of running.

The third is the most abused.

Distance covered and sprint counts are packaged as effort metrics. The team that runs more is praised as hungrier. The player who covers the most ground is voted man of the match. But ineffective running still produces pretty numbers. A full-back who runs eight kilometres while his team never has the ball is telling you about chaos, not endurance. A central midfielder who runs eleven kilometres while the back line is being stretched may be telling you he spent ninety minutes in the wrong place.

I have seen data reports post a player's heat map with the caption "covered the entire pitch". That heat map usually says something else: the player had no position.

Tactics are not a formula. They are the answer to the reverse question: what does the opponent fear most?

Once you ask that reverse question, volume metrics lose their authority. You stop asking "who ran the most". You ask "who ran at the right moment, in which zone, and what did that force the opponent to do".

Source quality is a field, not a ritual

In that empty report, one line held me longest. It sat in drawer eight, the drawer about media narrative. It said that grading sources could not be performed, because the "article source" field was blank.

Reading that, I recognised a structural problem across the entire sports content industry.

People treat sourcing as the last part of an article — a footnote, a formality, a social ritual. In professional analysis, sourcing is a data field, with tiers, with a score, with usability.

A tier-one source is a journalist with a direct relationship to the club, who has been accurate repeatedly and carries personal responsibility for errors. A tier-two source is mainstream media with a verification process but no direct relationship. A tier-three source is a line with no subject, no date, no one accountable — what the trade calls "reportedly".

When an analysis cannot grade its source, it is not being cautious. It is losing its ability to defend itself.

And in the annual season, when there is no major event to allocate attention, sourcing becomes the most expensive commodity. Which is also why it is the most counterfeited.

115 charges, 10 points, 4 points and 15 points

To understand why sourcing matters, look at the rules drawer.

In February 2026, the Premier League announced it had charged Manchester City with financial rule breaches, with the number of charges reaching 115 across multiple seasons. The process has been long and complex, and every step depends on specific accounting documents rather than public sentiment.

In November 2026, Everton were deducted 10 points for breaching profit and sustainability rules. In February 2026, that figure was reduced to 6 on appeal. In April 2026, Everton received a further 2-point deduction in a separate case. In March 2026, Nottingham Forest were deducted 4 points.

In Italy, in January 2026, Juventus were deducted 15 points in a case involving transfer transactions. By May 2026, the deduction was adjusted to 10 points.

Notice the structure of these facts. Each sentence contains a club, a specific deduction, a specific month, a decision-making body. These are anchored facts. Their reasonableness can be argued. Their existence cannot.

By contrast, a sentence like "several European clubs are facing the risk of points deductions" has no anchor. It sounds like information. It operates as a mirror — readers project onto it the club they already dislike.

In football, the most obvious thing is usually the least verified. And unanchored sentences live longest, because there is nothing to refute.

The dressing room has no balance sheet

Drawer six — management and dressing room — is the hardest of all nine. I say that after nine years observing the industry, including several years writing about things I had no right to know.

The problem with this drawer is that it has no direct metrics. You can measure passes, expected goals, distance covered. You cannot measure a captain's loyalty. You cannot measure an owner's patience.

So when analysing this drawer, a writer must accept working with indirect signals: the power structure inside the club, who decides on signings, who is accountable when a transfer fails, which players are in the final year of their contracts, which players have an injury record so dense that people nickname them for their fragility.

Without those signals, you do not have dressing-room analysis. You have a story retold from what others have retold.

And here is the blunt version: most of the "dressing-room crisis" content readers consume weekly is not built from signals. It is built by reverse-inferring from results. Lose three in a row and there is a crisis. Win three in a row and there is "fighting spirit". Both are the same method with the sign flipped.

The transmission chain: academies, clubs, broadcasters, and the betting markets too

Drawer nine is the most seductive and intellectually riskiest. It asks a writer to trace an impact across an entire industry: from the talent supply chain at academy level, through the club and competition system, down to broadcasting, commercial and derivative markets.

A transfer is not just a player changing shirts. It is a signal about a group of clubs' spending power, about market inflation, about agent strategy, and about audience expectations for years to come.

Take a verifiable example. On 31 January 2026, Chelsea completed the signing of Enzo Fernández for a fee reported at around £106.8 million — the highest fee ever paid for a player in English football history at that time. Half a month earlier, on 15 January 2026, Chelsea had also completed the signing of Mykhailo Mudryk for a base fee of around €70 million plus add-ons that could push the total close to €100 million.

Those two deals, placed side by side, create a very clear transmission chain. They lift the price floor. They force peer clubs to react. They create one new layer of content — analysis of why the price of young players has outrun every traditional valuation model. And they create another layer — criticism of the very inflation they caused.

Both layers have anchors. That is why they last longer than a week.

By contrast, a piece claiming "the transfer market is a bubble and a disaster is coming" with no numbers at all lasts a day. It operates as emotion, not as data.

Where I could be wrong

Now I have to put myself in a less comfortable chair.

If I treat data caution as the highest standard, I risk turning it into a shield. Once a writer learns the phrase "insufficient information, cannot be assessed", he can use it never to make a prediction at all. And a commentator who never predicts never has to answer for a prediction.

That is polite cowardice. It wears professional clothing and nobody notices.

There is another possibility I must admit. Perhaps I am overreacting. Perhaps empty reports are a minor operational problem, a sloppy incident in an overloaded production line — not an industry disease. Perhaps I saw one signal and gave it the weight of a trend.

That is the occupational risk of the exception hunter: pulling a single case out to generalise.

But I stand by one point. If a structure looks valid and is empty inside, that structure will be treated as real information somewhere, by someone, at some point. It will not be stopped. Fail-open means only one thing: the system does not save itself.

And one more point, more important: the test applied to such a structure is not "do you believe it". The test is "can you point to its anchor".

A verifiable prediction

I will not end with a summary. A summary is what a writer uses when he has nothing left to say.

I will end with a verifiable prediction.

In this annual season, before the next transfer window closes, at least one widely published analysis will be shared thousands of times, cited on commentary shows, and built on a source its own author cannot name. It will have full tables, full headings, full technical vocabulary. And if you strip out the adjectives, you will not find a single anchor.

A second prediction, closer to the reader: most of the audience will not notice.

Empty stadiums taught us this: when nobody is shouting, a team's true value surfaces. The same is true of information. When the professional shell is peeled away — no noise, no shares, no argument — what remains is the true value of an analysis.

And if you want one concrete action, here it is. Next time you read a football analysis, do exactly one thing for forty seconds. Underline every proper noun, every number, every date. If the page is still covered in ink, you are reading analysis. If the page is clean, you are reading an empty spreadsheet dressed in prose.

I read data, and data whispers a name nobody has picked. If there is no name at all, I will be the first to say so — even if it costs me an article, a view count, or an argument I badly wanted to win.