The Empty Cells in a Major-Tournament Analysis Sheet

In the fourth minute of stoppage time at Rostov-on-Don, Nacer Chadli put the ball into Japan's net, closing out a counter-attack that lasted less than ten seconds. Belgium won 3-2. Ten minutes earlier, I had been sitting in the commentary booth of a Brazilian television channel in Moscow, convinced Japan would pull off something remarkable.

My data sheet was open on the screen. The physical-duel column leaned heavily toward Belgium. The ground-duel column did too. The knockout-stage experience column was even more lopsided. And yet, inside the first seven minutes of the second half, Genki Haraguchi and Takashi Inui put Japan 2-0 up with two transitions so quick that Belgium's back line could not turn in time.

That night I rewatched the tape five times. Only on the fifth pass did I see what I had missed: the space between Belgium's lines was wide enough that a single vertical pass cut straight through. That metric did not exist in my toolkit in 2026. It lived in none of the columns I used to grade a match.

That is when I began paying attention to empty cells.

Context: an industry allergic to silence

Modern football analysis is not short of data. GPS vests, tracking cameras, probabilistic models, expected goals, passes allowed per defensive action — all available, all updated by the minute. A major tournament is when that volume swells fastest, because every match drags along hundreds of pages of numbers and thousands of charts.

My job has therefore become easier. And more dangerous.

The danger lies here: when metrics multiply, the analyst's reflex is to fill every gap with something that sounds plausible. A missing column gets interpolated. A small sample gets stretched. A phenomenon nobody has measured gets a prettier name — character, spirit, class.

I grew up in Vietnam, work in Brazil, and have followed professional football for thirty-two years. For most of that time I believed the best analyst was the one with the most data. I no longer believe that. The best analyst is the one who knows exactly what he has not yet measured.

In data science, that move has a name: null handling. An empty cell is a valid result, not a failure. But in football, where everyone must have an opinion within twenty minutes of the final whistle, leaving it empty is treated as weakness.

A major tournament compresses time in another way. A national team gathers for three weeks, plays seven matches, dissolves. There is no next season to correct mistakes. That compression turns every analysis sheet into a promise the writer is obliged to keep, even without enough data to keep it.

Core: three times I had to say 'not enough'

In 2026 I was an assistant tactical analyst at Fluminense. The coaching staff wanted to switch to high pressing, based on GPS data from the previous twelve matches. Twelve matches is a beautiful sample: enough to draw a trend, enough to win a meeting room.

I was the only one who asked for the data's stability to be checked across three seasons. The result: Fluminense's defensive system only functioned when the opponent's lateral-pass rate exceeded 62 percent. Below that threshold, high pressing became self-harm. I presented an analysis of 47 matches and proposed keeping the 4-2-3-1, tightening pressure only on the right flank.

Fluminense finished sixth, four places better than the previous season. The point is not that I was right. The point is that if I had accepted the twelve-match sample, I could have delivered a very confident and very wrong conclusion.

A confident, wrong conclusion leaves no mark on the scoreboard. It leaves a mark elsewhere: we gradually lose the ability to tell what we know from what we want to believe.

Two years later the lesson returned in another form. In the 2026 Brasileirão, when the pandemic forced matches behind closed doors, I was assigned to analyse thirty matches for a sports magazine. Home win rate fell from 48 percent to 39 percent. High-pressing teams lost an average of 12 percent effectiveness. Home advantage does not sit on the scoreboard; it sits in the player's eardrum — and when that eardrum falls silent, an entire tactical system loses part of its energy.

I wrote a forty-page report and proposed adjusting a home-pressure index for every future analysis. The editors objected that it was too long. It was later split into three instalments. An empty stadium is the flattest mirror football has ever held up to itself.

The contrarian angle: the blind spot is not missing data

A common misreading holds that analysis's greatest risk is a shortage of data. I think the greater risk sits on the opposite side — filling empty cells with plausible noise.

The transfer market exposes that habit most clearly. A player with fewer than fifty top-flight appearances can be valued at one hundred million euros, and the accompanying analysis will be full of metrics sliced from a few months. The thinner the sample, the prettier the chart. That is a naked gamble wearing a data jacket.

I am not arguing against models. A model is not wrong — it simply has not yet learned how to speak. It answers exactly the question I asked, and stays silent on the question I have not yet thought to ask.

So the blind spot in this profession is operational rather than technical. It appears in the moment an analyst is required to conclude before the data has ripened. Humility is not the same as avoiding judgement. Once cross-verification is done, a practitioner must state plainly: this is what I believe, at this level of confidence, under these conditions. The best coaches know which number to trust when things are difficult.

What to watch in the coming weeks

World Cup 2026 taught me that every model needs a humble seat. The major tournament ahead will test an entire generation of analysis sheets: who dares to leave a cell empty, and who fills it with a good story.

Data tells the first part of the story; the rest is flesh and sweat. When you read an analysis in the coming days, the most interesting thing may be the empty cell — where the author admits he does not yet know. That empty cell is the promise of a better question.