Reading an Empty Spreadsheet: The Courage to Write 'Insufficient Information' in Football Analysis

It was a quarter to eleven at night. Wet clothes on the balcony line, a laptop on the table inside, a spreadsheet on the screen. Four columns, three rows, and every cell humming the same note — N/A. A match had finished that evening and the deadline was breathing down my neck, yet I did not have a single point of information in hand. I closed the sheet, made tea, opened it again. The spreadsheet blinked first, and I followed it into the story. That night's story was not about a match; it was about a pipeline — a place somewhere in the chain where extracting facts from the game had jammed, leaving the nine pillars of analysis standing on zero and waving at the air.

The rule is simple: evidence before comment, source before evidence. Since I launched Expected Dhaka in 2026, my work has split into two stages. The first stage squeezes information points out of raw reports and match accounts — who said it, when, in what context, and how reliable the source is. The second stage raises nine pillars on those points: tactics and execution, club finance and transfers, the results-and-opinion cycle, league landscape and team positioning, rules and governance, management and the dressing room, the risk map, the media narrative, and industry-wide transmission. As an economics graduate, xG is for me a currency of chance quality; if the currency is counterfeit, the ledger will not balance. When stage one is empty, the nine pillars of stage two are only scaffolding, not life — and that night proved it.

The tactical pillar emptied itself most shamelessly. This is where possession, passing, PPDA, field tilt, penalty-box entries and shot quality belong. I still use Spain against Russia at the 2026 World Cup as my teaching example: Spain completed 1,029 passes with 75 percent possession but generated only 1.1 xG, while Russia scored from 0.3 xG and won the shootout 3-4. One thousand and twenty-nine passes later, possession forgot how to score. I could tell that story because the numbers were in front of me. On a day when the sheet carries neither pass counts nor xG, writing about tactics means inventing fiction.

The same holds for the finance and transfer pillar. In January 2026 Chelsea paid Benfica 121 million euros for Enzo Fernandez — a 21-year-old midfielder who had just won Best Young Player at the Qatar World Cup with one goal, one assist and 87 percent pass completion. The model I built from progressive passes, xG chain and pressures per 90 had flagged him as elite before the fee looked obvious. The model worked because the input existed. Without input, that same model is just a handsome table.

The results-and-opinion cycle and the league landscape map stayed equally silent. After the pandemic break in 2026, I watched and wrote about 83 Bundesliga matches from home: in empty stadiums the home win rate fell from 43 to 33 percent, away teams' PPDA improved, and draws rose. Haaland's goals in Dortmund's 4-0 win at an empty Signal Iduna Park sat at the centre of that piece. Crowd, travel, emotion — those variables have entered every model of mine since. Silence is not something you merely endure; you have to learn its rhythm. But when a variable cannot be measured, the model stops.

The rules-and-governance room is where the VAR argument walks in. My experience says technology does not reduce controversy over decisions; it changes the controversy's address — from the pitch to the review room, and from the review room to the grey pages of the rulebook. The same logic applies to the analytical pipeline: adding information does not dissolve the argument, it relocates it somewhere more specific. So in the governance pillar, FFP or PSR calculations, transfer registration and sanctions are all in no state to be commented on today.

The dressing room and load-management pillar is the most sensitive one for me. Minutes, distance, recovery days, the age curve, injury history — these are not just numbers, they are career security. When a young midfielder's minutes suddenly double, I look first at medical access and travel schedules, and only then reach a conclusion. Without data, that responsibility too hangs over the table.

On the risk map, only one risk was identified that night, and it was not a sporting one — it was procedural. A stage-one pipeline returning empty means there is a crack somewhere in ingestion or parsing. In the media-narrative pillar, sample size, narrative lifespan and the tier of a rumour's source all wait for conjecture; and in the industry-transmission pillar, the chain from academy to broadcasting, from agent markets to the national team, remains a mere diagram.

There is also a Bangladeshi reading of these empty cells. Outside Dhaka, in district and divisional leagues where heat pools under stadium roofs and the travel budget means bus fare, dropping a European xG or pressing model in unchanged is not analysis — it is colonisation. The core job of Expected Dhaka is to fit the model against bumpy pitches, sweat, empty galleries and limited scouting. A model that does not measure is merely a pitiable object.

The same caution applies when drawing a transfer-value map. Hunting undervalued midfielders across Bangladesh and regional markets, I find the fee number incomplete unless family, education, migration risk and club stability sit beside it. Likewise, a minutes graph only becomes meaningful in the light of a young player's age, position, medical access and rest management. When a number does not speak about the person beside it, the number is half a truth.

This is where an uncomfortable question surfaces. Saying 'there is no information, so no assessment is possible' is admirable honesty, but it is also a comfortable shelter. Making a careful estimate on limited data and staying silent under the excuse of missing data are two different professions. The reality of football journalism is that deadlines often demand decisions on half-information, and readers need a weighted verdict grounded in experience. My own experience says the empty cells are themselves information: which question nobody wanted asked, which number never surfaced, who is comfortable keeping facts hidden. An empty spreadsheet is therefore not only a failure; it is also a signal.

The signal for the next round is simple. Every stage of data collection needs a completeness lock — a minimum number of information points, identified entities, a verifiable source; only then does analysis begin. The question is no longer football's but ours, the people who talk about football: what can we truly see in front of the game's truth, and have we learned to name what we cannot?