The Blockchain of an Empty Spreadsheet: A New Path to Verifying Football Data

The spreadsheet blinked first, and I followed it into the story. Last week, sitting on my balcony in Dhaka with morning tea, I opened an analysis document. The title field said: not applicable, insufficient information. The source field said the same. The core viewpoints were blank. The list of information points was blank. A document meant to analyse football across nine dimensions had the same sentence inserted into every cell: not enough information.

For more than three decades I have held football scorecards in my hands. I have watched a goalkeeper's hands shake before a penalty shootout, watched a ball die on a rain-soaked pitch, watched a team search for the goal's mouth after nearly a thousand passes. This document was still different. No team, no player, no goal — only a confession: I do not know.

In the world of football data, that confession is rare. Rare enough to be news. And that news pulled me toward a question now being whispered in European club offices, in agents' inboxes, and across South Asian scouting networks. If data really is football's new currency, who protects its history, its ownership, and its integrity? This is where blockchain walks in — loudly.

Over the past decade, football analysis has split into two stages. Stage one is deconstruction: extracting information points from a match, a report, or video. Stage two is deep analysis: reaching conclusions across nine dimensions — tactics, club finance, results and public-opinion cycles, league geography, rules and governance, management and dressing room, risk, media atmosphere, and industry transmission.

The entire logic of that pipeline rests on one belief: the information points from stage one are reliable. What happens to stage two when that belief collapses? The document in my hands answered it, and the answer is not comfortable. Every cell read: not applicable. The stated reason: stage one produced no analysable content.

When I left a Dhaka daily's sports desk in 2026 to launch a one-man data newsletter, I had one condition: I must know the birth story of every number I publish. I called the newsletter Expected Dhaka. As an economics graduate, I treated expected goals as the currency of chance quality — an exchange rate that tells you how much danger a team actually created.

At the 2026 Under-17 World Cup, I analysed England's 5-2 final win over Spain with shot maps and xG. Rhian Brewster's eight goals and Phil Foden's two in the final made a thread go viral, and I understood that from Dhaka I could still tell the world's football data stories.

The following year, after Spain's match against Russia at the World Cup, I wrote a piece titled Possession Is Not Control. Spain completed 1,029 passes, held 75 percent possession, and generated only 1.1 xG. Russia scored from 0.3 xG, made it 1-1, and won the shootout 4-3. One thousand and twenty-nine passes later, possession forgot how to score — that sentence still follows me.

In 2026, when sport stopped, I spent a week nearly unravelling. Then the Bundesliga returned, behind closed doors. I analysed 83 matches after the restart and found home win rate fell from 43 percent to 33 percent, away teams' PPDA improved, and draws rose. Borussia Dortmund's 4-0 win, with Erling Haaland scoring, became my case study.

In 2026, Denmark's run after Christian Eriksen collapsed on the pitch at the Euros, and 13-year-old Momiji Nishiya's skateboarding gold in Tokyo, taught me something models cannot measure: crowds, fear, grief, and the breaking of habit.

At Qatar 2026 my eyes locked onto Enzo Fernández. Best Young Player, one goal, one assist, 87 percent pass completion. On 31 January 2026, Chelsea paid Benfica 121 million euros for him. My transfer-value model had flagged him as elite before the fee looked obvious, because it watched three fingerprints: progressive passes, xG chain, and pressures per 90.

So many years, so many numbers — and then a completely empty document landed in my hands. That is what pushed me into football's newest argument. If data is the raw material of decisions, then the truth of the data must be provable before the decision. A handful of European leagues, clubs, and broadcasters are now trying to do exactly that with blockchain.

The first problem is not the model. It is the certificate. An xG figure today can arrive six different ways from six sources, because each provider uses its own model, its own shot data, and its own weights. Post-match debate is about the number; nobody asks which model version, which dataset, and which moment produced it. Blockchain's simplest use sits right here: writing an immutable hash of every model version on-chain so any number's birth certificate can be verified later.

I call this the birth certificate of data. Model version, training data source, correction date — if those three live on-chain, the argument between analyst and club disappears, and so does the back door for quietly swapping a number. Readers of my old newsletter know I like a data source beside every claim. Blockchain turns that source into an immutable receipt.

The second place is the transfer market, and this is where the money is largest. A modern transfer is not one club paying another. Sell-on clauses, performance bonuses, appearance fees, solidarity payments, agent commissions — at least six parties sit behind a single move. In a deal like Enzo Fernández's 121 million euros, those layers become so complex that verifying who was paid what, and when, is nearly impossible from outside.

Smart contracts can solve a large part of this. If contract conditions are written in code, appearance fees pay automatically, sell-on shares distribute automatically, and every transaction stays in a public ledger. But here is the first trap. Code enforces conditions; code does not interpret them. Injury, tax regimes, disputed clauses — in these places a smart contract is cold.

The third place is the player's body, and here I want to be most careful. Minutes, distance, sprints, recovery — this data is locked in club servers today. When a player leaves, the history of his own body does not travel with him. In the tournament load index I work with, a young player's minutes spike is alarming — especially somewhere like Bangladesh, where recovery facilities, medical support, and pitch quality are three separate barriers at once.

A consent-based blockchain model could help: the player owns his medical data, a club gets permission for a defined period and purpose, and the record of that permission cannot be erased. It sounds good. The reality is that a player on a fifty-thousand-taka monthly contract does not gain bargaining power from data ownership. He gains paperwork.

The fourth place is referees and VAR, and I have an old suspicion here. VAR has not reduced controversy; it moved controversy from the pitch into the review room and the grey zones of the rulebook. Why a decision was made in slow motion on television is an answer viewers never receive. If referee audio logs, VAR communication, and decision timestamps sat in a verifiable ledger, suspicion would not vanish — but its object would change.

Blockchain's biggest promise here is integrity, not transparency. A decision on the pitch can be wrong, but the record of that decision cannot be perfectly erased. That distinction matters. Transparency means everyone sees everything; integrity means what was seen cannot later be altered. For football administration, the second is more urgent.

The fifth place is geography, and here I will speak most plainly. The Bangladesh Premier League, the divisional leagues, the district leagues — their data infrastructure is not Europe's. One camera at the venue, a scorer with a handwritten notebook, scouting reports built from a team leader's spoken words. In that reality, building an on-chain ledger does not mean planting a server beside the pitch. It means something far more basic: match score, line-up, cards, and minutes recorded immutably in at least one place.

There is a danger here and I see it clearly. European models, European thresholds, European language — transplanted unchanged into South Asia, that is not analysis. It is colonisation. On a pitch where dew settles on the grass in the evening, where floodlights die mid-match, where an away trip takes four hours, pricing a player by pressures per 90 is absurd.

The core lesson of Expected Dhaka was this: a model can be imported, but its local assumptions must be rewritten. From that came the order — first the integrity of basic facts, then transfer-value models, then pressing, then higher feature engineering. In a league whose goal counts cannot be verified, writing an xG chain on-chain is a meaningless ritual.

The sixth place is the data trade. Football data is sold today to broadcasters, bookmakers, fantasy platforms, insurance companies. A player does not know who is buying his sprints per minute. A blockchain-based data marketplace could surface ownership — a player could sell a share of his performance data, take a cut of the contract, and no one could hide the transaction.

I remain sceptical of that promise, because in football's economy a player does not control the market for his own labour. Why would an agent earning a twenty-million-dollar commission take on the job of explaining the terms of a data economy to his client? The same applies to fan tokens. A token converts devotion into a product; it does not give supporters real voting power over club decisions.

The seventh place is management and the dressing room, where data helps least. Why a manager makes a substitution in the 68th minute may rest on load data — or on personal relationships. Contracts, age curves, injury history, and media pressure do not change because blockchain arrived. An owner's patience is not verifiable, only accountable.

So of the nine dimensions meant to carry an analysis, only three can genuinely be improved by blockchain: the record of results, the flow of money, and regulatory compliance. The other six — tactics, dressing room, public opinion, the interpretation of risk, industry transmission — gain nothing from a ledger. Human judgement, fear, and error are bigger truths here than numbers.

And this is where my objection must be said loudly. The document that started this article is not really about the commercial potential of blockchain projects. It is about an embarrassing fact. Stage one of the pipeline came back empty. If someone had filled those empty cells with attractive numbers, no one could have caught it. The greatest danger in the data world is not the absence of data. It is the skill of hiding that absence.

An immutable ledger builds a wall against that skill. An empty document cannot later be filled in. But the wall protects the record, not the truth.

Blockchain does not stop lies. It stops lies from being hidden. Miss that distinction and football administration will repeat the mistake it made with VAR — bringing in a new machine, moving an old controversy to a new address, and declaring the problem solved. If a large share of the money spent installing blockchain went instead to hiring scorers at district grounds, buying cameras, or digitising last season's notebooks, information integrity would rise far more.

One more question circles my head. Much of football's data is produced on pitches in the global South and sold into northern markets. An on-chain ledger does not erase that inequality; it can give it a permanent, currency-like form. If ownership rests with the body that runs the app, hosts the server, and sets the language of interpretation, then decentralisation will create a new centre rather than remove the old one.

Still, this is no moment to sit entirely empty-handed. I have been talking with young club analysts who want at least line-ups and card records stored somewhere with a timestamp. Start small. Four facts from one match: score, line-up, cards, time. A four-month district league fixture list. One young player's full season of minutes. Models come after things accumulate, not before.

At fifty-six, one rule has stuck with me: technology does not change leagues; the internal blood pressure of leagues changes. I have heard stories of broken notebooks and blank scorecards from venues in Pakistan, Nepal, and Sri Lanka. The problem there is not blockchain, and blockchain is not the solution. The problem is that nobody considers the notebook important.

I am still hopeful, because I am a numbers man. If an immutable record exists, a player's minutes history does not change when he changes clubs. If a sell-on clause lives in code, there is less room to stiff a small club. If three matches of a Bangladesh district eleven sit immutably on record, that creates a new scouting reality outside Dhaka's inner circle. Bringing the districts to the centre has no quieter route than this.

It needs nothing large. A small budget, a simple specification, and one commitment — preserving history, not numbers. The day nobody can quietly alter a Bangladesh league scorecard from a Dhaka desk, we will have crossed a night in the language of data.

What is still missing is a name for this data. What shall we call the blockchain that walks into football data? Ledger? Ownership? Accountability? I do not know. Some things never get a data name; they get a player's face, the smell of a pitch, and the name of a truth that arrived slightly late. Perhaps that is the most honest definition of this technology.

At the next match, when I look at the scoreboard, I will search for one extra thing. Not whether the number is right. Whether someone can show where the number came from. If the answer matches, I will say: this time, the data cannot hide. If it does not, I will say: the room to hide still exists, and that is football's biggest gap.