The Empty Column: When Cricket's Data Returns Nothing

In the last week of January 2026, I had fourteen columns open on my laptop in an auction hall in Bengaluru. Purse left, role gap, overseas slot, the mood of the bidding team. The fourteenth column — "role gap" — stayed empty for the first four hours, because until then nobody had worked out what kind of bowler RCB was actually buying. The moment that column filled, the whole reading of the auction changed.

On 12 February 2026, a different document landed in front of me. Thirty-two pages, eight sections, a subheading under every heading, tables under every subheading, and in every row of every table the same phrase: "Insufficient information — cannot assess."

The document was not broken. It was doing its job correctly. The difficulty was that by doing its job honestly it had proved that the material handed to it contained not a single fact. No match, no player, no format, no date. Just a framework, admitting with great politeness that it had not been filled.

Twenty-seven years ago, on the sports desk of The Times of India, I was taught something: don't fear the blank page, fear the filled one. A blank page tells you plainly that you have nothing. A filled page where every sentence reads fine and not one of them carries information quietly eats your credibility.

Context: procedure growing between the facts

Cricket journalism has arrived, over the past decade, at a place where the biggest enemy of fact is not the lie but the process. Franchise data desks, broadcaster graphics, fantasy-platform indices, and now systems that write their own summaries — all of them make the same claim: that what happened on the field can be converted into a number. Most of the time the claim holds. My entire beat-keeping rests on it.

In 2026, when I was assigned to spend a full IPL season with RCB, I stopped attending press conferences within the first month. The team won three of fourteen matches and finished last. Virat Kohli missed the early games with a shoulder injury; AB de Villiers made only nine appearances, with back trouble. The conference question was "how is the mood", and the answer was "we trust the process." Both sentences were true and both were useless.

Instead I kept a ledger: throwdown counts at every M. Chinnaswamy training session, ice-bath minutes, travel delays, how long each batter stood in the nets actually working. That ledger explained selection calls better than the press conferences did. A "process notebook" began filing alongside the match reports, and my copy began running a day late.

The following year, at the January 2026 mega auction, that ledger became a spreadsheet. RCB retained Virat Kohli for ₹17 crore, AB de Villiers for ₹11 crore and Sarfaraz Khan for ₹1.75 crore; Brendon McCullum, Chris Woakes and Moeen Ali came in through the auction. My fourteen columns ended with a warning: this squad would not carry more than five specialist bowlers. That is what happened. RCB finished sixth in 2026 with a bowling economy around 8.9.

There is the first lesson. The model surfaced what the room would not say — that the purse constraint had eaten the bowling depth, while the public language was all about a "balanced squad". The model was right. The model could not tell you why sixth place happened.

In 2026 the question inverted. Inside the UAE bio-bubble I logged sleep, net sessions and travel windows for fourteen players, and built a fatigue matrix. The Dubai–Abu Dhabi–Sharjah legs were the noisiest part of that matrix. After back-to-back night matches, three middle-order batters logged under six hours' sleep. That middle order sagged late in the season; the team finished fourth and lost the Eliminator to Sunrisers Hyderabad. The team publicly denied the sleep data.

The table told one story; the dressing room kept another time. The way to publish both is to show first where they agree — the middle order was late on the ball — and then where they diverge, which is on why.

In November 2026 I was in Adelaide for the T20 World Cup semi-final. India made 168/6; England chased it without losing a wicket in sixteen overs, with twenty-four balls to spare. Jos Buttler and Alex Hales were at the crease when the last run came. I had spent that tournament building a powerplay strike-rate framework across twelve teams. India's score was not poor; it was an old-structure score for that pitch and that opponent. The fifth bowler was never used, and the run-rate maths in front of the bowling was running on boundary percentage rather than wickets. That night I did not write the dressing-room blame story; I wrote the chart showing where T20's scoring ceiling had moved.

The anatomy of a zero

Back to those thirty-two pages. They carried eight sections: format and match, player technique and data, team landscape and ranking, league and commercial ecosystem, rules and governance, risk, public narrative and expectation, and industry transmission. Three or four tables in each, and in every table the same phrase.

The document is itself a story, and should be read as one. When a system reaches the point of stating that it has nothing to report, that system has passed its hardest test. The difficulty lies in the next step nobody takes: printing it as it is, without trying to fill it with excitement.

In cricket journalism this takes three forms, and all three happen daily.

First — empty but valid. Correct schema, zero content. This is the most honest failure, because it is embarrassed by itself. It is easy to spot.

Second — filled but hollow. An eighty-word quote, six hundred words of scaffolding around it, and in the middle that line about "sources close to the squad" which is free of any name, any date, any accountability. This failure is never embarrassed, because nobody calls it a failure.

Third — inference seated in the chair of fact. It has numbers, decimal points, a graph — and not one verified point in the foundation.

All three run on the same fuel: the demand of the framework. If a report's structure requires no fewer than three analytical conclusions and two hidden-information items from every section, the report will produce them — whether or not the material exists. In journalism that demand is called an "angle". In politics it is called a "narrative". In cricket it is called "the mood".

I imposed one rule on my own work, and it cost me twice: two independent sources for every injury story. No second source and the story ran a day late. Once the delay was vindicated — what was described as a "shoulder strain" was really a workload case, and the team had sat on it. The second time the delay was wasted — the story was right and a rival beat me to it. That second day taught me that verification pays off in the credibility race, not the headline race.

The model's edge

The auction's purse arithmetic has become Indian cricket's most powerful selection committee. The work zonal selectors once did by touring grounds is now done by franchise scouting networks and retention maths. My fourteen columns at the 2026 auction showed exactly this: a player's price is set less by his ability than by the scarcity of his position.

And here the model's limit begins. The model hears what the room cannot say — it cannot tell you whether the room is empty or simply quiet. In that 2026 five-bowler projection I did not write that RCB would finish sixth. I wrote that there was a crack in the bowling depth and that it would show in the back half of the season. The difference matters: one is a prediction, the other a structural question. Readers prefer predictions; the model was built to ask questions.

After the 2026 Impact Player rule, that question sharpened. The rule shifted bowling depth at a cost the purse columns could not measure — teams began carrying an extra batter instead of a seventh or eighth specialist bowler, because the rule had made that batter nearly free. When the rule changes, every number from before it loses its comparative ground. I applied that to my own 2026 model: it is a historical document now, not a forecasting instrument.

Then there is the part least often written: printing the error bars alongside the number. With the 2026 fatigue matrix I stated three things plainly — that the sleep data came from self-reported player logs, that only eleven of fourteen players had complete records, and that the matrix could not distinguish whether the lost sleep hit technique or morale. Printing all three did not weaken the story; it raised the trust in it.

The habit is rare in cricket because our media ecosystem rewards claims and does not notice limits. The broadcast graphic glows with "economy 8.9"; underneath it does not say that the economy was built on Chinnaswamy's short boundaries, or how much of it came in the death overs. Nobody is hiding that. Nobody has the time to write it.

And that is the real information crisis in Indian cricket: not a shortage of information, but a habit of separating information from its context.

The cleanest example is domestic cricket. The Ranji Trophy's media footprint has shrunk steadily outside knockout weeks. That decline was never caused by T20 arriving; it was caused by the shrinking of the selection process that once connected domestic performance to the international door. When a reader stops believing that runs in Ranji lead anywhere, he stops reading Ranji. Then we say audiences prefer T20. Audiences prefer whatever visibly leads somewhere.

I have never treated India's bench strength as a talent shortage. The second XI is the hardest team in world sport to make and the hardest to keep coherent — and in India both problems exist at once, because the calendar and the selection do not speak each other's language. The end of the domestic season, the start of the next tour, and the workload of the man sitting out in between are decided at three different desks.

Where I agree with the consensus, and where I don't

The common view is that Indian cricket journalism's biggest problem is the hot take without data. That view strikes me as half right and entirely dated. The problem that has emerged in the last five years is the inverse: too much data, too much procedure, too little verification. The framework has itself become the alibi. A thirty-two-page report with eight sections, fourteen tables and zero information points is not a data failure — it is a process success that produced nothing.

The second common view is that the table and the dressing room are adversaries. It is the easiest and most misleading shape the material takes, because it writes the best sentence. The truth is that on most occasions the two say the same thing; only the language differs. In the 2026 bubble the table said the middle order was late on the ball; the dressing room said the same, calling it "rhythm". They separate only when the argument turns to cause. And the argument over cause runs on evidence rather than data, which requires a name, a date and accountability.

Third, and I am writing this against my own habit: where the consensus is correct, say so. Fixture congestion is the biggest cause of injury in cricket. Players have said it for years, physios have said it for years, and the fatigue data says it too. No medical team can fix a calendar of two matches a week; it can only keep the accounts of the damage. Dismissing that as sensationalism, or converting it into a clever contrarian line, is unjust to the fact.

Fourth, the thing that bothers me most: the underdog story. "Small town beats big city" — that line sells, and that line is often false. The player from the small town goes for less than the big-city player in the same auction, because his exposure is thinner, his video record shorter, and the school network behind him absent. Making his win into a story is easy; looking at his price in the table is necessary. Here the table and the story agree, and we ignore one of them.

Fifth, and I am certain of this: there is no conspiracy anywhere in this. Data systems sometimes return zero because the material never arrived. That is a plumbing defect, not an analytical one. Framing it as "a crisis in cricket journalism" would be another symptom of the very disease I am describing — putting the story ahead of the fact. I was not angry at that document. I was envious of it. It did what I fail to do most weeks: it refused.

What to watch

Over the next few months I will watch three things, and all three are small.

One: whether any broadcaster will print "insufficient data" on its own graphic. That single phrase is a maturity test for the whole industry. The channel that can print it will have every other number it shows trusted more.

Two: whether franchise data desks will publish a method note with their findings — where the data came from, how many players have complete records, what has been left out. That sounds absurd to demand until you remember that these desks inform auction bids, and auction bids decide careers.

Three: whether the domestic game's media footprint grows next season. That number will never appear on a graphic, but it will answer Indian cricket's second-largest question.

And one thing I am keeping for myself. At the 2026 auction I stopped counting bids and started counting the pauses between them, because a pause tells you when the room is thinking and when it has given up. The beat is not the crowd; it is the quiet before the structure breaks. Today I have a document with thirty-two pages and not one pause in it, because the material never came.

The next time a table completes a story for you, keep one question back: which column was left empty, and who was in a hurry to fill it?