The Ranji Blackout and the Selection Question: Where the Data Ends, the Bench-Strength Debate Begins

Indian cricket's richest ball-by-ball record sits at the very top of the pyramid — the IPL. Below it, the Ranji Trophy, Vijay Hazare and Syed Mushtaq Ali tiers sit in partial darkness. For the past few weeks I was doing a simple task: listing which domestic-season matches have publicly available ball-by-ball data, and comparing that against matches where only the scorecard survives. The result was what I suspected, but the scale was larger than expected: a full Ranji season yields less detailed ball data than a single IPL weekend. This comparison is aimed at no team — it is aimed at the number we repeat in every selection debate without auditing it: bench strength.

I built the ladder by hand — first deciding which data exists, in what format, from which source, and then placing it into a table. Sources were of three kinds: board-published scorecards, broadcaster data, and public scoring platforms. All three speak different languages and define accuracy differently. So the first task was to state sample size and confidence before any finding. When you can compute a 40-ball phase split — powerplay, middle overs, death — the temptation is to do it. But 40 death balls means two or three matches; building or destroying a "death specialist" label on that is model abuse.

This is where the real subject emerges. India's domestic structure runs three formats, but the depth of record differs across all three. Ranji has long-format games that can stretch to 150 overs an innings, and several state associations do not publish the full ball-by-ball log. Vijay Hazare has 50 overs, where the scorecard exists but line, length, field placement and shot selection do not. Syed Mushtaq Ali holds the largest reserve of pace and finishing, but the thinnest recorded history. The IPL, by contrast: batter, bowler, fielder, shot type, angle — everything.

The effect on selection is direct. When searching for "young talent" or a "death-over specialist," the data comes from where it is cleanest — the IPL. Selection's evidentiary base thus becomes the competition that is most visible, not the one that is most representative. I call this the availability bias. It does not add falsehood to the numbers; it deletes the rows that were never recorded. What looks like a trend is often a missing column in disguise.

I isolated domestic players with enough matches across all three formats in recent seasons, and checked what public opinion about them rested on. In nearly every case, the strongest part of the opinion came from the format with the most complete data, and the weakest from the format with the most incomplete. That is not coincidence. When a scout compares two players and one has 60 matches of data while the other has 12, the model will still run — but the confidence it reports should differ. Most models do not say so.

The sharpest example is death bowling. An IPL bowler may have 200 death deliveries, enough for economy, wicket rate and wide-yorker frequency to be stable. The same bowler in domestic T20 bowls 60 — small enough that one bad day distorts a season average. And because domestic T20 data is less visible, the selector's mind returns to the number that glows. This is not bad intent; it is a data-collection gap that we rename as a selection debate.

Now the caution. It is easy to say "domestic data is incomplete, therefore selection is wrong." But correlation is not causation. It is also possible that some players shone in the IPL because their domestic record was already good — the IPL revealed rather than made them. My table cannot cleanly separate that, because the detailed domestic record needed for comparison simply does not exist. I will not make a firm claim here even after three independent checks — and when I don't, the reader deserves to know why I stopped.

On the other hand, a data gap is not a player's gap. There are Ranji bowlers averaging 19 whose speeds or seam movement are unrecorded. There are batters who made 400+ runs in the fourth innings, with no record of the bowling or conditions they faced. That does not make them weak; it means we often count what we don't know against them. This is a structural inequity that is administrative, not technical.

The gap is deeper in women's cricket. Domestic women's competitions have never had IPL-scale public ball-by-ball records. When we discuss selection for a World Cup or major tournament, the men's team has at least three tiers of data; the women's team often has only scorecards and a few figures. This inequality is about investment, not just reporting. What is not seen does not sell; what does not sell does not generate data; and what has no data has a selection debate forever.

Last year I attended a domestic match in a small stadium where the scorebook was kept by hand. A scout in the pavilion told me he could not find the match data on any app. I said he was not alone. That comment still bothers me — the player who made 80 that day exists in no table, only in a handwritten book.

The solution is technical, but it begins with intent. The board must mandate ball-by-ball logging for domestic matches, at minimum for wickets and key events. Some state associations already do this, but the standard varies. Until a shared framework exists, every selection debate will end where it began: "How did he do in the IPL?"

If we want to treat bench strength seriously next season, the first question should not be who plays — it should be how much we know about whom. Because while the table is incomplete, selection will always be an estimate, however confidently it is presented.