SL vs Ind, 2nd Test - The trouble with trying to understand Rishabh Pant

In 2026, cricket is being overrun by armies of spreadsheet merchants who take pride in quantifying information that had previously been the preserve of received wisdom, gut feeling, and guesswork. Every major cricket team now carries outright data scientists or science-adjacent professionals in the backroom whose job it is to attach numbers to physical cricketing acts.

There are no fast bowlers who happen to “bowl a heavy ball” any more, there are only quicks who have a release point X% later than the average bowler, and whose deliveries lose pace at Y% less than the mean loss of pace for balls that pitch on that length. Spinners don’t just “give the ball a rip”, they impart X revolutions-per-second as measured by high-speed cameras, and get Y degrees of turn off the deck.

More than any force acting upon cricket, hard science has shaped the last 15 years of the game’s evolution. Cricket, largely, is better for the granular – almost molecular – understanding of its own physics. It makes teams better at picking players that will sustain their performance, and better at identifying and correcting technical issues, better at devising strategy, better at reading conditions, better at phase-wise breakdowns of expected wickets given bowling lengths delivered on surfaces of a specific profile. If you’re still making cricketing decisions based on a “hunch”, put on this loincloth and rub a pair of sticks together, my friend. Have fun in the Stone Age.

All the data ever mined from all cricket games ever played, pushed through the greatest processors known to man, drawing from acres-big water-guzzling data centres would struggle to quantify Pant. Our man has no love for predictability, no preclusions towards convention, and does not do reverence.

He doesn’t revel in chaos exactly. He just embodies it. Happens to embody it. A Rishabh Pant six is happening to Pant just as much as it is happening to the bowler and everybody else. As Karthik Krishnaswamy wrote last week “even our years of watching Rishabh Pant have helped only so much in understanding him.” Statistical models. Generative AI. Advanced algorithmic modelling. They could never. Not yet.

Which algorithm would spit out this sequence of events for example?

On the first evening of a Test, Pant tries to hook a 133kph short ball from Lahiru Kumara with one of his falling-over pull shots. He misses completely and is struck on the wrist, forcing him to retire hurt, although the way he left the field it felt like he was retiring hurt against his own will. Before long he was down at the dugout, looking ruefully at the runs his teammates were making and he was not. Before the end of the day he was padded up again, at the edge of the field, available at a moment’s notice.

He had to wait till the following morning and until after Sri Lanka had taken the second new ball to get out there, and having taken a couple of singles against Asitha Fernando, he faced a series of bouncers from the bowler who had hit him the day before. The first one, he ducked. The second one, he attempted to play a controlled pull shot to deep fine leg to, and missed. To the third one, at 137kph (4kph faster than the one he was hit by), Pant falls over to the off side and plays his favourite hook shot again, connecting so sweetly, so utterly spectacularly, that it lands on the gabled roof of the highest stand in the stadium, and leaps for good out of the camera’s view, possibly into one of the other cricket grounds on Maitland Place.

Imagine finding that ball on another outfield, or on the road, a four-piece Test-match Kookaburra, only 9.5 overs old. It may as well have fallen from outer space. Like Pant.

He didn’t crow about this mega-six either. Didn’t stare Kumara down. Didn’t gesture at the bowler who had struck him the previous day. He doesn’t look to dominate bowlers exactly. He just happens to dominate them. He doesn’t need them to fear him. He is content to be the tornado that occasionally blows through their lives, uprooting foundations laid in previous spells, upending plans devised by information parsed in spreadsheets.

In 2022, a car crash almost ended his life, not merely his career, and yet he has come back as one of the best wicketkeeper batters in the Test game currently, adhering to an onerous diet and sleep regime to aid his recovery. Who could predict he was capable of such discipline? And having treated his start on the previous evening, and the re-start on the second morning with such respect, who would expect him to run down the track first ball after lunch and hole out to mid off? Even his unpredictability is unpredictable. He started shoulder-barging bouncers at one point, the ball looping off his flesh almost onto the stumps, missing them by millimetres. Among dismissals, it would would have been one of the strangest ever in cricket. Like Pant.

“Pant doesn’t look to dominate bowlers exactly. He just happens to dominate them. He doesn’t need them to fear him. He is content to be the tornado that occasionally blows through their lives, uprooting foundations laid in previous spells”

There is a concept in astrophysics that encapsulates what Pant brings to the game: The Three Body Problem. When just two cosmic bodies of roughly the same size and density fall into each other’s orbit, scientists are capable of calculating the orbital movements this pair will eventually settle into. In fact, they have been able to make this calculation for centuries. But add a third body of roughly the same gravitational mass, and suddenly the system descends into indecipherable chaos. One body entering the system at a fraction of a kilometre a second faster, or at a fraction of an a degree in another direction, leads to wildly different results. As astrophysics educator Neil de Grasse Tyson explains, “what chaos will do for you in a mathematical model is that if you change the initial conditions by a little bit, the solution diverges. It goes crazy.” A whole new branch of calculus may be needed to work this out, if ever it happens.

You can predict where balls bowled at X pitch, released from Y height, on a Z-type pitch will end up in relation to the average left-handed batter. But what the synapses in Pant’s brain will do in response is a subject as-yet undemistyfied by science. Wheeling freely in the gaps of human knowledge is this India wicketkeeper batter.

We might not know how he will play to which ball when, but we do remember the grins we broke into when he struck another tumbling slog sweep for six, the gasps that left our mouths when he made a sweet connection with the ball he had no business making, and jaws we chase around the living room after he made us drop them. Long may his chaos reign.

Andrew Fidel Fernando is a senior writer at Cricinfo. @afidelf

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