3 years

Openomics 2018

The Kohli Rate of Growth

Aditya Iyer is the sports editor at Open
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Economic lessons from the captain’s chase

IN THE BOOK Soccernomics, a crash-course into viewing a global sport through the prism of economics, authors Simon Kuper and Stefan Szymanski, a football journalist and an economist, respectively, expend a fair amount of pages on the penalty kick. Of course they do, given, ‘a surprising number of economists have thought hard about the humble penalty kick… even Steve Levitt, winner of perhaps the most important prize in economics, the Clark Medal (which some insiders think outranks the Nobel)’.

But the chapter doesn’t instantly jump into how the simple spot-kick illuminated research into game theory, which in turn helped the American government predict and plot against Soviet moves during the Cold War. It begins with John Terry, Chelsea’s legendary defender and captain, missing a penalty against Manchester United in Moscow in 2008 that left his side inches short of club-football’s most coveted trophy, the UEFA Champions League. In popular culture, Terry’s small miss (the ball smacked the post) has had big repercussions: it is widely regarded as the club- equivalent of Roberto Baggio’s shank for Italy in the World Cup final of 1994.

‘We now know that a Basque economist told Chelsea that Edwin Van der Sar (Manchester United’s goalie) tended to dive right against right-footed kickers,’ write Kuper and Szymanski. ‘Van der Sar did indeed dive right, as the Basque economist had foreseen, but Terry slipped on the wet grass, and his shot into the left-hand corner missed by inches.’ It cost Chelsea the trophy but according to the economists in the book: ‘By one estimate, Terry’s penalty cost Chelsea $170 million.’

Fans, however, will tell you that the real cost of Terry’s miss was neither the silverware nor the money; it was the lifelong scar that that moment left on the 25.6 million loyalists Chelsea had worldwide in 2008 (data from Sport+Markt).

That is quite a figure. Yet, it doesn’t hold a candle to the number of TV viewers an international cricket match involving the Indian team generates, a number that only balloons further if that match happens to be a World Cup fixture. When India played Pakistan in the semi-final of the 50-over World Cup in India back in 2011, 495 million individuals tuned in. Which, then, begs the question: What is the real cost of an India loss in a match of consequence? Is it the crores lost in revenue? Or is it the half-a-billion broken hearts?

Cricket, unlike football, does not have anything as diabolical as penalties in its game play. But it does have a run chase and every single cricket match ends in one. In a match limited to 50 overs per side—just the right limit for each of the 300 balls to feel at a premium and the target daunting enough for each of the 11 batsmen to saddle a share of the burden—a run chase can often sustain the unnerving pulse of a penalty shootout for close to three hours. Couple that with the parameters of situation and stage, and the ODI run chase is an economist’s dream; a dream that involves metrics deeper than just overs left, wickets in hand and required run rate.

In the summer of 2003, with all these ingredients in place at the World Cup final in Johannesburg, the Indian team experienced its own Terry moment—a jolt that rankled among, conservatively speaking, 250 million fans in India, or 10 times the quantity of Chelsea’s worldwide fans. And unlike Chelsea, the Indian dressing room did not have an economist at its disposal to work out an endgame. But they did have Sachin Tendulkar, the most calculative cricket brain the world had seen yet.

At the Wanderers, after India captain Sourav Ganguly had put Australia in to bat, Ricky Ponting’s unbeaten 140 helped his side to 359 runs—the most runs ever scored in a World Cup final. When Tendulkar noticed the long faces and drooping shoulders of his teammates during the innings break, he delivered a speech that was an education in the fundamentals of economics: the scarcity of a key resource and how best to optimise its use in achieving a goal. “If we aim to hit one boundary every over, just one, then we would have scored 200 runs in 50 balls,” Tendulkar’s fabled pep-talk went. “If we do that successfully, only 160 runs will be left, with 250 balls in hand.”

Thanks to his phenomenal rate of success, Virat Kohli's brain began attracting the analysis of economists, mathematicians and statisticians

Tendulkar put his theory to test in the very first over. Fourth ball, he pulled Glenn McGrath through midwicket for a boundary. But then, the very next ball, as Tendulkar looked to repeat the feat, he top-edged a pull, was caught and bowled by the bowler. India folded soon after. In a recent interview with this magazine, Ganguly revealed that this loss remains “the greatest regret” of his life.

Many years later, in a round-table conversation with McGrath in New Delhi, the Australian fast bowler was informed of Tendulkar’s dressing room talk. McGrath pressed his lips together to show that he was impressed, only to wink and add: “But it really didn’t work now, did it?” McGrath, like many old timers in cricket, resisted data and was under the impression that number-crunching had no place in practice, especially during the inevitability that is a run-chase in a big game. And to be fair to him, McGrath’s audience that day readily agreed. Until, that is, Tendulkar’s heir-apparent, Virat Kohli, showed up.

Fond of ‘calculations on a cricket field’, as he put it in a recent interview, Kohli has redefined the way both cricketers and analysts approach the second innings of a cricket match. It will be fair to say that no other batsman in the history of the game has approached targets quite as clinically as Kohli does and thanks to his phenomenal rate of success, his brain began attracting the analysis of economists, mathematicians and statisticians. And, in one case, even a cosmologist.

WHEN SOCCCERNOMICS was published, Kuper was asked by the New York Times just why he put himself through the arduous task of explaining a game through the lens of economics, to which he answered: “The heart of the matter is that thinking in soccer is outdated, backward and tradition based. It needs a fresh look based on data.” Himanish Ganjoo, a Delhi-based cosmologist, echoes Kuper’s sentiments when he says: “I got into data because as a cricket fan, I found it appalling that stats in the game didn’t include context.”

Ganjoo was used to crunching astronomical banks of numbers—he simulates large-scale distribution of dark matter across the universe for a living. That bent of mind, then, came in handy when he decided to simulate the distribution of matter across the smaller but largely untouched landscape of cricket. “More than most other global sports, cricket is a stats-oriented game,” Ganjoo says. “But I found it disconcerting that despite the large wealth of numbers, most of the analysis done was rudimentary.”

Which is another way of saying that everyone knows Virat Kohli revels in run chases. And that out of his 35 ODI centuries (second only to Tendulkar on the all-time list) thus far, 21 Kohli tons have been struck with India hunting down a total. Or that 19 of those 21 hundreds were scored in winning causes. These numbers— figures representative of a winning Indian team—have kept sponsors and broadcasters agog. Last year, Oppo spent Rs 1,079 crore to be India’s title shirt sponsor, and Star Sports broke the bank with Rs 16,347.5 crore for exclusive media rights to the IPL for the next five years.

The big wheel of Indian cricket turns on the nuts and bolts of numbers and performances—both largely produced by Kohli these days

The big wheel of Indian cricket turns on the nuts and bolts of numbers and performances—both largely produced by Kohli these days—so Ganjoo decided to see just what India’s star batsman does right to keep the economics of the game ticking. “I was more interested in how Kohli scored those runs. What made him score those runs. And why he has become the greatest run chaser we have ever seen,” he says. He built his database from scratch, learnt to code, and constructed his own metrics to get some in-depth answers.

To understand Kohli, Ganjoo approached his vast reservoir of numbers as an economist would, reading heavily into how the batsman makes use of the most significant finite resource at his disposal during a chase—deliveries. His findings are laid bare on his computer monitor, crunched by the Python programming language, and in the form of graphs and numbers on an Excel sheet. “To start things off, I found out his balls-per-dismissal—or the deliveries version of his batting average in run chases,” he says, “How many balls does he face on average between dismissals when India is batting second?” The spreadsheet says Kohli gets out once in 71.1 balls, fourth on the list after Michael Bevan (83.6), Sunil Gavaskar (79.5) and Gordon Greenidge (75.7). “Now this is a remarkable achievement for Kohli, given that Bevan was a lower-order finisher and stayed not out a lot and both Gavaskar and Greenidge were openers so they of course had more balls to face. For a batsman who has batted predominantly between No 3 and No 6, Kohli is the only one up there.”

The next metric is balls-per-innings, or how many balls on average Kohli consumes in a run-chase: 53.9 balls. Doesn’t sound like a lot? Here’s some perspective. Kohli is fifth on this list (behind four openers, Gavaskar, Greenidge, Geoff Marsh and Kepler Wessels but at a far superior strike-rate to any of them) and way ahead of every other ODI legend—39 places above Brian Lara (44.2), 43 places ahead of Ricky Ponting (43.4) and 48 spots above Tendulkar (42.4). Says Ganjoo: “These two indicators reveal to us that Kohli likes to spend more time at the crease in pressure situations than any of the other greats, so the next obvious question is: what does he do with that time at the crease?”

For one, it is common knowledge that Kohli likes to run a lot—singles, doubles and triples—pushing his batting partners to the point of exhaustion. As Kohli transformed physically from fat to fit to freak, his mental approach to the game metamorphosed too, as Kohli shelved rope-clearing hits for hard bursts across the 22-yard strip. Can this strategic change be tracked on the spreadsheet? “Sure,” says Ganjoo. “During ODI chases, Kohli has scored more non- boundary runs on average than any other player in the history of the game. He is No 1 here, with an absolute number of 26.9 non- boundary runs per game.” On this indicator, his ‘greatest of their era’ predecessors, Tendulkar and Viv Richards, are positioned 48th and 49th respectively.

But Kohli’s reputation for being the game’s finest run-hunter isn’t based solely on him being able to physically out-run his competition. What makes him truly unique is that he likes to smack swift and safe grass-hugging fours as well. Only his Delhi-mate Shikhar Dhawan hits more boundaries on average (5.9 per game) in ODI run chases than Kohli (5.6). So when Kohli’s boundaries per innings (BPI) and non-boundary runs per innings (NBRPI) are plotted on the X and Y axes of a graph respectively, Kohli’s data point threatens to tear out of the two-dimensional surface— placed at the diametrically opposite end of the origin, many logarithmic miles away from anyone else who has played the game.

That’s not just it. While only scratching the surface of his research, Ganjoo points out in one-day run chases, Kohli scores an average of 25.5 per cent of the required runs (third on the all-time list)— for any player who bats in the top 4, that is, a parameter placed to weed out players in the lower order who score a bigger chunk of the remaining runs at the fag end of the game—from when he walks in to bat, suggestive of his ability to dominate the attack. Also, from the moment Kohli walks in to bat in a chase to when he is dismissed, the team accounts on average for 40 per cent of the chase runs (third on the all-time list), which highlights his ability to forge partnerships.

“To really understand Kohli and the game as it is played today,” says Ganjoo, “one cannot continue to ignore the principles of economics. The more we apply it, the deeper our idea of what is unfolding on the field. Baseball, for example, understood this concept very early and it has changed not just the fan’s approach to the sport but the way the game is played itself.” He’s right. Oakland Athletics’ general manager Billy Beane applied micro-economics to change his club’s fortunes and the way the game is played in America today, a story that found global appeal thanks to Michael Lewis’ book Moneyball (later made into a movie starring Brad Pitt).

In the book, Beane says ‘winning is simply a matter of figuring out the odds, and exploiting the laws of probability’. Kohli perhaps works out these odds instinctively. But only via data, vast swathes of it, do we get to enter his calculative mind and witness what he does and how he does it.

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