Nathan Leamon has come up with a new book 'The Test' © Leamon's Twitter handle
Nathan Leamon has come up with a new book ‘The Test’ © Leamon’s Twitter handle

England cricket analyst Nathan Leamon has recently written a novel ‘The Test’ which is a fictional account of a Test match where the England captain attempts to win the deciding Ashes Test. Leamon has drawn extensively from his experiences inside the England dressing room, he has been serving as a cricket analyst for England since 2009 apart from being an author.

It has been a grouse amongst cricket writers and historians that statistics employed in cricket has tended towards trivial at times and lacks coherence. The problem has been one wherein numbers are often present aplenty, but meaningful analysis has been woefully lacking on most occasions – either in on-field analytics or off-field applications of numbers related to the game, i.e., crowd behaviour, ticket pricing, tournament scheduling, financial forecasting of leagues, weather analytics etc.

Leamon has tried to venture into on-field analytics related to the game in his book and has delved into and suggested means to develop better and more evolved models for the game which could include more data points related to fielding positions, captaincy decisions, mapping of the pitch etc.

“At the moment we dig into numbers at quite a surface level. I think what you’ll see is more and more modelling of the game, which will enable you to make deeper and better inferences about the value of players,” Leamon said in an interaction with The Telegraph. “Then you can start to do some really interesting things about analysing the value of different fielding positions, the value of captaincy, and much more. Fielding is the area of the game with the biggest headroom to improve,” he added.

There is another grouse that cricket lags behind another popular and arguably similar game baseball in its use of data. Leamon has employed Monte Carlo simulations of random samples of available data to solve problems that might be deterministic in nature, e.g., probabilistic sampling on the likely percentages of winning/not winning/losing/not losing/draw in case of Tests.

In his work with England cricket, Leamon has particularly employed simulation models, wherein he breaks down the pitch into 20 blocks of 100cmX15cm, well to inform the team’s strategy regarding batsmen in the opposition and the best areas to bowl at them. There have been numerous benefits accrued by English bowlers over the years against top batsmen from around the world, particularly in Tests in English conditions.

Sachin Tendulkar had scored 1302 runs in his 13 Tests in England prior to the 2011 tour at a mightily impressive average of 62. England cricket’s analytics team including Leamon conducted a segmented analysis of where Sachin scored most runs in the initial part of his innings; an analytical tool often used in baseball. When the data set showed that Sachin scored quite less in the off-side in his initial periods at the crease, say upto 30 runs, it prompted the England bowlers to bowl more on the off-stump and around to deny scoring opportunities off the pads to the Little Master.

The strategy paid off and Tendulkar made only 273 runs in his four Tests on the 2011 tour at a relatively low average of 34.12. He scored two fifties, 56 at Trent Bridge and 91 at The Oval, and it is not that Sachin got out only on deliveries in the corridor outside off stump as perusal of match data would indicate. But the score range comparison of Tendulkar’s figures on the 2011 tour vs 1990-2007 period Tests in England show that English bowlers got him out on half the occasion for scores between 0-30 on the 2011 tour as compared to 40.90% times in the 1990-2007 period.

1990-2007 (22 innings) 2011 (8 innings)
Scores between 0-30 9 4
Scores >30 13 4

Development of models which include more match-specific parameters would go a long way in actually establishing a cause-effect relationship between results obtained in cricket and the factors behind it, as indicated by Leamon. Indeed, the question of adding significance to data analytics in cricket may be as much a mathematical conundrum as philosophical, in the final analysis, but there is no denying the fact that careful analysis does yield benefits, if applied well.