Prithvi Shaw Is A Conservative T20 Bat
Prithvi Shaw is a reckless strokemaker. He slogs routinely, gets out cheaply, and is generally an unreliable batsman. As a player whose purpose is to stay in and accumulate runs, he’s reckless. But what’s he like as a hitter, and how do we measure that?
Over the past several years, I’ve tried several different ways of estimated expected runs (I call them Misbah for the batsman, and Jogi for the bowler). The system I’ve settled on considers the balls remaining, the wickets lost and the scoring rate at the start of the delivery as the factors which shape the expected runs from a delivery. For instance, if a side is 80/2 in 8 overs (or 48 balls), then what one would expect from the 49th ball would be different (higher) from what one would expect when a side is 56/2 in 8 overs. The fact that 10 an over have been scored in the first case is a signal which differs from the one which 7 an over sends. From the expected runs record, when the score is 80/2 after 48 balls, 1.20 runs are expected from the 49th, while a score of 56/2 after 48 balls suggests that 1.12 runs are expected from the 49th (the difference is roughly 0.5 runs per over)1.
The chart below gives two types of summaries for each player. The top chart gives the performance of the batsman by the over in the match. It shows how often (as a share of total balls faced) the player is likely to be on strike in a given over), and what the player is likely to produce in the terms of runs above (or below) the average expectation.
The second chart shows the player’s returns by the nth ball in the player’s innings. It also gives how often a player survives upto the nth ball (as a percentage). For example, only 46% of Shaw’s innings last upto his 15th delivery. Only 26% last upto his 25th. The corresponding figures for KL Rahul are 71% and 44%. Rahul is less likely to be dismissed than Shaw. The chart also gives what the player’s score is likely to be relative to the average expectation by the nth ball (as described in the paragraph above). The idea is to show when the speed at which the player cross the average expectation.
Seen as batsmen - as players whose role it is to stay at the wicket and accumulate runs - Shaw is clearly more reckless than Rahul. Rahul is the more cautious, more reliable batsman.
But consider it from the point of view of hitting - the art of exploiting each delivery for as many runs as possible, because there are very few deliveries available. Here, the chart shows that Rahul scores quicker than average by his 16th delivery. But he only survives upto his 16th delivery in 64% of his innings.
By contrast, Shaw produces above average runs by his 5th delivery. He survives 5 deliveries in 83% of his innings.
So, while Rahul is the more cautious batsman, Shaw is the more cautious hitter. For a batsman, the low score is the under par effort, but for the hitter, the slow score is the under par effort. The player whose game is designed to produce under par efforts less often is the more reliable, more conservative choice.
Prithvi Shaw is the more conservative choice in T20 compared to KL Rahul. His propensity to get out means that he’s unlikely to produce the headline innings of 90 in 45 balls very often. KL Rahul is more likely to produce those types of scores. Only 3% of Shaw’s T20 innings last 45 balls, while 22% of Rahul’s T20 innings last 45 balls. Assuming that some fraction of innings lasting 45 balls are blockbuster blowouts where the player strikes as 10 -12 runs per over, Rahul is more likely to produce those. But Shaw is more more likely to produce 20 in 10 than Rahul is. Or 30 in 15.
So, out of Shaw and Rahul, who’s going to provide the bread and butter above-average contribution which keeps a team competitive in a T20 match more often? The answer is Shaw.
Prithvi Shaw is a cautious T20 bat. He’s a reckless Test and ODI bat, but he’s a cautious T20 bat. KL Rahul is precisely the opposite.
An earlier version of the Jogi/Misbah rating considered only the balls remaining and the wickets lost. This meant that high scoring venues very systematically favored over lower scoring ones. The tweak described in this paragraph overcomes this difficulty.