IPL 2019

Deciphering bowlers in IPL with contextual stats

by Himanish Ganjoo • Last updated on

Ngidi was arguably CSK's most valuable cog during the 2018 IPL season © BCCI

With the advent of T20, number nerds, teams and players have awakened to the importance of adding context to conventional cricket stats, that do not tell the full story, especially in the 120-ball format where strategies are vastly different from ODIs. For instance, an economy rate of 8 runs per over is high, but not if you consider a bowler who only bowls at the death. There is a need to integrate this information into our numbers.

How do we go about that?

We look at the average rate of conceding runs in each over of a T20 innings. We break a bowler's stats to look at his economy rate in different overs. We then scale his economy rate by the "average" economy rate in each over. This helps us establish a baseline for conceding runs in each over.

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This method divides performances by overs, all of which have different contexts due to being at different times in an innings. It then includes that context and presents a run-saving value for each over.

For instance, here are the run saving values for Jasprit Bumrah in IPL 2018:

We can see that in overs 18-20, Bumrah's economy is 39%, 10% and 3% better than the par scoring rate in those overs ©Cricbuzz

Whatever his economy rate overall, this graph splits it up over by over. We can see that in overs 18-20, his economy is 39%, 10% and 3% better than the par scoring rate in those overs.

We know he's a brilliant death bowler, but these numbers actually tell you how economical he is while taking into account the high scoring rates at the death.

We have successfully included some context. We also see his value in the late Powerplay overs, and the middle overs, where he is much more economical compared to expectations.

Doing this for each bowler can be a data-heavy exercise, and we might want to find a sort of "average" run-saving value for each player: a single number that tells us how miserly a bowler is, including the context of the overs he bowls. This, for example, tells us the true value of a death bowler who might have a higher economy rate.

In fact, we can apply the same machinery to wicket-taking rates as well. The only difference is that now, we consider bowling strike rates instead of economy. In the end, we get a wicket-taking value for each bowler.

These two values combined tell us how miserly a bowler is, and how much striking ability he has. And the good thing is, these numbers include information about context, which is invisible in conventional statistics.

Let's look at this graph for all IPL seasons from 2014 to 2018:

Rashid is 23% more likely to take wickets, and has a 20% better economy, compared to others ©Cricbuzz

Andrew Tye and Rashid Khan are established as legends (if that needed any proof) Rashid is 23% more likely to take wickets, and has a 20% better economy, compared to others. Tye bowls at the death, where wickets are known to fall more frequently, but still has a 40% better strike rate compared to the par.

A host of Indian medium pacers populate the ignominious lower-left quadrant, which means they are profligate and less threatening.

Dwayne Bravo's death bowling sees him in the upper left quadrant, which means he saves runs given the situations he bowls in, but does not strike as often as the average bowler does.

The same is the case with Bumrah as the data shows him to be a very economical, non-wicket taking bowler. More on this later.

Splitting open bowling performances this way illuminates the exact roles of individual bowlers better. To analyse more recent performances, let us look at the same graph for IPL 2018 only:

Lungi Ngidi stands out like a Bradmanesque outlier, about 70% more likely to take wickets given the situation ©Cricbuzz

Let's take the top right quadrant first, which has bowlers who save runs and take wickets at the same time.

First up, Lungi Ngidi stands out like a Bradmanesque outlier, about 70% more likely to take wickets given the situation, and about 40% more economical. These qualities, with the tough job profile of bowling at the death, made him the most valuable cog of CSK's win in 2018. He will be missed, and these numbers show how much.

His companions in this aspect are two usual suspects: Tye and Rashid. Krunal Pandya is immensely valuable for Mumbai as a 4th bowler: 10% more economical than the par, and 10% more likely to pick up wickets.

Jofra Archer is proven to be a bright spot in a mostly forgettable campaign for the Royals.

Significantly, it seems like teams have figured out a strategy to keep Sunil Narine out. He is in the positive region, but very close to the center, which means that teams play him out quietly, not losing too many wickets to him in the middle overs.

Most telling are the positions of India's premier white ball spinners. Kuldeep Yadav is the perfect wrist spinner: slightly expensive, but also a strike weapon. On the other hand, Chahal's role has changed: he contains the run flow much better, but takes wickets at the expected rate. This in itself is a great achievement, given that he bowls half his overs at the batting-friendly Chinnaswamy.

Finally, India's pace bowling hopes for the upcoming World Cup, Bumrah and Bhuvneshwar are at the top left, which means they are stellar at saving runs (remember, they bowl at the death), but cannot take wickets as often as the average bowler does. This is not as bad as it looks, because batsmen are unable to hit them in the slog overs, leading to fewer outfield catches. They are so good that batsmen can't even take risks against them.

© Cricbuzz

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