Super-specialisation in cricket

Cricket has always been a reasonably specialised sport. You are either a batsman or a bowler or a wicketkeeper or an all-rounder. If you’re a bowler, you’re classified based on your bowling arm and the speed at which you bowl and the spin you impart the ball (last two are not independent). If you’re a batsman you’re classified based on your batting stance and whether you’re an opener or a middle-order batsman.

In Test cricket, there’s further specialisation if you’re a middle-order batsman. You have specialist Number Threes, like Rahul Dravid or Ricky Ponting. You have specialist Number Fours, like Sachin Tendulkar or Younis Khan. Five and six are fungible, but a required ability for both these positions is the ability to bat with the tail.

In One Day cricket, too, there’s some degree of specialisation within the middle order but it’s not to the same extent as in Test Cricket. In One Day cricket, batting orders are more flexible and situation-based. You do have specialist threes (Dravid and Ponting again come to mind) and sixes (usually hitters) but the super-specialisation is not as much as in Test Cricket.

A logical extension of this would be that in T20 cricket, which is played over an even shorter duration and where batting orders are even more flexible, you don’t need even as much of specialisation as in ODIs. However, Siddharth Monga argues in this piece that this lack of specialisation is why India isn’t doing as well as it could in T20s (having just lost the home series to South Africa).

In other words, what Monga is arguing is that Kohli, Raina and Sharma are all similar batsmen and effectively Number Threes for their IPL franchises, and when they are arranged 2-4 or 3-5 in the Indian national team, two of them are effectively batting out of position.

It would be interesting if Monga is indeed right and that T20s require a higher degree of specialisation than ODIs. It is also interesting that India’s number 6, MS Dhoni, bats like a typical number 5 in T20s, accumulating for a while before going bonkers. Maybe T20 will end up as a much more specialised sport than Tests? That would be interesting to watch.

The pressure of chasing a target in One Day Internationals

I was looking at the average runs scored per over in One Day Internationals from 2009 onwards (data from cricsheet ). The data is presented in the graph below. What is striking is the difference in runs scored per over between the team batting first and second.




The  blue line shows the runs per over for the team batting first, and the red line for the team batting second. These figures are averaged over all ODIs from 2009 till the end of the recent Asia Cup. What you will notice is that the way you score runs in the first and second innings is different.

For the first part of the innings, till almost over 35, the team batting second scores much faster than the team batting first. Then somewhere around over 40, the two lines cross, And then the blue line pulls away from the red one – and really fast.

In the last over of the innings, for example, the team batting first is expected to score ten runs, while the team batting second is expected to score only eight and a half. In the forty fifth over, the team batting first scores seven runs on an average, while the chasing team only scores six!

The difference in scoring patterns is striking, and the only possible explanation is the pressure of chasing! When you have a target in mind, and you are chasing, you are unable to bat as freely as you do when you are setting a target. Consequently, you are not able to score as many runs!

The next question is if there is a variation across teams. Given below is the same graph as above, but plotted by batting team.




The graphs are smaller, so the gaps aren’t too visible, but if you look for a gap between the blue and red lines by team, you will find that the biggest gaps are for India, New Zealand and Australia! Sri Lanka and Pakistan seem to bat similarly, however, irrespective of whether they are setting a target or chasing!



Sehwag versus Tendulkar

Though he hasn’t formally retired yet, given that he is hopelessly out of form, one can probably conclude that Virender Sehwag is unlikely to play for India again, and hence it is time to pay tribute.

I have developed a little visualization where I plot the trajectories of a batsman’s innings based on his past records. There are basically two plots – in the first, I track the expected number of runs he would have scored as a function of the number of balls he has faced. In the second, I plot the probability of the batsman still batting as a function of the number of balls faced.

I’ve created an interactive visualization using the Shiny Server plugin for R, on a little Digital Ocean server that I’ve leased. In this application, you can compare the innings trajectories of different players in different formats. I have taken my raw ball by ball data for this application from cricsheet and have analyzed and visualized the data using R.

Having built this “app”, I was playing around with random combinations of players and formats, and soon started comparing Sachin Tendulkar with Virender Sehwag. Medium-timers like me might remember that back when Sehwag started out in the early 2000s, he was called “the clone” for his batting style was extremely similar to that of Sachin Tendulkar. That they are both short and chubby also helped fuel this comparison. One thing that sets Sehwag apart, though, is his sheer pace of scoring, especially in Test matches.

So while playing around with the “app”, when I loaded Sehwag and Tendulkar together, I noticed one interesting thing – Sehwag in Test matches plays exactly like how Tendulkar plays in ODIs, and Sehwag in ODIs plays like Tendulkar does in T20s (data includes IPL  games). Check out the graphs for yourselves!




I’m not sure how much load my small server can take so I’m not putting the link to the app here. However, if you think you’ll find this interesting and will want to play with it, write to me and I’ll send you the link.