Earlier this month I blogged about how the loss of wickets shifts the chances of victory and the number of runs scored in the remainder of the innings. In this post, I’m delving into how the speed of a team’s scoring effects their chances of losing wickets.
In an ideal world we would have ball-by-ball data which would include data on what sort of shots players attempt, and I would expect you would see a trend where batsmen attempting a lot of aggressive batting (whether or not those shots turn into runs) would be at a higher risk of losing their wicket. Unfortunately we don’t have that data, so we can only rely on the total number of runs scored, and the number of wickets lost, in each over.
I have to make a few assumptions here:
- Teams don’t dramatically change their batting behaviour from over to over, particularly if a wicket hasn’t been lost. So if a team is batting in a risky manner in one over and this results in the team losing a wicket, they would be more likely to have been batting in a similar way in the previous over.
- There is a correlation between batting in a more risky way, and scoring more runs. So while we don’t have enough data to actually categorise play according to risk, we can use the run rate immediately before the loss of the wicket as a proxy.
I have over-by-over data for just over 4000 men’s Twenty20 matches.
Firstly, let’s look at every over in the data set (excluding the first over of each innings), and the number of runs scored in the previous over, to identify how many of those overs resulted in the loss of a wicket.