Against the Spin

Conventional wisdom in cricket says that taking wickets helps slow the scoring rate.  Not surprisingly, this is supported by actual data.  As the keen fan is no doubt aware, cricket is very much a game of momentum.  When a bowler is in full swing, taking wickets and bowling economically, it’s likely that the next balls and overs will be more of the same — wickets falling, and not many runs.  Similarly, when a batsman hits the first three balls of the over to the fence, you can expect some carnage off the last three as well.  Using Twenty20 data from the WorldTwenty20 and IPL available at http://data.againstthespin.com, I ran the numbers on some of these generalizations.  All of the differences you see below are highly statistically significant.

As you’d expect, the scoring rate drops the ball after a wicket is taken.  Usually there’s a new batsman trying to get his eye in, and deny the bowler the confidence boost that comes from taking two wickets in two balls.  What you may be surprised at is that the effect is so pronounced.  The scoring rate drops about 40%, from 7.0 runs per over to 5.0 runs per if a wicket fell the previous delivery.

Bowlers also turn on the pressure after a dot ball.  Batsmen score only at 6.4 runs per over the delivery after a dot ball, compared to 7.2 runs per over if they managed to score off the previous delivery — that’s a reduction of 11% in the scoring rate.  So it’s important for batsmen to keep the scoreboard ticking, and thus keep the momentum on their side.  There’s a confounding factor here, though — the ability of the bowler.  A bowler that bowls a dot ball is likely to be a good bowler, and thus already likely to have a lower economy without the effect of the dot ball.  Controlling for the bowler’s economy would make this result more meaningful.  Unfortunately I wasn’t able to do that for this analysis.  I think the results are interesting nonetheless, and I suspect this difference would still be significant after controlling for the bowler’s economy.  This same confounding factor (player’s ability) is present in all three graphs, but probably affects this one most.

It’s not only the bowlers who can pile on the pressure with dot balls and wickets.  If a batsman hits one ball for a boundary, more runs are likely to be scored off the next ball as well  — 18% more runs in fact.  The scoring rate of 6.7 runs an over when the previous ball wasn’t a four or six jumps to 7.9 runs per over following a boundary.

It would be interesting to see if these effects, particularly the post-wicket scoring reduction, linger on for several balls after the event.  But that’s a topic for a later post. If you liked this post, you can subscribe to future posts (2-3 per month) by email.

Commentators often talk about players planning out an over.  A batsmen may want to see off the first couple deliveries, and a bowler may try to keep it tight off the last ball of the over.  It is interesting to look at the actual data behind those strategies.  Using ball-by-ball data from the Against the Spin data repository, we can look at run-scoring and wicket-taking across the six deliveries of each over.

This particular analysis used all matches from the 2007 and 2009 World Twenty20 tournaments, and the 2009 IPL.  The patterns are interesting, and are largely preserved when looking at these tournaments individually.  There is some evidence that batsmen may score less of the first ball of the over, possibly trying to be cautious against the new bowler.  For their part, bowlers take some time to settle down, conceding a significantly higher number of wides & no balls of the first delivery of the over.  Batsman are also more likely to take a single of the last ball of an over, presumably in an attempt to keep the strike (graph not shown).  The error bars on the graphs represent two standard errors of the mean.

Batsmen are less likely to hit the first ball of a bowler’s over for a boundary than they are to hit subsequent balls to the fence.  They also score less off the first ball; that graph is very similar, and hence omitted here.

The third ball of an over has a higher likelihood of taking a wicket, though this may just be a statistical fluke.

This graph is perhaps the most interesting.  The average runs conceded in no balls & wides (these are the extras where the bowler is at fault) is significantly higher off the first ball of an over, compared to the middle of the over.  This suggests that bowlers may be a little tight at the beginning of an over, resulting in overstepping, or a wild delivery.

Here’s a challenge to the reader: find another publicly available cricket data source that gives you the data to build the graphs above.  I’m curious as to what’s out there, since I haven’t been able to find such a source myself.