Visualising cricket - an alternative to the worm?

Cricket is a great game for statisticians. I think this is because of the structured nature to the game. Like baseball, well known for its stats, the play is broken into discrete units, each with a finite number of outcomes. Balls and overs act as natural denominators for many metrics such as:

• Run rate - the mean runs per over of the batting side
• Strike rate - the mean number of balls a bowler needs to take a wicket
• Economy - the mean number of runs given away by a bowler per over.

Unlike baseball however, some would say that the statistics used in cricket are not as helpful as they could be. A bowler's strike rate, for instance, very much depends on the quality of the batters that they are up against. With this in mind I set myself the challenge of seeing if I could improve upon one of the key visualisations used to describe a cricket match - the worm.

The worm shows the cumulative runs scored by each team across the overs in the game. In a recent One Day International (50 over game) between England and Pakistan, the worm looked like this:

Pakistan batted first and scored 247, by today's standards a fairly low score. The worm reveals that England were able to stay ahead of Pakistan's position at the same point in the game throughout their innings, winning with around three overs to spare.

But is that the whole story? The worm doesn't show a crucial part of the equation, which is wickets in hand (the number of batters still available to the batting team minus one). After a given number of overs, a team could be well ahead in terms of the number of runs they have relative to the other team at the same point of their innings. However, if they've lost nine wickets, you would not expect them to score many more. A quick 100 all out from 10 overs, does not beat a slow 200 from all 50 overs.

In my attempt to improve on the worm, I've focused on the second innings. Is there a better way to show how the team batting second is doing in their run chase? Are they looking like they are going to win or lose? To do this I've enlisted the help of the famed Duckworth Lewis Method.

Duckworth Lewis is a calculation that is used for interrupted cricket matches to determine whether the score the team batting second has reached is a winning score at that point in the game. Crucially, it takes into account how many wickets the batting team have remaining.

I've plotted the net position of England against the Duckworth Lewis target at the end of each over of their innings. If England are ahead of that target then they're on track to win. If they're behind then they need to turn things around. This approach reveals a very different interpretation of the game:

For the first 15 overs England were not doing well. They lost too many wickets to be in a winning position, even though they were just ahead of Pakistan's score at the same point in the innings. A strong partnership between Ben Stokes and Jonny Bairstow was key to turning the game around, allowing England to cruise for the last 15 overs.

Personally, I think this second chart tells a much more interesting story about the match. The feeling of momentum swinging from one team to the other is key to enjoying cricket and I think this comes across strongly.

I'm interested to hear your thoughts? If you're a cricket fan (or a fan of another sport) is there a visualisation you love? Are there any you hate? What do you think of mine?