Tuesday 12 June 2018

The greatest ever wicket keeping batsman.

The first article that I wrote that garnered any attention was a look at Matt Prior's career as a wicket-keeper batsman, and to see how he stacked up against some of the greats: Gilchrist, Flower and Ames. It had about 200 reads, until Jarrod Kimber tweeted out a link to it, and then it had about 1000, doubling the total number of reads that my blog had had up until that point. Then there was a rain break in the England vs India test, and one of the Cricinfo commentators decided to link to the article with "here's something to look at while you wait for the rain to clear." I was swamped. About 24000 people read that article in the next 4 hours, and my little project blog became something that people started to read.

I also included a brief comparison with MS Dhoni, which got me a couple of death threats, for daring to suggest that Prior was better than Dhoni. (My favourite was "I'm going to come to England and burn your house down, you biased English." - not particularly concerning at the time, as I lived on the opposite side of the world from England).

I'm going to attempt to play with fire again, and re-look at the question.

Over the past 6 months, I've given up my job, and gone back to university to study statistics. This post is in part me attempting to use some of the tools that I've learned in that process.

One thing that comes up when discussing this, is how difficult it is to bat and keep, and if it's easier to bat with the tail, or with at the top of the order.

To try to answer those questions, I took some information for a few keepers, and had a go at running some models on them. The list of keepers that I've looked at is: Adam Gilchrist, Kumar Sangakkara, Andy Flower, Matt Prior, Brendon McCullum, Mahendra Singh Dhoni, Mushfiqur Rahim, Alec Stewart and BJ Watling. Initially, I also looked at Clyde Walcott and Les Ames, but it was difficult to get some of the information to build the models for them, so I've left them out. I'm only looking at batting. This is comparing the batting of players who kept wickets.

The variables that I looked at were as follows:
1. Average of partnerships when they came to the wicket. For example if a player came to the crease at 20/4, this was 5, if they came to the wicket at 380/2 it was 190. For opening batsmen I used 21, as this is the median opening partnership, so it is a reasonable expectation of how difficult it is to bat.
2. How many balls have passed. If the player comes to the wicket in the 51st over, it's likely to be different conditions to coming to the wicket in the 3rd over.
3. Are they the designated keeper or not. For some players, being the designated keeper hurts their batting, but for others it has the opposite effect.

I then split the data into two randomly, created the most parsimonious model that I could with half of one particular batsman's data, and then tested it on the other half of the data. I repeated this 100 times, then took the average coefficients from the 10 models that tested the best.

There are possibly better options for how to do this, but it seemed to return reasonably sensible results.

The next thing that I did was to apply those models to a number of different scenarios, some as a keeper, and some as a batsman.

That resulted in the following graph:

The answer to the question, based on these models, is quite comprehensively Andy Flower. If you're wanting to select another one, as a pure batsman Sangakkara is your man. If you want someone to bat in a crisis, then Gilchrist is the second best option, but to grind the opposition into the dust, after, Flower, you would want BJ Watling.

I quite like the idea of thinking about players based on situations, rather than overall averages. There is certainly more options that I could look at to build the model, including controlling for opposition and location. But for now this is an interesting look at a difficult problem.

No comments:

Post a Comment