The cricketer’s new face

Ever wondered if cricket data can be “visually” represented? Here’s a look at how Chernoff faces can do so.

While browsing the Internet for innovative statistical analysis in sport, I stumbled upon an April 2008 article in the New York Times, titled “Professor puts a face on the performance of baseball managers”.

I was pleasantly surprised because we had done something very similar – and a year earlier – during the 2007 Cricket World Cup. We had put a face on the performance of cricketers!

It is common knowledge that while looking at huge multivariate data sets – such as cricket data sets – it is not easy to quickly identify similar and dissimilar data subsets. Looking at the data, can we say if it is related to a batsman or an all-rounder? Or, looking at the data of two batsmen, can we say who is performing better?

One particularly elegant idea, first employed by Chernoff, is to use cartoon faces to represent many variables. This graphical tool works because the human eye finds it easier to spot similarities between faces, rather than cold data sets.

We used Chernoff faces, using the SYSTAT software, to depict the most valuable players of the 2007 Cricket World Cup featuring over 200 cricketers.

We created Chernoff faces for each player based on the following assignment of variables to facial features:

Here are the Chernoff faces of the nine most valuable players of the 2007 World Cup.




If a layman sees these faces, he will discover that “Matthew Hayden” and “Ricky Ponting” have striking similarities. Both have rounded faces, wide noses and big smiles, although “Hayden” is smiling a little more.

 If we now look at our variable assignments we see that the smile is because the number of runs is linked to curvature of the mouth (variable 1); the wide nose is because the number of runs is also linked to the width of the nose (variable 3). So both “Hayden” and “Ponting” have offered immense value as batsmen, although Hayden’s wider smile suggests a slightly greater batting value (659 runs at a strike rate of 101.1, in comparison to Ponting with 539 runs at a strike rate of 95.4).

If we continue looking, we’ll find that “Hayden” and “Hogg” are very dissimilar. Hogg has no smile (didn’t score runs), and has a tall, thin nose. Hogg also has massive ears and a tapered face. Hogg’s tall nose (variable 4) and big ears (variable 19) suggests that he has taken a lot of wickets (21). This is further confirmed by Hogg’s tapered face (imagine that the face is made up of an upper and lower ellipse) because wickets are linked to the eccentricity of the ellipses (variables 16, 17).

We also discover that “McGrath” is very similar to “Hogg” (26 and 21 wickets respectively).

Next, we find a lot of similarity between “Jayasuriya” and Styris”. This duo looks slightly different from “Hayden” – in comparison, they have a taller nose and bigger ears – but sufficiently dissimilar to “Hogg”. We guess – correctly – that they are batting all-rounders.

Finally, don’t be surprised by Jayasuriya’s big eyes. He was responsible for quite a few run outs (variables 10, 11).