August 07, 2006 — Baseball
In 1976 statistician Herman Chernoff had the idea of representing multivariate data in figures now known as Chernoff Faces. The theory is that since we are highly practiced in the art of facial recognition, and can discern minute variations in features and expression, perhaps encoding data in a likeness of a human face would reveal things that, say, a bar graph wouldn't. And reading the diagram would, ideally, be as natural as interpreting the face of your best friend. As an example, here are some team statistics from the 2005 baseball season:
Let's depict these numbers as a series of Chernoff Faces:
For me, the Chernoff Faces have never been particularly effective or easy to read. While I can effortlessly tell how Pedro Martinez is feeling on the mound by looking at his face (on the TV broadcast), when reading Chernoff's faces I have to stop and think carefully about each one. It's not natural or easy, and usually I'd prefer a good old fashioned bar graph.
Specifically, what's wrong with Chernoff Faces? Allow me to propose that the problem lies in the un-human-ness of the stick figure drawings. They look more like bits of a breakfast cereal than a person. What's needed here are realistic human faces. And so, I humbly submit, for your consideration, Reisner faces:
Since, clearly, a more readable expression for the Mets in 2005 would be the one at right it seems I haven't done any better than Chernoff.