The superbowl, earthquakes, and spatial statistics

Posted on 02/04/2011 by


In anticipation of Superbowl weekend, I figured I should post a football-themed data visualization. Now, I was thinking about doing something on one of the playing teams, but my best friends are split down the middle between born-and-raised Wisconsinites (including Dan Plechaty, one of our contributors) and Pittsburgh natives. So I decided to display this graphic, courtesy of the Seattle Times:

From the Times:

During the game’s pivotal play — Marshawn Lynch‘s 67-yard touchdown run — the crowd of 66,336 cheered and jumped and stomped so vigorously that the vibrations registered like a small earthquake on a nearby seismometer.

The play:

As a continuation of some older posts, what I think is so important about this visual data is that it can show both temporal as well as spatial characteristics of a particular event.

(via Seattle Times)

Seismic data are all around us, and graphical representations of seismic movement are something we see pretty frequently without really thinking about it.  But lets look at that Seahawks data again, this time from Datapointed, one of my other favorite blogs:

(via Datapointed)

But I think this could be of use as a demonstration to social scientists. When I recall some of the more complicated political economy papers I’ve read, there is a dearth of this dual-feature thinking. Data is displayed in time-series format in a way that is sometimes efficient:

(A good visualization. Via Visualizing Economics, one of my favorite blogs ever)

…but often inadequate or unnecessarily complicated.  Unfortunately, social scientists either do not know or do not want to learn about the innovations in graphic design that allow multiple ways to represent complex data.

As I’ve said before, beyond a lack of training in graphic design, what I think is lacking in the social sciences is the ability to imagine the brain as a machine. Graphics encode data more efficiently than text because our brains are hardwired to interpret images faster than words, which are a fairly recent construct of human society (depending on who you ask, between 2.5 million to 50,000 years ago). Experiments have shown that under stress the brain can process facial emotions in milliseconds, while it takes minutes to read a text and interpret its meaning (or years if you are an English major).  If the brain can decode visual data faster, then we can encode data more efficiently in images, with overall less interference. Of course, the problem is that academia does not write for an audience that requires that efficiency, because other academics in their field can easily interpret text based on their own experiences with that data.