Monday, December 8, 2014

A Tennis Match Graphic

I know you're not thinking about tennis in December (at least those of you north of the equator). I'm generally not either. But this post is really about graphics, and I may have something that will interest you. And remember, the Australian Open and the 2015 season will soon be here.

Tennis scoring is different and tricky compared to other sports. A 2008 New York Times piece, "In Tennis, the Numbers Sometimes Don't Add Up," is apt:
If you were told that in a particular match, Player A won more points and more games and had a higher first-serve percentage, fewer unforced errors and a higher winning percentage at the net, you would deduce that Player A was the winner. But leaping to that conclusion would be a mistake. ... In tennis, it is not the events that constitute a match, but the timing of those events. In team sports like baseball, basketball and football, and even in boxing, the competitor who scores first or last may have little bearing on the outcome. In tennis, the player who scores last is always the winner.
Tricky tennis scoring makes for tricky match summarization, whether graphically or otherwise. Not that people haven't tried, with all sorts of devices in use. See, for example, another good 2014 New York Times piece, "How to Keep Score: However You Like," and the fascinating GameSetMap.com, "A blog devoted to maps about tennis," emphasizing spatial aspects but going farther on occasion.

Glenn Rudebusch and I have been working on a graphic for tennis match summarization. We have a great team of Penn undergraduate research assistants, including Bas Bergmans, Joonyup Park, Hong Teoh, and Han Tian. We don't want a graphic that keeps score per se, or a graphic that emphasizes spatial aspects. Rather, we simply want a graphic that summarizes a match's evolution, drama, and outcome. We want it to convey a wealth of information, instantaneously and intuitively, yet also to repay longer study. Hopefully we're getting close.

Here's an example, for the classic Federer-Monfils 2014 U.S. Open match. I'm not going to explain it, because it should be self-explanatory -- if it's not, we're off track. (But of course see the notes below the graph. Sorry if they're hard to read; we had to reduce the graphic to fit the blog layout.)



Does it resonate with you? How to improve it? This is version 1; we hope to post a version 2, already in the works, during the Australian open in early 2015. Again, interim suggestions are most welcome.