Big Data, Big Deal?

“What happens in matches, and what the numbers say can be very different.” – Andy Murray.

Big data using quantitative and qualitative analysis to uncover tennis play patterns has become a big deal in the tennis world. Can these analytics really help us to develop and use better tactics and strategies?

Of course we can look at data derived from matches and learn a lot about what happened by recognizing patterns, but is such knowledge useful to guide us on what to do to get the best results in future matches?

Let’s start with the idea that for such analytics to be useful they must be predictive, and to be predictive, they must be precise or repeatable and representative or accurate.

To understand the answer to the above questions here are a few definitions that are relevant to addressing this complex concept.

1. Chaos Theory is a part of math that deals with the complex systems in which behavior is highly sensitive to conditions which make it move from order to disorder. Mike Tyson described it well when he said, “everyone has a plan until they get punched in the face.”
2. The Butterfly Effect is a part of chaos theory in which a tiny local change in a complex system can have large effects elsewhere. So if I come to the net eight times in a match and win six points, I win 75 percent of those points and that’s great, so maybe I should come in more? Well, the Butterfly Effect would suggest that by even coming in just 16 times total I change the dynamics in such a way that now my opponent is ready for my new strategy and thus I win only four of the 16 points, or 25 percent.3.
3. Game Theory is that part of math focused on analysis of strategies in competitive situations where the outcome of one participant’s actions depends greatly on the actions of the other participants. Tennis can be seen as one big game of Rock, Paper, Scissors in which we formalize If/Then statements.

So data can get skewed easily and that’s just a part of this issue because what transforms data into analytics is interpretation, which is highly subjective and only as good as the coach performing the process. Still, a good coach can find value in numbers, but as the old saying goes, “statistics are like a bikini: what they reveal is important, but what they conceal is vital.”

So to put all this together let’s consider the song by One Direction, “You Don’t Know You’re Beautiful”. The lyrics tell a girl “you don’t know you’re beautiful, that’s what makes you beautiful.” Of course if she believes what is told to her, she now knows she is beautiful and according to the lyrics, this self awareness makes her no longer beautiful. And since she now knows she can no longer be beautiful, she is thus beautiful again in this never ending cycle of interdependent cause and effect.

We can simplify big data as a popular website, Brain Game Tennis, attempts to do as it tries to find play patterns with profound meaning in chaos. However, without recognizing the principles of causation, the conclusions we reach are too simple to solve the complex issue of how to predict future patterns and prepare with a better plan of action.

I think that Andy Murray is right that the numbers don’t always reflect play because they don’t travel in only one direction.