If you’ve watched my MIT Sports Analytics presentation video (you can watch it on the video page here too) you’ll remember the three main challenges that leading franchises are trying to tackle… Width, Depth, and Speed.
Width in this context is the concept of data diversity. Width describes the desire to incorporate many different data perspectives together. Sports data sets have started to go beyond strictly the game data and into the areas of psychology, physiology, salary cap data, biology, etc. It is the desire to use these sets of data together in an integrated way that is challenging the top franchises in sport. This is not an easy problem to solve and teams have learned the hard way over the years that interns aren’t able to accomplish. It takes someone with technical experience to get it done.
Depth in this context is the concept of increasing data detail. As time has gone by and data driven analysis has started to gain a toe hold in the sports world, there has been a growing desire for more data. This has been particularly painful with the advent of the tracking systems in baseball, soccer, and basketball that track player and ball movements many times a second and generate corresponding large amounts of data. It is this mechanically generated data that is becoming a challenge for franchises both in methods of managing it and analyzing it.
The leading analytic franchises are looking to shorten the time that it takes to acquire, process, analyze, and show analytical results with which to base decisions. This speed is important to get the answers you need before your competitor and perhaps be able to use this information during matches as game play is occurring.
As you might imagine, tackling these three areas is a very challenging endeavor, but those that choose to tackle them and are successful will have an advantage over their competitors.