Analysing Analytics

While I haven't joined the course, I've been following the current Sports Information and Analytics conference presented by University of Canberra. There have been a lot of discussions and links to follow, most of which have got me thinking about analytics.

This article provides a nice definition of Analytics: the science of logical analysis. I've written about various aspects of this topic for a number of years:
There has rarely been a neater example of the extremes of analytics opinion as the recent debate centring on former NBA star, turned commentator, Charles Barkley and former non-athlete, turned NBA team GM, Daryl Morey. This debate could only happen because of the advancement in the analysis of data and the credibility that provides.

I'm not saying analysis wasn't done previously, but it didn't have the same resources. A lot of the time 'analytics' was done by the intern with the GPS devices. He was collecting a millions of points, but never had time to analyse them because he was too busy putting together powerpoint presentations for the head coach (because he was the only 'tech guy' on staff). In many cases data was collected because opponents were doing it. Data collection tools proliferated but data analysis remained largely stagnant.

This article on Tennis is great, pointing out that the barrier to advanced analytics isn't due to ability or interest, its due to the fragmented nature of the competitive calendar (compared to NBA where the same 29 venues are used for every single match of a 2,460 game (plus playoffs) season). Having said this, don't be fooled by scientific literature. Analytically minded coaches were doing very high level analytics 10+ years before anything comparable was published, and small groups in tennis are currently doing very sophisticated analysis, but aren't publishing it.

Another barrier in the development of 'analytics' was the sophistication and ease of video manipulation which started in the late 1990s.  This obsession with video analysis meant that data analysis was sidetracked for a decade.

Ultimately though, analytics became very big in sports (particularly high profile professional sports) only when huge resources were invested in it. The key difference here is not the ability to collect data, but the ability to analyse it. It is the distinction between data collection and analytics. Now there are large staffs of highly trained and educated analysts, many of whom have no sports background, who's analysis is providing insights that former athletes and coaches could never have determined with a trained eye.

(Photo Credit)


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