The Future of Sports Analytics

So often at conferences and technology meetups people ask us,  “Where is sports analytics and health analytics headed in the near future?” This typically begins a discussion about prescriptive analytics and SyncStrength. I thought it would be a good idea to bring our online community into the conversation.

It’s clear that sports analytics is in its infancy.  In many SyncStrength presentations we discuss the past, present and future of sports analytics.  The direction is shifting from the current state of descriptive & diagnostic analytics into a prescriptive analytics space.  While not a company in the sports analytics world, Netflix is a great example of a company exhibiting prescriptive analytics. Netflix does a good job of “prescribing” new television shows and movies for me to watch based on my viewing history. I take time to consider these recommendations to learn about new shows and movies. In fact, I just recently watched and enjoyed a documentary on the sneaker industry that Netflix suggested.

Even with implants, patches and ingestible sensors entering the market, we are a few years away from seeing Netflix-like smart algorithms for the individual training and health of athletes. Until then, we can think about the future trajectory of analytics in a four-phase process.  This process is similar to the trajectory that took place within business analytics and is currently taking shape in health analytics.

Four Phases of Analytics and the Questions they answer.

1)   Descriptive  – “What Happened?”

2)   Diagnostic – “Why Did It Happen?”

3)   Predictive – “What Will Happen Next?”

4)   Prescriptive – “What Should We Do?”

The four phases increase with difficulty with each phase incorporating the previous one. Descriptive analytics requires an understanding of univariate or bivariate statistics (ie. minimum, mean and maximum.) Meanwhile, prescriptive analytics requires a combination of mining big data sets, models and other heuristics to find valuable insights. Because of this, the predictive and prescriptive phases have much greater impact. Prescriptive analytics not only anticipates WHAT will happen and WHEN it will happen, but also WHY it will happen.  Thus providing information to suggest decision options on future opportunities as well as the implications of each decision option.

This will be useful in sports analytics when combining unique datasets to predict the health and performance of athletes. These unique datasets could include individualized information about nutrition, sleep patterns, training plans, game statistics, psychological health and social health just to name a few. Once the datasets get big enough the possibilities of what to include are almost endless.

What do you think? How far away are we from prescriptive analytics in sports?

Progression of Sports Analytics

Progression of Sports Analytics

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