O.K. Jim McKay (R.I.P), I have not exactly “spanned the globe to bring a constant variety of sports” insights, but I did attend the MIT Sloan Sports Analytics conference for the first time last week and I was not disappointed! The event includes a tremendous line-up of league and team operations heavyweights, sports media personalities, authors and analytic firms doing some amazing things in the world of sports analytics.
A couple of WOW moments for me included the following:
Amazon Web Services is working with data scientists from the NFL, MLB and F1 and using the Amazon SageMaker machine learning platform to predict the probability a wide receiver will make a catch, or the probability a base runner will steal a base, or the probability a driver will overtake another race car. They are then partnering with the sports media networks to present these real-time predictive insights to fans during live broadcasts in an effort to personalize and enhance the viewing experience.
STATS.com, a leader in sports data collection, is using AI technology called AutoSTATS to collect player-tracking data directly from broadcast video, without the need for any in-venue hardware. For example, in basketball the technology can track body-pose information, such as location on the court, body position, shot form, torque, and other aspects of the game. This data can then be analyzed and used to help improve player performance or prevent player injuries.
Quite honestly, I still need to fully process these new data collection and analytic capabilities to decide if they will improve my fan experience or cross my moral line on data privacy. However, as a long-time analytics professional that is also an extreme sports enthusiast, the conference provided two days of pure excitement, thinking about the endless possibilities and applications of analytics in sports.
It was also eye opening to see the attention that eSports is getting. I attended a fantastic panel that discussed how eSports leagues work with sponsorship partners to generate insights, establish trust and identify opportunities to engage with fans. In fact, the well-known global measurement company Nielsen has recently launched an eSports division that provides objective, unprecedented insights into game and tournament viewership and fan attitudes and behaviors. Because the majority of the viewing takes place through online live streaming video platforms, the data collection and fan experience personalization opportunities are tremendous.
As you may expect, the ongoing legalization of sports betting is also ripe territory for the use of analytics in sports. I already experience this when watching Boston Celtics games, as the Linebacker sports betting tool is used to present the real-time odds of my home team winning the game. It was certainly comforting that several sessions at the conference were devoted to how to address the integrity challenges arising from betting in sports.
My only complaint about the conference was that it was painful to decide which session I would attend when 3-4 concurrent options were available. Do I listen to Malcolm Gladwell talk about the making of the modern athlete or listen to Sue Bird talk about the challenges of being an athlete in the era of social media obsession?
Maybe it’s time for the conference to introduce an analytically-driven recommendation engine that provides personalized session attendance suggestions based on my self-reported interests. This probably already exists and I just missed it.
I welcome your thoughts and comments.
Please check out www.mcguirkanalytics.com/blog-1 for additional blog posts on a variety of analytic topics. #sportsanalytics #analytics #customerexperience #eSports #AI #machinelearning