'Real-Time Does Have Benefits Over Data Logging' In Sports

We sat down with Robert Sorenson, Founder at Litespeed


Robert Sorenson is the founder of Litespeed.co based in Park City, Utah (USA). He comes from the business side of data analytics enablement working with retail, loyalty and programmatic ad data. He has worked with leading retailers in the USA and is currently working on a project with Coles and their flybuys loyalty program. While doing a side project, Robert serendipitously walked into sports analytics. As a result, he has pushed athlete and equipment data collection to a new level in a blend of blue skies research and finding data applicability that benefits athletes and sports.

Ahead of his presentation at the Sports Analytics Innovation Summit this March 8-9 in Melbourne, we sat down with Robert to discuss sports analytics and the challenges in sports that don't necessarily lend themselves to analytics.

What, in your view, were the defining sports analytics trends of last year?

My background is in BI and data analytics, but in the retail, loyalty and programmatic marketing side. I haven’t been around long enough in sports analytics to properly discern the trends. However, I can see parallels emerging similar to what business is going through in dealing with the vast amounts of data.

Everyone is resolved to use and understand data to better enable sports in a number of different fronts. The technology to generate and acquire data is coming along quite well, but I think this will continue to evolve over the next 10 years. Nevertheless, data is being generated at a healthy pace. Where issues have surfaced on the business side is the technology and data side of the equation has matured much faster than the organizational side can absorb it. Specifically, people and processes globally have not moved at the same pace to truly use and benefit from it.

With the incredible amount of data available to analytics teams in modern sport, how can analysts identify which metrics are important?

I started in an area of more non-traditional sports such as speed skating, skiing and surfing. These sports have three facets to overall performance: athlete fitness, technique and equipment choice and setup. Each one of these contributes to the data in their own way and untangling, for example, whether an athlete has a technique deficit or poor equipment choice or setup is incredibly difficult.

These sports have no hard and fast rules and the parts discussed reside to some degree or another in tribal and experiential knowledge. Decisions are made based more on gut feel and the quality of relationship between the athlete and coach.

Using data to find that extra bit of performance, correct the right problems and measure ongoing progress is going to be the most difficult aspect sports analytics will face. As exciting as it was to first get the data, the unexpected realization of how to build an effective collaborative framework to use it is a daunting challenge.

In what ways has the explosion of data analytics affected speed skating in particular? Do you think some sports lend themselves to analytics more readily than others?

Speed skating lacks data. It has only been a year since I started acquiring and analyzing the data and you can characterize the people I work with as early adopters. The most serious attempts at analytics in speed skating in the past was with video, but video is too coarse grained for the complexity and dynamism of skating and didn’t yield much of anything.

I do believe some sports will lend themselves better to analytics than others. For example, in speed skating and skiing the technique differences between a top winning athlete and one that is almost there, but can never hit the next level is incredibly subtle, if not impossible to pinpoint visually.

Is it important that data analysis in sports be delivered in real-time?

I collect data wirelessly in real-time, but don’t necessarily need to at the stage I am at. However, real-time does have benefits over data logging in that I know during data acquisition if all is going well. I have yet to experience a test session with an athlete where I failed to collect data.

Who are you most looking forward to hearing from at the summit?

I am more interested in hearing from everyone and what they are doing. Listening to the wide range of ideas will be incredibly valuable because it could be something I can bring to the work I am doing.

You can hear more from Robert, as well as many other industry leading sports analytics practitioners, at the Sports Analytics Innovation Summit, this March 8-9 in Melbourne. To see the full schedule, click here.

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