Bret Myers – Sports Data Science

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Bret:  My experience, I’m very knowledgeable when it comes to, the use of data in sports, in particular in soccer, which I was a former player myself.  When I played the game – I don’t want to date myself but it goes back a number of years but, these clubs weren’t really doing much with performance data but, through the rise in technology, the ability of computers to process information went much quicker and sort of opened the door to companies that can use video and kind of convert that video into data, offer it to clubs, offer a variety of platforms which they can sort of access, data and get inside as to how their team is performing and whether its, in matches or, devices that could be worn in training sessions and this is what I’ve observed in soccer, in recent years and it transcends multiple sports.  So again it’s a similar problem that, you know, other industries have, across the spectrum, of various businesses where you now have all this data that you can potentially have and so, where are the capable analysts to help take this on?  So I could kind of see this trend early and, I sort of was able to jump into the game so I have made connections as a player, and have maintained those relationships and once I started doing the research in the area, it opened the door to consulting opportunities so, in my work with major league soccer teams.  I looked at first can I help teams of a higher level of how they can create an analytics department and sort of what touch points within the club that data can be used to support decisions so that could be team player assessment, that could be opposition scouting, so preparing for the next match, that could be player recruitment so looking at other teams in your league or teams outside of your league and around the globe which is, you know, the problem in soccer and to also use, sports science methods so this is where the GPS devices could come into play or heart rate monitors in training.  So, then, once you started getting down to the lower level, this is sort of where you’re now, bringing in some of your academic methods, maybe it’s a, complex data mining problem or, regression predictive model that could be valuable to that team – that predictive model can help forecast how many wins you expect your team to have in a season or it could be used as a sort of a risk indicator but with injuries.  So there’s just a tremendous upside when it comes to the role of data in sports.

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