Thursday, September 15, 2016

Big Data: The Winning Formula in Sports

According to Bernard Marr, author of Big Data: The Winning Formula in Sports, the landscape of sports is changing rapidly and will continue to evolve as big data analytics continues to grow. Made famous by the film Moneyball, the use of data in sports, refered to as sabermetrics has changed the way players, managers and owners view their respected sports. Since Billy Beane, the star of Moneyball revolutionized the sports industry, data has a more widespread use in sports. Data in sports was originally used to track on field performance and acquire players whose stats provided the greatest value to their team. In this article, Marr describes the various different ways big data analytics influences sports including injury prevention, off field tendencies, and fan interaction.

After seeing Moneyball I knew big data was prevalent in sports, but I had no idea to the extent of which it was being used. Players are essentially extremely high priced assets in the eyes of their owners, and data analytics allow teams are now able to monitor their players at all times. Injuries are a huge part of sports and can not only affect the on field product, but also the revenue and bottom line of the team as a business. Players now wear devices that track how their body reacts to the vigourous training they endure. I believe this will become an essential function of every team throughout sports. With the data these devices collect, coaches should be able to know when players are most susceptible to injury and in turn can know when to shut them down to recover. I also found it intriguing that teams are keeping data on their players away from the facilities, including players eating, sleeping and recovery habits. This can help in various ways, for example, if the data suggests that a player had a good night sleep, then they are more likely to perform at a higher level. A fascinating aspect of data analytics in sports is how it goes beyond the players and to the fans.

Teams have begun collecting data on fans and their watching and purchasing habits. I believe companies should continue to invest in data analytics based on fans’ social media presence. This could allow teams to see which of their players are being talked about most frequently and in turn teams can market the given player and their merchandise more prominently. Also with streaming services such as Facebook Live becoming more popular, fans are now able to watch their team's’ games on social media. If teams have data on their fans social media presence, they could be better informed whether they should pursue the various live streaming possibilities.

Pundits in the sports world will argue that big data analytics takes away from the fundamental principles of the sport, but the reality is the stakes are so high in the business of sports that teams have no choice but to implement data analytics in some capacity to better their franchise.



Source: http://www.forbes.com/sites/bernardmarr/2015/03/25/big-data-the-winning-formula-in-sports/2/#228d607913be

1 comment:

  1. Kris' explanation and analysis of his article has provided us with two unique ways that sports franchises are using big data analytics. As he touched on, most people have seen "Money Ball" and are familiar with the way Billy Bean took statistical analysis and was able to change the way the Oakland A's played the game of baseball. Since then, teams all around the world (including the Baltimore Orioels thanks to Loyola's own Econ instructor, Professor Walters) are implementing various forms of data and statistical analysis into their overall strategy on everything from player acquisitions to how many kegs of beer they should order.

    One aspect of Kris’ explanation that I thought was extremely interesting and highly prevalent in todays digital age was the way organizations are using the data of not only players, but of fans as well. Just like the stockholders of a company, the fans are the way a team keeps making money year after year. From merchandize and ticket sales to tuning into the game from your living room or favorite corner bar, the revenue teams recognize from their devoted followers are what makes the big business of professional sports run. The way they are using social media to see how fans are interacting with their brand will give them great insight into various aspects of the game day operation. They will have granular insight into the fan experience inside the stadium, as well as from wherever else they may be watching. While they will be inundated with frustrated fans on days the team doesn’t do well, the benefits of this information definitely the negatives.

    It will definitely be interesting to see how the use of big data analytics evolves over the coming years. There is a clear upside in terms of the business information teams will garner from their fans. While Bean and the A’s were successful in building a contender in Oakland, one must ask if this analytics practice will translate to other sports. Being a Cleveland Browns fan, many of us were shocked when the front office hired notable Money Ball character Paul DePodesta to be the teams new Chief Strategy Officer. He along with Sashi Brown announced the Browns organization would begin to put an emphasis on analytics, when considering future draft picks and free agent signings. It’s too early to make a judgment just yet, but I wait with baited breath to see if these new data analytics strategies will finally bring the Lombardi Trophy to my hometown.

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