In Today’s world, immerging businesses across all different industries have found it extremely beneficial to collect massive amounts of data. In doing so, businesses are able to use Big Data and analytics to develop strategic plans that evolve their companies and maximize their profits. One industry where this is specifically relevant is sports.
Today, in most professional sports, you can find a camera almost anywhere on the field. In the stands, you can find scouts recording every move a player makes. Even a player’s free time is recorded; what they’re eating, how they’re sleeping, and their exercise routines are all evaluated. All of this data is collected by organizations, critically assessed, and then molded into a strategic plan to improve a players speed, skill, strength and value.
With sports organizations collecting Big Data and improving their analytic strategies, I believe they will find themselves saving millions of dollars on contracts and trades, as these methods basically eliminate the risk that a player they are looking at will not preform up to the standard they were valued at. Collecting Big data not only limits the amount of risk an organization faces when signing a player, it also helps organizations improve a player’s overall skill and value. Players and coaches can closely evaluate every move a potential prospect makes at practice and in games, find problems in their performance, and plan how they can improve on these weaknesses. As coaches use this data to improve their player, I believe that in the future, organizations will begin producing athletes that can preform at a much level than athletes today. Ultimately, improving the overall quality and value of the organization.
Though Big Data in Sports is very beneficial for organizations, many players argue that these analytics do not give the whole story and are not always correct. For example, When the LA Lakers were considering signing Kobe Bryant, 35, who was coming back from an Achilles tear, if they had just gone by the data of past injuries and players his age, the organization would have come to the simple conclusion that he was not worth it. However, Bryant disagreed. He insisted the data was wrong and was eventually signed. This signing proved to be a huge fail for the Lakers and ended up being a $48 million mistake.
In conclusion, I agree that “Big Data” and analytics are very beneficial to any organization within any industry, especially the sports industry. In the sports industry, Analytics play a special role because without these statistics no player, team, or origination could be given a value or be evaluated based on skill. Sports organizations are reliant on this “Big Data” and I believe that in the future, as innovative technology continues to progress, collecting “Big Data” will ultimately become a necessary tool to improve, grow, and expand any organization, within the sports industry and all industries.
Marr, Bernard. "Big Data: The Winning Formula in Sports." Forbes. Forbes Magazine, 25 Mar. 2015. Web. 15 Sept. 2016.