In today's information age, the use of data is becoming more and more prevalent in the sports industry. Very few organizations use analytics as extensively as professional sports. The use of this data extends widely, whether it is to evaluate player performance, their selection or injury prevention. While there remain several hurdles before data analytics is truly integrated into a professional team's core values, there is evidence that using this data can help push the team in the right direction toward success. when used correctly. Say no to plagiarism. Get a tailor-made essay on “Why violent video games should not be banned”? Get an original essay The challenge with data analysis in sports is that it is not at the forefront of management and decision-making minds. general managers who make decisions regarding players. performance-based. There is still some distrust about the usefulness of this data, especially considering that there are many different metrics to track in sports. Jim Tobin of SAS said that “teams collect massive amounts of data on player performance – more than they know what to do with” (Tobin 2). Ultimately, data will become less useful when there is too much of it, because it will be more difficult to interpret. The purpose of data is to allow sports performance analysts to tell a story that summarizes the data so that executives can make decisions based on that information. You'll be hard-pressed to find an executive or manager in professional sports who made the decision. job they have in the front office because of their passion for analytics. The demand for managers and executives is extremely high given the amount of data analyzed across different sports leagues. Compared to some large healthcare organizations, as wealthy as their owners are, they do not have the means or resources to make huge investments in technology and analytical tools, given that they place a premium on great importance to player salaries. In fact, these teams are far from having the capacity to support the infrastructure of these systems to analyze the data. “Professional sports teams are, by and large, small businesses” (Davenport 2). This means that these teams do not have the financial resources to invest in maintaining this data infrastructure. Right now, we're only scratching the surface of what this data allows us to do, although not every sports team has invested in it wholeheartedly. Many teams have used it to their advantage and experienced success in its implementation. Analyzing player performance has been proven to help decision makers determine some success on the field, but it's not relying on analysis alone that can lead to a few bad decisions. Some of the most analytical teams are the Boston Red Sox and New England Patriots, who have made a concerted effort to use data to their advantage by assessing the value of players they would like to acquire. On a smaller scale, players like Tom Brady have taken it upon themselves to become a “student of error” by using analytics to evaluate their own performance. By understanding the game at this level, he puts himself in a position to find new ways to continue his development as a player. When this is coupled with hard work off the field, it..