In today's information age, the use of data is becoming more and more widespread in the sports industry. There are very few organizations that use analytics as extensively as professional sports. The use of this data spreads far and wide whether it is for evaluating player performance, player selection or injury prevention. While several hurdles remain before data analytics is truly integrated with the core values ​​of the professional team, it has been proven that the use of this data can help push the team in the right direction towards success if used correctly. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original Essay The challenge with data analytics in sports is that it is not at the forefront of the minds of executives and general managers who make decisions regarding players based on performance. There is still some mistrust about the usefulness of this data, especially considering that there are so many different parameters to monitor in sport. Jim Tobin of SAS stated that “teams are collecting enormous amounts of data on player performance, more than they know what to do with” (Tobin 2). Data will eventually become less useful when there is too much of it available because it is more difficult to interpret. The purpose of the data is for sports performance analysts to be able to tell a story that summarizes the data so that executives can make decisions based on this information. You will be hard pressed to find an executive or manager in professional sports who has taken over the 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 that is analyzed in various sports leagues. Compared to some of the major healthcare organizations, as wealthy as the owners are, they don't have the means or resources to make large investments in technology and analytical tools given that they place such a large focus on player salaries. In fact, these teams don't come close to being able to take care of the infrastructure of those 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 the data infrastructure. Right now, we're simply scratching the surface of what this data allows us to do, even if not all sports teams have wholeheartedly invested in it. There are many teams that have used it to their advantage and have had success with its implementation. Analysis of player performances has been proven to help decision makers determine some success on the field, but this is not done based solely on analytics which can lead to some poor 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 evaluating 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 performances. By understanding the game at this level, he puts himself in a position to find new ways to further his development as a player. When this is combined with hard work off the pitch, it allows him to reap the rewards of his tenacity. Using this data can give smaller market teams an advantage where many wouldn't see one by investing the appropriate resources into analytics. That is.