Scrutinizing and Executing the Positive Aspects of Big Data in World of Sports via Apache Hadoop Framework

“Big data”– which admittedly means many things to many people – is no longer confined to the realm of technology. Big data has thoughtful impact on the daily lives of consumers. Big data have successfully altered the approach businesses operate. The sports world is no longer an exception and have been benefited with the use of big data. Coaches excellently watch video to measure opponents’ skills and advance their own players’ performance, using knowledge gathered in the training room, but now they’re also using big data analytics to gain an edge. With the use of sensors, GPS trackers, and RFID, training and coaching staff can capture information, feed the data into analytical engines and use it to inspire strategic decision-making. This approach can help them choose exactly the right player for any given play: As wearables like accelerometers, heart rate monitors and other devices have become more refined and precise, coaches and trainers are using them to keep players physically fit as they train and to restrain injuries, both during training and in the heat of competition. Wearables can also permit trainers and coaches to gather more accurate data on speed, acceleration and durability during combines and tests. This can help them accumulate more operative teams and choose the most promising players at draft time. The ability to produce and study data in real time to notify replay commentary, offer game-day facts and provide up-to-date player statistics can permit broadcasters to do a healthier job of interacting with fans and keeping them well-versed. Eventually, the goal for trainers, athletes, broadcasters, coaches, and others involved in sports decision-making is to influence real-time data to advance live performance. Like smaller companies that must find an edge to compete successfully with larger enterprises, a team with a smaller budget or more limited pool of athletes can use big data and analytics to gain an advantage. In that way, big data can make sports smarter. Abstract: Big Data is a prevalent term among data analyst involved in mining huge databases to extract hidden information. Any data which poses a challenge for currently existing database technologies is termed as Big Data. Today only big giants in the different fields like sports, retail, medical, stock exchange etc., can think of handling it because of expensive and huge infrastructure involved in handling it. This research paper is based on highlighting how sports science is benefited with Big Data. Each day many international and national matches are played in different sports and with each match new records, statistics, equations, and data is generated. With the arrival of wearable devices, the data collection has become very convenient for the analysts. This data assists the team management and coach to take critical decisions like which player should be in playing team and which should be rested, deciding the positions of the players, deciding the task to be fulfilled by the player, and much more. A team game can be improved by monitoring that whether players are playing the game as a team or does there any gap persists in the flow of the play. For handling such a huge database of thousands of players, analysts make use of powerful framework like Apache Hadoop. Apache Hadoop is one such framework which is capable of handling huge databases via its several components. It makes use of Map Reduce algorithm. The central theme of the research paper is elaborating the working of Map Reduce technology and Apache Hadoop framework in handling the enormous databases relevant to sports.