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.