Analyzing and Exploring the Impact of Big Data Analytics in Sports Sector

Big data are the first-ever use of data and statistics enabling us to make effective decisions in professional sports. The primary focus of the research paper is to evaluate how the use of big data has benefited sports. The research work conducted in the paper focuses on extracting information from the constructed database as per user requirements. Two different databases have been constructed by gathering data from espncricinfo.com. The first database consists of the records of batsmen comprising 16 attributes relevant to the international career of the batsmen. The second database contains records of bowlers involving 18 attributes relevant to the international career of the bowlers. The research paper encompasses a detailed flowchart and an algorithm detailing the systematic approach followed to mine required data from the database. The research has been conducted focusing to come up with a user-friendly tool that would offer optimal results via simplified scripts and queries in tabular and visualization form. The research enables any cricket fan or a layman to mine the information in which he/she is interested. The research paper elaborates on the use of the Hortonworks Hue 2.2.0 framework in analyzing the gathered data and extracting information via appropriate tools of the framework as per need. The screenshots included in the research work enable the general masses to have insight into the workflow of the conducted research and to gain a better understanding of performing different functions on different tools. As compared to past research, the research work does not make use of any statistical tools which are difficult to understand and work upon. The constructed database is made available to the framework and the queries and scripts are formatted to get results in tabular and graphical form. The research work enables coaches and instructors to select the best batsmen and outstanding bowlers to construct a strong team via mining the relevant databases and come out with the best outcome. The research work even enables general masses to build their teams after analyzing the past performance of different batsmen and bowlers and construct their teams and participate in fantasy gaming platforms like Dream11, MyTeam11, Howzat, etc. The research paper illustrates the work conducted on sentiment analysis using Python and Java programming languages to predict the popularity of batsmen or bowlers via word cloud to get a deep insight into the public opinion regarding upcoming tournaments based on past performances of the players and the teams. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.