Data Analytics in Football Sport to Identify Gaps For the Improvement of Quality Opportunities Throughout World-Wide Teams
Syed Ali Fathima S J1, Sumathi V P2, Sumanth S3
1Syed Ali Fathima S J, Assistant Professor, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
2Sumathi V P, Assistant Professor, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
3Sumanth S, UG Scholar, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 15 December 2018 | Revised Manuscript received on 27 December 2018 | Manuscript Published on 24 January 2019 | PP: 364-368 | Volume-7 Issue-4S2 December 2018 | Retrieval Number: ES2081017518/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Football is a widely known sport. Billions watch and play the game around the world. Data Analytics has assumed a huge role in the world of Football. It has transformed how people approach games, team formation, player selection etc. Data analytics has enabled teams from around the world to understand their game better and perform better. Data analytics is also used to predict the outcomes of games enabling people to make educated guesses while betting. There is no doubt that Football is worldwide sport. However, there are so many teams worldwide who haven’t improved when compared to some of the others. Few teams don’t even manage to make into the main tournaments like FIFA. Some countries lack funding and some teams don’t have the exposure to standard equipment, coaching opportunities etc. It is very important for a Football enthusiast to know that the game keeps evolving towards a point where there are more quality teams around the world. It is very important for data analytics to move into this direction of finding answers to the question “What can be done to provide quality opportunities to the teams worldwide?”. The present paper discusses exactly that and looks to provide an answer to that very question.
Keywords: Data Analytics, Football, Pandas, Players, Python, Sports, Statistics.
Scope of the Article: Data Analytics