Paper Key : IRJ************613
Author: Khushi Talaviya,Rushi Kamble,Satvik Nayak,Saniddhya Dubey,Dr. Hemant Gianey
Date Published: 29 Oct 2023
Abstract
The world of football is undergoing a data-driven transformation, and the demand for real-time analytics is greater than ever. This project explores the realm of real-time football analytics using Apache Spark, to enhance match analysis, engage fans, and preventing injuries. The research begins by setting clear objectives and systematically collecting data from various sources, including player tracking systems, social media platforms, and in-game statistics. The heart of the project lies in Apache Spark, a real-time data processing framework that efficiently handles vast volumes of data generated during live matches. This technology allows for data transformation, feature extraction, and the application of machine learning algorithms to provide real-time insights. User-friendly dashboards and interactive elements elevate the fan experience, offering live commentary and sentiment analysis during matches. The accuracy and effectiveness of the real-time analytics are rigorously assessed through comparisons with actual match outcomes and user feedback. By sharing research findings and methodologies, this project contributes to advancing real-time football analytics. The potential impact is profound, revolutionizing how football matches are analyzed, enhancing fan engagement, and offering invaluable insights to decision-makers in the world of football. The project underscores the power of Big Data technologies and a passion for the beautiful game in the ever-evolving landscape of football analytics.
DOI LINK : 10.56726/IRJMETS45613 https://www.doi.org/10.56726/IRJMETS45613