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Automated Football Scrutiny: Algorithm and Data Structures

Aditya Krishna Singh, Aditya Tribhuvan Singh

Abstract


Analyzing a football game is a crucial task for coaches, teams, and players, and with modern technology, more and more match data is being collected. Companies now offer the ability to track the location of each player and the ball with high precision and detail. Utilizing this location data can be very beneficial. Some companies offer basic analysis such as statistics and fundamental queries. However, it is a challenging task to conduct a more advanced analysis. In our study, we are assuming we only have access to the location data of all players and the ball with high precision and detail. In this research paper, we introduce two tools. The first tool is a machine learning model that can predict the outcome of a football game based on the location data. The second tool is a visualization tool that can be used to analyze the location data and discover patterns and trends in the data. Together, these tools can help to gain a deeper understanding of a football game and make more informed decisions to improve team performance.


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References


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