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The thesis explores the transformative impact of Fantasy Cricket platforms like Dream11 on sports engagement, focusing on how data-driven decisions shape team management. It emphasizes the significance of datasets, such as Head-to-Head Stats and Venue Records, in player selection. Using the K-Nearest Neighbors algorithm, the study identifies promising players to form a winning Dream11 team, highlighting the intersection of cricket, fantasy sports, and data analytics. The research introduces innovative methodologies and comprehensive data analysis tailored to the dynamic landscape of fantasy…mehr

Produktbeschreibung
The thesis explores the transformative impact of Fantasy Cricket platforms like Dream11 on sports engagement, focusing on how data-driven decisions shape team management. It emphasizes the significance of datasets, such as Head-to-Head Stats and Venue Records, in player selection. Using the K-Nearest Neighbors algorithm, the study identifies promising players to form a winning Dream11 team, highlighting the intersection of cricket, fantasy sports, and data analytics. The research introduces innovative methodologies and comprehensive data analysis tailored to the dynamic landscape of fantasy sports, aiming to enhance understanding and decision-making in this field.
Autorenporträt
Sukhdayal Dhanday, a Master's student in Computer Science at I.K. Gujral Punjab Technical University, specializes in sports analytics. With a focus on leveraging data insights for Fantasy Cricket platforms, Sukhdayal combines expertise in machine learning and analytics to advance strategic decision-making in sports.