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Touchdowns and Data Points: A Modern Approach to Fantasy Football

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dc.contributor.author Chowdhury, Md. Kamruzzaman
dc.date.accessioned 2024-06-12T03:56:31Z
dc.date.available 2024-06-12T03:56:31Z
dc.date.issued 2024-01-22
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/12716
dc.description.abstract The study embarks on an innovative journey to integrate advanced data analytics into the world of fantasy football. Utilizing a comprehensive dataset sourced from Kaggle, which encompasses an extensive array of player statistics across 96,169 rows and 37 columns, this study delves into the dynamic and often unpredictable realm of fantasy football with a fresh, data-driven perspective. At the core of this research are various sophisticated machine learning models, including Logistic Regression, Random Forest, Gradient Boosting Machines, and Neural Networks. Each of these models was meticulously selected and applied to uncover the underlying patterns and relationships within the complex dataset. The Logistic Regression model served as a foundational approach, providing a clear, initial understanding of the data. In contrast, the more complex models like Random Forest and Gradient Boosting Machines offered deeper insights, capturing the nuanced interactions between the various variables. The study's results were impressive, demonstrating high accuracy and F1-scores across the models. However, it also highlighted areas for improvement, particularly in the models' ability to differentiate between performance categories, as evidenced by the ROC AUC scores. This insight sets the stage for future research endeavors to enhance predictive accuracy further. Ethical considerations were paramount in this study, with a strong emphasis on data privacy, fairness, and responsible use of predictive analytics. The project also recognized its environmental footprint, underscoring the importance of sustainable practices in digital and computational work. The broader societal implications of this study are significant, extending beyond fantasy football. It serves as a model for the application of data science in sports analytics, demonstrating how quantitative analysis can enrich the understanding and enjoyment of sports. Furthermore, the study contributes to the growing field of sports analytics, providing valuable insights for fantasy sports enthusiasts and professionals alike. en_US
dc.publisher Daffodil International University en_US
dc.subject Touchdowns en_US
dc.subject Data Points en_US
dc.subject Modern Approach en_US
dc.subject Fantasy Football en_US
dc.subject Neural Networks en_US
dc.subject Machine Learning en_US
dc.title Touchdowns and Data Points: A Modern Approach to Fantasy Football en_US
dc.type Other en_US


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