ProPredict: Unlocking Sports Insights, Creating an Interactive Dashboard with Predictive Modeling Algorithms
Project Author
Issue Date
2023-05-07
Authors
Black, Liam
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First Reader
Bonham-Carter, Oliver N.
Additional Readers
Luman, Douglas J.
Keywords
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Abstract
This study introduces an intuitive sports analysis tool, ProPredict, with advanced features that offer an interactive experience for users. ProPredict is an ideal tool for both sports teams and fans seeking to conduct their own analyses of their favorite teams and players. By utilizing machine learning algorithms, ProPredict empowers users to gain valuable insights and stay ahead of the curve, enabling them to be proactive in their approach. The tool allows users to easily import their preferred datasets and generate graphs quickly to identify patterns in the data.
This thesis highlights the effectiveness of the tool in meeting its goal, providing a flexible interface that meets users' needs, while generating accurate predictions. It also sheds light on the challenges of predicting sports data, due to the complexity and external factors of sports data . The analyses show that perfect accuracy in sports data prediction is unattainable, but continued testing and tweaking of models can lead to improving results.
The study suggests that future work and testing could extend the tool's capabilities to include various sports data, leading to the development of more effective models that enable users to identify trends and answer underlying research queries. Overall, this tool is a valuable resource for sports enthusiasts and researchers, offering a versatile platform to conduct analyses and obtain findings for the future of sports.
Description
Chair
Major
Computer Science
Department
Computer Science