Data Analysis on Predicting the Top 12 Fantasy Football Players by Position
Year: 2024
Type: article
Abstract: Fantasy football enthusiasts rely on rankings populated by their platform of choice to draft winning teams and make strategic roster decisions. This study presents a comprehensive analysis of player performance data to forecast the top 12 fantasy points performers per position for the upcoming season. Leveraging machine learning techniques and historical data, our model identifies key performance indicators and trends to inform player evaluations. Insights gleaned from positional trends, breakout candidates, risk assessment, and matchup analysis offer a competitive edge. By addressing limitations, ethical considerations, and avenues for future research, this study contributes to the advancement of fantasy sports analysis and enhances fan engagement with the NFL and other professional leagues.
Authors: Abadzic, Alan, Cheun, Jacquelyn, Patel, Milan
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6980903441
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