Introduction to NFL Analytics with R
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By: Bradley J. Congelio
Presents an introduction to the analysis of NFL data using R. It emphasizes the use of the tidyverse in R, together with NFL-specific packages, such as nflverse, nflfastR, and nflreadr. It covers the entire sports analytics framework, including data collection, cleaning and wrangling, visualization, analysis, and advanced methods.
AI Overview
Overview of "Introduction to NFL Analytics with R" by Bradley J. Congelio
Author and Background Bradley J. Congelio is an Assistant Professor in the College of Business at Kutztown University of Pennsylvania, specializing in Data Analytics and Sport Analytics. He is the author of "Introduction to NFL Analytics with R," which was published by CRC Press in December 2023.
Key Themes
- NFL Analytics and R Programming: The book focuses on using the R programming language to analyze and visualize data related to the National Football League (NFL). It covers various aspects of NFL analytics, from basic statistical analysis to more advanced machine learning techniques.
- Investigative Inquiry: The book emphasizes the importance of investigative inquiry in data analysis, encouraging readers to delve into the data to uncover meaningful insights. It modifies the standard outline for investigative inquiry to include communicating findings effectively to the public.
- Real-World Applications: The book aims to provide practical knowledge that can be applied in real-world scenarios, such as creating robust visualizations and machine learning models for assignments or professional projects.
- Impact on Football Strategy: The book highlights how analytics has transformed football strategy, particularly referencing the Philadelphia Eagles' use of analytics in their 2017 Super Bowl win. It discusses how teams are adopting new-age analytics approaches to gain competitive advantages.
Plot Summary
The book is structured to guide readers through the process of learning NFL analytics using R. It begins with an introduction to NFL analytics and the R programming language, then moves on to practical examples of data analysis and visualization. Each chapter includes investigative inquiries that help readers develop useful insights about NFL teams and players. The book concludes by emphasizing the importance of effectively communicating these findings to the public.
Critical Reception
The book has received positive reviews from data scientists and professionals in the field:
- Data Scientist Tej Seth from SumerSports praises the book for its comprehensive coverage of NFL analytics, stating it is invaluable for both beginners and experienced data scientists.
- Data Scientist Sam Hoppen from Fantasy Pros appreciates the book's focus on coding and machine learning in sports, noting that it is great for those trying to get into these areas.
The book's approach to integrating investigative inquiry and effective communication has been well-received, making it a valuable resource for both educational and professional purposes.
Additional Information The book is available in paperback and has been featured on various media outlets, including USA Today and Sports Illustrated. Bradley Congelio's research on the impact of professional stadiums on neighboring communities has also been highlighted, showcasing his broader expertise in data analytics and sport analytics.