About NBA Analytics Textbook

The NBA Analytics Textbook is a free, open-source educational resource designed to teach basketball analytics using R and Python. Our mission is to make the analytical skills used by NBA front offices accessible to everyone.

Our Mission

Basketball analytics has transformed how the game is played, coached, and evaluated. Yet the skills required to participate in this revolution have remained largely inaccessible to casual fans, students, and aspiring analysts.

We believe everyone should have the opportunity to learn these skills. Whether you want to work in an NBA front office, dominate your fantasy league, or simply understand the game at a deeper level, this textbook provides the foundation you need.

What Makes This Different

Dual Language Support

Every example is provided in both R and Python, allowing you to learn in your preferred language or master both.

Modern Techniques

Learn the same methods used by professional analysts, including tracking data, machine learning, and advanced metrics.

Practical Focus

Every chapter includes real-world examples, hands-on exercises, and portfolio-worthy projects.

Completely Free

No paywalls, no subscriptions, no registration required. Just open the site and start learning.

Who Is This For?

  • Aspiring Front Office Analysts - Build the portfolio and skills needed to break into professional basketball
  • Fantasy Basketball Players - Gain a data-driven edge in your leagues
  • Students & Academics - Perfect for sports analytics courses or independent research
  • Journalists & Content Creators - Learn to find and communicate data-driven stories
  • Coaches & Scouts - Understand and apply modern analytical methods
  • Basketball Fans - Deepen your appreciation and understanding of the game

Prerequisites

This textbook is designed to be accessible to beginners. You should have:

  • Basic understanding of basketball (rules, positions, common terms)
  • Willingness to learn programming (no prior experience required)
  • Access to a computer with internet connection

We start from the fundamentals and gradually build to advanced topics. If you're new to programming, Chapter 1 will guide you through setting up your environment.

Acknowledgments

This project wouldn't be possible without the incredible basketball analytics community and the creators of the data tools we use:

  • The teams behind hoopR and nba_api
  • Basketball Reference for their comprehensive data
  • The NBA for making tracking data accessible
  • Pioneers like Dean Oliver, John Hollinger, and countless others who built the field
  • Inspired by mlbanalytic.com

Contact

Have questions, suggestions, or found an error? We'd love to hear from you:

Ready to Start?

Begin your analytics journey with Chapter 1

Start Learning