College Football Analytics and Visualization

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28 chapters ~14 hours total 157 pages

1

Front Matter

6 chapters

• College Football Analytics and Visualization
• Preface
• Acknowledgments
• How to Use This Book
• Prerequisites
• College Football Analytics and Visualization

2

Part I: Foundations

6 chapters

• Part I: Foundations
• Chapter 1: Introduction to College Football Analytics
• Chapter 2: The Data Landscape of NCAA Football
• Chapter 3: Python for Sports Analytics
• Chapter 4: Descriptive Statistics in Football
• Chapter 5: Data Cleaning and Preparation

3

Part II: Core Metrics

7 chapters

• Part II: Core Metrics
• Chapter 6: Traditional Football Statistics
• Chapter 7: Advanced Passing Metrics
• Chapter 8: Rushing and Running Game Analysis
• Chapter 9: Defensive Metrics and Analysis
• Chapter 10: Special Teams Analytics
• Chapter 11: Efficiency Metrics (EPA, Success Rate)

4

Part III: Visualization

6 chapters

• Part III: Visualization
• Chapter 12: Fundamentals of Sports Data Visualization
• Chapter 13: Play-by-Play Visualization
• Chapter 14: Player and Team Comparison Charts
• Chapter 15: Interactive Dashboards
• Chapter 16: Spatial Analysis and Field Visualization

5

Part IV: Predictive Modeling

7 chapters

• Part IV: Predictive Modeling
• Chapter 17: Introduction to Predictive Analytics in Football
• Chapter 18: Game Outcome Prediction
• Chapter 19: Player Performance Forecasting
• Chapter 20: Recruiting Analytics
• Chapter 21: Win Probability Models
• Chapter 22: Machine Learning Applications in College Football

6

Part V: Advanced Topics

5 chapters

• Part V: Advanced Topics
• Chapter 23: Network Analysis in Football
• Chapter 24: Computer Vision and Tracking Data
• Chapter 25: Natural Language Processing for Scouting
• Chapter 26: Real-Time Analytics Systems

7

Part VI: Capstone

3 chapters

• Part VI: Capstone
• Chapter 27: Building a Complete Analytics System
• Chapter 28: Career Paths in Sports Analytics

8

Appendices

4 chapters

• Appendix A: Python Quick Reference for Sports Analytics
• Appendix B: Glossary of Terms
• Appendix C: Data Sources and APIs
• Bibliography

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