The Sports Betting Textbook

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42 chapters ~63 hours total 322 pages

1

Frontmatter

6 chapters

• The Sports Betting Textbook
• Preface
• Acknowledgments
• How to Use This Book
• Prerequisites
• About the Author

2

Part I: Foundations of Sports Betting

6 chapters

• Part I: Foundations of Sports Betting
• Chapter 1: Introduction to Sports Betting
• Chapter 2: Probability and Odds
• Chapter 3: Expected Value and the Bettor's Edge
• Chapter 4: Bankroll Management Fundamentals
• Chapter 5: Data Literacy for Bettors

3

Part II: Statistical Foundations

6 chapters

• Part II: Statistical Foundations for Sports Betting
• Chapter 6: Descriptive Statistics for Sports
• Chapter 7: Probability Distributions in Betting
• Chapter 8: Hypothesis Testing and Statistical Significance
• Chapter 9: Regression Analysis for Sports Modeling
• Chapter 10: Bayesian Thinking for Bettors

4

Part III: The Betting Marketplace

5 chapters

• Part III: The Betting Marketplace
• Chapter 11: Understanding Betting Markets
• Chapter 12: Line Shopping and Market Analysis
• Chapter 13: Value Betting Theory and Practice
• Chapter 14: Advanced Bankroll and Staking Strategies

5

Part IV: Sport-Specific Modeling

9 chapters

• Part IV: Sport-Specific Modeling
• Chapter 15: Modeling the NFL
• Chapter 16: Modeling the NBA
• Chapter 17: Modeling MLB
• Chapter 18: Modeling the NHL
• Chapter 19: Modeling Soccer
• Chapter 20: Modeling College Sports
• Chapter 21: Modeling Combat Sports and Tennis
• Chapter 22: Modeling Emerging Markets

6

Part V: Advanced Quantitative Methods

6 chapters

• Part V: Advanced Quantitative Methods
• Chapter 23: Time Series Analysis for Betting
• Chapter 24: Simulation and Monte Carlo Methods
• Chapter 25: Optimization Methods for Betting
• Chapter 26: Ratings and Ranking Systems
• Chapter 27: Advanced Regression and Classification

7

Part VI: Machine Learning

6 chapters

• Part VI: Machine Learning for Sports Betting
• Chapter 28: Feature Engineering for Sports Prediction
• Chapter 29: Neural Networks for Sports Prediction
• Chapter 30: Model Evaluation and Selection
• Chapter 31: The Complete ML Betting Pipeline
• Chapter 32: Natural Language Processing for Betting

8

Part VII: Live Betting and Advanced Markets

4 chapters

• Part VII: Live Betting and Advanced Markets
• Chapter 33: Live and In-Play Betting
• Chapter 34: Prop Bets and Player Markets
• Chapter 35: Futures and Season-Long Markets

9

Part VIII: Psychology and Discipline

4 chapters

• Part VIII: Psychology and Discipline
• Chapter 36: The Psychology of Betting
• Chapter 37: Discipline, Systems, and Record-Keeping
• Chapter 38: Risk Management and Responsible Gambling

10

Part IX: Industry and Future

3 chapters

• Part IX: Industry and Future
• Chapter 39: The Sports Betting Industry
• Chapter 40: The Future of Sports Betting

11

Part X: Capstone

6 chapters

• Part X: Capstone
• Chapter 41: Putting It All Together
• Chapter 42: Research Frontiers
• Capstone Project 1: Complete NFL Prediction and Betting System
• Capstone Project 2: Multi-Sport Arbitrage and Value Detection Platform
• Capstone Project 3: Season-Long Betting Simulation Challenge

12

Appendices

8 chapters

• Appendix A: Mathematical Foundations
• Appendix B: Statistical Tables
• Appendix C: Python Reference
• Appendix D: Data Sources Directory
• Appendix E: Glossary
• Appendix F: Notation Guide
• Appendix G: Answers to Selected Exercises
• Appendix H: Bibliography

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