Chapter 1 Further Reading: Introduction to Sports Betting

The following annotated bibliography provides resources for deeper exploration of the topics introduced in Chapter 1. Entries are organized by category and chosen for their relevance to a quantitative approach to sports betting.

1. Moldea, Dan E. Interference: How Organized Crime Influences Professional Football. William Morrow, 1989. A thoroughly researched investigative work tracing the historical connections between organized crime and professional sports betting in the United States. This book provides essential context for understanding why sports betting was prohibited for decades and the regulatory concerns that persist today. Particularly valuable for the historical exercises in this chapter.

2. Levitt, Steven D. "Why Are Gambling Markets Organised So Differently from Financial Markets?" The Economic Journal, 114(495), 2004. While technically a journal article, Levitt's accessible writing style makes this readable for a broad audience. He examines why sportsbooks set lines to maximize profit rather than to balance action, challenging the conventional wisdom about how the vig model works. This is foundational reading for understanding the sportsbook business model discussed in Chapter 1.

3. Vaughan Williams, Leighton, ed. Information Efficiency in Financial and Betting Markets. Cambridge University Press, 2005. A comprehensive collection of academic essays examining market efficiency across both financial and betting markets. The chapters on betting market efficiency are directly relevant to Chapter 1's discussion of whether and how quantitative methods can find edges. Suitable for readers who want a rigorous, economics-grounded perspective on sports betting markets.

4. Kucharski, Adam. The Perfect Bet: How Science and Math Are Taking the Luck Out of Gambling. Basic Books, 2016. An engaging popular science book that traces the history of mathematical approaches to gambling, from Galileo's dice calculations to modern machine learning models. Kucharski writes for a general audience while covering surprisingly deep quantitative concepts. An excellent starting point for readers new to the intersection of mathematics and betting.

5. Peta, John. Trading Bases: How a Wall Street Trader Made a Fortune Betting on Baseball. Dutton, 2013. A first-person account of a former Wall Street trader who applied financial modeling techniques to baseball betting. The book vividly illustrates the parallels between financial markets and betting markets that Chapter 1 introduces. It also demonstrates the practical challenges of implementing a quantitative betting strategy, including bankroll management and sportsbook limitations.

6. Roxborough, Roxy and Rhoden, Mike. Race and Sports Book Management. UNLV Press, 1998. Written by the man who ran the Las Vegas Sports Consultants line service for decades, this book provides an inside look at how sportsbooks set and manage lines. Though somewhat dated in its technology references, the core principles of sportsbook operations described here remain relevant and directly inform the business model discussion in Chapter 1.

Books: Academic and Technical

7. Cortis, Dominic. Expected Values: What the Data Tells Us About Betting Markets. Routledge, 2021. A rigorous academic treatment of betting market analysis that bridges theory and practice. Cortis covers odds formation, market efficiency, and the mathematical foundations of sports betting with quantitative precision. This book serves as an excellent companion text for readers who want more mathematical depth behind the concepts introduced in Chapter 1.

8. Hausch, Donald B., Lo, Victor S.Y., and Ziemba, William T., eds. Efficiency of Racetrack Betting Markets. World Scientific, 2008 (2nd edition). Although focused on horse racing, this collection is the seminal academic work on betting market efficiency and has influenced all subsequent research on sports betting markets. The chapters on the favorite-longshot bias and optimal betting strategies provide foundational concepts that apply across all sports betting. Essential for readers pursuing the market efficiency topic in depth.

9. Winston, Wayne L. Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports. Princeton University Press, 2022 (2nd edition). A textbook-style treatment of quantitative methods applied to sports, including dedicated chapters on betting and odds. Winston provides worked examples and problems that complement the exercises in this chapter. Particularly useful for readers who want to strengthen their mathematical foundations before proceeding to the probability and statistics chapters of this textbook.

Academic Papers and Working Papers

10. Shin, Hyun Song. "Prices of State Contingent Claims with Insider Traders, and the Favourite-Longshot Bias." The Economic Journal, 103(421), 1993, pp. 1109-1119. Shin's model explains how the existence of informed bettors (insiders) causes sportsbooks to shade their odds, contributing to the favorite-longshot bias. This paper is a foundational reference for understanding why implied probabilities systematically deviate from true probabilities, a key concept underlying the expected value framework in Chapter 1.

11. Borghesi, Richard. "The Home Team Weather Advantage and Biases in the NFL Betting Market." Journal of Economics and Business, 59(4), 2007, pp. 340-354. An empirical study examining how weather conditions create systematic biases in NFL betting markets. This paper is a concrete example of the kind of market inefficiency that a quantitative bettor might exploit, and it illustrates the research methodology relevant to the analysis exercises in Part D.

12. Humphreys, Brad R., Paul, Rodney J., and Weinbach, Andrew P. "Consumption Benefits and Gambling: Evidence from the NCAA Basketball Betting Market." Journal of Economic Psychology, 36, 2013, pp. 27-36. This paper investigates the behavior of recreational bettors and provides evidence that many bettors derive entertainment value (consumption benefits) beyond expected monetary returns. It helps explain why the betting market can sustain a vig: recreational bettors are willing to accept negative expected value for the entertainment experience. This directly informs the discussion of stakeholder motivations in Chapter 1.

13. Kaunitz, Lisandro, Zhong, Shenjun, and Kreiner, Javier. "Beating the Bookies with Their Own Numbers -- and How the Online Sports Betting Market Is Rigged." arXiv preprint, 2017. This widely cited preprint demonstrates that comparing odds across multiple sportsbooks can identify positive expected value bets, but also documents how sportsbooks restrict winning accounts. The paper provides empirical evidence for both the possibility of finding edges through line shopping and the practical barriers to exploiting those edges, themes central to Chapter 1.

Websites and Data Sources

14. Odds Portal (oddsportal.com) A comprehensive odds comparison website that aggregates lines from dozens of sportsbooks worldwide across all major sports. Invaluable for the line shopping and odds comparison exercises in this chapter. The historical odds data allows users to track line movements and analyze closing line value. Free to use with optional premium features.

15. The Action Network (actionnetwork.com) A leading sports betting media and data platform that provides real-time odds, public betting percentages, sharp money indicators, and line movement tracking. The site's educational content is accessible to beginners while its data tools serve advanced bettors. The public versus sharp money data is particularly relevant to the line movement analysis in Exercise D.4.

16. Sports Business Journal / Legal Sports Report (legalsportsreport.com) The authoritative source for tracking the legal status of sports betting across all U.S. states and internationally. Updated continuously as new legislation is enacted or regulations change. Essential for the legal landscape research in Exercise E.1 and for staying current on the rapidly evolving regulatory environment discussed in Chapter 1.

17. Kaggle Sports Betting Datasets (kaggle.com) Kaggle hosts numerous user-contributed datasets containing historical odds, game results, and betting market data across various sports. These datasets are useful for the programming exercises in Part C, particularly for building and testing the bet tracking and odds comparison tools. Search for datasets tagged with "sports betting," "odds," or specific sport names.

Podcasts and Media

18. Beating the Book Podcast A long-running podcast hosted by Gill Alexander that focuses on the analytical and quantitative side of sports betting. Episodes cover line movement analysis, market theory, and interviews with professional bettors and analysts. The show's emphasis on process over picks aligns with the quantitative philosophy introduced in Chapter 1. Particularly recommended are the early episodes covering fundamentals of odds and market structure.

19. Behind the Bets (ESPN / David Purdum) David Purdum's reporting for ESPN covers the business and culture of sports betting with a focus on the industry's major players, legal developments, and market dynamics. His work provides accessible, well-reported context for the stakeholder analysis and legal landscape topics in this chapter. Available as articles on ESPN.com and through various ESPN podcast feeds. Purdum's coverage of major regulatory milestones is especially relevant to the post-PASPA landscape discussed in Chapter 1.

How to Use This Reading List

For readers working through this textbook sequentially, the following prioritization is suggested:

  • Start with: Kucharski (entry 4) for an engaging overview, and Legal Sports Report (entry 16) for current regulatory context.
  • Go deeper on sportsbook operations: Roxborough (entry 6) and Levitt (entry 2).
  • Go deeper on market efficiency: Vaughan Williams (entry 3) and Shin (entry 10).
  • For programming exercises: Kaggle datasets (entry 17) and Odds Portal (entry 14) for real data.
  • For ongoing learning: Subscribe to the Beating the Book podcast (entry 18) and follow Action Network (entry 15) for daily market analysis.

Many of these resources will be referenced again in later chapters as we build upon the foundational concepts introduced here.