Chapter 22: Further Reading - Modeling Emerging Markets

Academic Papers and Research

  1. Broadie, Mark. "Assessing Golfer Performance on the PGA Tour." Interfaces (2012). The foundational academic paper on the strokes gained framework by its creator. Explains the methodology, validates it against traditional golf statistics, and demonstrates its superiority for evaluating golfer performance. Essential reading for anyone building a golf tournament model.

  2. Gu, Weifeng, and Thomas L. Saaty. "Predicting the Outcome of a Tennis Tournament." Journal of Quantitative Analysis in Sports (2019). Explores the application of various prediction models to tennis tournament outcomes, with insights on handling bracketed competition structures that transfer directly to esports tournament prediction.

  3. Karakus, Ogulcan, et al. "Predicting the Outcome of Esports Matches." Expert Systems with Applications (2023). A systematic comparison of machine learning approaches to esports prediction across multiple titles. Finds that Elo-based features combined with game-specific metrics outperform pure ML approaches, validating the hybrid modeling strategy presented in this chapter.

  4. Woodland, Lin, and Bill Woodland. "The Effects of Risk Aversion on Wagering: Point Spread Versus Odds." Journal of Political Economy (1994). Classic paper establishing the theoretical framework for understanding why different market structures (moneyline vs. spread) exhibit different efficiency properties. The insights apply directly to comparing efficiency across prop, futures, and niche sport markets.

  5. Smith, Michael A., David Paton, and Leighton Vaughan Williams. "Market Efficiency in Person-to-Person Betting." Economica (2006). Examines market efficiency in betting exchanges versus traditional sportsbook markets, with findings relevant to understanding why thin markets are less efficient and how the presence or absence of sharp bettors affects price accuracy.

  6. Connolly, Robert, and Rendleman, Richard J. "Skill, Luck and Streaky Play on the PGA Tour." Journal of the American Statistical Association (2008). Investigates the role of randomness versus skill in golf, providing the statistical foundation for understanding tournament variance and why Monte Carlo simulation is the appropriate modeling approach for golf prediction.

  7. Becker, Adrian, and Xiao-Li Sun. "An Analytical Approach for Fantasy Football Draft and Lineup Management." Journal of Quantitative Analysis in Sports (2016). While focused on DFS, this paper's methodology for projecting individual player performance under game-environment constraints transfers directly to player prop modeling.

Books

  1. Broadie, Mark. "Every Shot Counts: Using the Revolutionary Strokes Gained Approach to Improve Your Golf Game and Strategy." Gotham Books (2014). The definitive book on strokes gained by its inventor. Explains the intuition, mathematics, and applications of the framework in accessible terms. Essential for any golf bettor, even those who will never play the game.

  2. Winston, Wayne. "Mathletics: How Gamblers, Managers, and Sports Enthusiasts Use Mathematics in Baseball, Basketball, and Football." Princeton University Press (2012). Contains excellent chapters on probability in individual competitions and long-shot markets that apply to futures analysis, golf outright betting, and prop market structure.

  3. Haugh, Martin B., and Raghav Singal. "How to Play Fantasy Sports Strategically (and Win)." MIT Sloan Management Review (2018). Provides a systematic framework for player projection optimization under salary constraints, with methodology directly applicable to prop market screening and portfolio construction across multiple prop bets.

Data Sources

  1. HLTV.org (CS2). The gold standard for competitive Counter-Strike data. Provides comprehensive match results, map statistics, player ratings, and team rankings. The free tier covers match results and basic stats; advanced statistics require a paid subscription. Available at https://www.hltv.org.

  2. Oracle's Elixir (League of Legends). Free, comprehensive statistical database for professional League of Legends across multiple regional leagues. Includes game-level and player-level statistics with downloadable CSV formats. Available at https://oracleselixir.com. The most accessible starting point for LoL modeling.

  3. PGA Tour ShotLink Data / Data Golf. The PGA Tour's ShotLink system tracks every shot on tour, providing the raw data for strokes gained calculations. While direct ShotLink access is restricted, Data Golf (https://datagolf.com) provides processed strokes gained data, historical tournament results, and betting market analysis for golf.

  4. PandaScore API. A professional-grade multi-game esports data API covering CS2, LoL, Dota 2, Valorant, and more. Provides real-time and historical match data, odds, and statistics. Paid access with tiered pricing. Available at https://pandascore.co. The preferred source for production esports models.

  5. Covers.com Consensus and Odds. Tracks opening and closing lines, line movement, and public betting percentages across major sportsbooks for both mainstream and emerging markets. Useful for identifying line movement patterns and market sentiment in prop and futures markets.

Online Resources and Communities

  1. Data Golf Blog. Regular analytical articles on golf tournament prediction, strokes gained methodology, course fit analysis, and betting strategy. Combines academic rigor with practical betting insights. One of the best publicly available resources for golf modeling.

  2. r/esportsbetting (Reddit). Community discussion of esports betting strategy, including model sharing, data sources, and market analysis. While quality varies, the community provides useful information on lower-tier leagues and market inefficiencies that are difficult to find elsewhere.

  3. Fantasy Labs and Fantasy Life. Platforms that provide prop market odds comparison, player projection tools, and historical prop line data. While designed for DFS and casual bettors, the odds comparison feature is valuable for identifying soft lines across sportsbooks.

  4. Pinnacle Sports Betting Resources -- Esports and Golf Sections. Pinnacle publishes articles on esports and golf market efficiency, including detailed analyses of their own closing lines and the predictive accuracy of various modeling approaches. Their esports-specific content is particularly valuable given their position as a leading esports sportsbook.

Methodological References

  1. Shin, Hyun Song. "Measuring the Incidence of Insider Trading in a Market for State-Contingent Claims." The Economic Journal (1993). The original paper introducing Shin's method for extracting implied probabilities from bookmaker markets while accounting for insider information. Technically demanding but provides the theoretical foundation for the most accurate vig-removal method discussed in the futures analysis section.