In our fourth episode of the Sport Analytics Podcast, our host Amrit Vignesh sits down with Riley Leonard, a Data Scientist in Sports Modeling & Innovation at FanDuel who’s also worked in the Boston Red Sox baseball analytics department. Riley shares how he built robust models to price MLB odds in real time, balanced fast-paced sports betting challenges, and leaned on the same pitch-by-pitch data used in MLB front offices. Riley also dives into how his academic background in behavioral economics influenced his baseball research and gave him a unique lens on batting decisions. From applying advanced R packages for predictive modeling to communicating insights with non-technical teams, Riley’s journey shines a light on the intersection of analytics, player evaluation, and sports betting innovation. Whether you’re fascinated by the fantasy baseball aspect of an MLB front office or curious about real-time sports betting operations, you won’t want to miss Riley’s insights into predictive modeling, robust data pipelines, and bridging academia with high-stakes professional environments.
Key Takeaways: MLB & Sports Betting: How publicly available StatCast data underpins both front-office scouting and real-time odds making. Fast-Paced Model Updates: Why reliability and edge-case testing matter when you’re live in the sportsbook. Behavioral Biases: Applying cognitive science to understand why players swing—and what that means for predictive analytics. Communication is King: Translating complex data insights for traders, coaches, scouts, and executives alike. Building a Portfolio: Why diving into public projects—even with simple R or Python scripts—can fast-track your sports analytics career. 🔔 Subscribe to our channel for more episodes featuring leaders in sports analytics, career advice, and technical breakdowns! 📧 For inquiries or collaborations, contact Dave Yount at dave@sportanalytics.com. 🎵 Music Credit: Intro and outro music for this episode is “Nomu” by Good Kid. #SportsAnalytics #FanDuel #MLB #BaseballAnalytics #PredictiveModeling #BehavioralEconomics #SportsBetting #DataScience #CareerAdvice #CollegeBaseballAnalytics