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
[email protected].

🎵 Music Credit: Intro and outro music for this episode is “Nomu” by Good Kid.

#SportsAnalytics #FanDuel #MLB #BaseballAnalytics #PredictiveModeling #BehavioralEconomics #SportsBetting #DataScience #CareerAdvice #CollegeBaseballAnalytics

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