Sport Analytics Podcast - Episode #3 - Neil Pierre-Louis - Baseball Systems - Boston Red Sox

01/17/25 • 28 min

In the third episode of the Sport Analytics Podcast, our host Amrit Vignesh sits down with Neil Pierre-Louis, a Software Engineer for Baseball Systems at the Boston Red Sox. Neil takes us on a fascinating ride—starting as an Environmental Science major, interning at Google, leading analytics projects for UNC Baseball, and now contributing to an MLB front office. Neil explains how he built a robust foundation in SQL and software development, created hockey analytics tools like expected goals models, and collaborated with coaches to turn raw data into strategic insights. He also offers candid advice on building a standout portfolio, navigating cross-departmental projects, and knowing when (and how) to showcase your work. Whether you’re already in the sports analytics space or just exploring your passion for data-driven insights, you won’t want to miss this deep dive into the intersection of tech and baseball. Key Takeaways: Balancing passion projects in hockey analytics with a fast-paced MLB role Bridging Google’s large-scale processes with a startup-like environment in sports Building front-end solutions and managing tight deadlines in baseball research and development The pivotal role of SQL in handling massive sports datasets Tips for communicating complex models to non-technical stakeholders 🔔 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 #BaseballAnalytics #BostonRedSox #SQL #HockeyAnalytics #SoftwareEngineering #DataEngineering #CareerAdvice #CollegeBaseballAnalytics

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Sport Analytics Podcast - Episode #2 - Maezelle Millan - Senior Data Analyst - Chicago Bulls

In our second episode of the Sport Analytics Podcast, host Amrit Vignesh sits down with Maezelle Millan, Senior Data Analyst at the Chicago Bulls. Maezelle takes us through her inspiring journey from collegiate basketball player at Claremont McKenna College to a thriving career in professional sports analytics. She highlights how her background as a point guard shaped her problem-solving mindset, shares the challenges she faced transitioning from a consulting role at Semler Brossy to the fast-paced world of NBA business analytics, and dives deep into her day-to-day workflow with SQL, Tableau, and CRM systems. Throughout the conversation, Maezelle explains how she collaborates with VPs and Directors in corporate partnerships, offering data-driven insights that help shape high-level decision-making. She also reveals her favorite projects—including the development of a new in-house data warehouse—and provides invaluable advice on breaking into the sports analytics field, building a standout portfolio, and sharpening both technical and soft skills. On top of that, Maezelle discusses her involvement in Women in Sports and Events (WISE) and how she’s leveraged leadership lessons from her time as a student athlete to excel in her current role. Whether you’re aiming for a career in the NBA, passionate about data analytics, or simply curious about the intersection of sports and technology, this episode is packed with practical tips, industry insights, and inspiration. Don’t miss it! 🔔 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.

Topics Covered: Maezelle’s journey from collegiate athlete to Senior Data Analyst at the Chicago Bulls Transitioning from consulting to pro sports analytics Day-to-day responsibilities and collaboration with corporate partners Key tools and technologies (SQL, Tableau, Snowflake, DBT, CRM) Advice for aspiring analysts and portfolio development tips Leadership insights from basketball and involvement with WISE Relevant Hashtags: #SportsAnalytics #NBAAnalytics #ChicagoBulls #BasketballAnalytics #SQL #Tableau #DataVisualization #SportsTech #BusinessAnalytics #CorporatePartnerships #DataWarehouse #WomenInSports #WISE #CareerAdvice #ConsultingToSports #LeadershipSkills #AnalyticsCareers #CRM #SportsMarketing #DataScienceInSports #ProfessionalDevelopment #SportsBusiness

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Sport Analytics Podcast - Episode #4 - Riley Leonard - Data Scientist - Sports Modeling - FanDuel

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