Sports Analytics Speaker Series

Abstract: In 2016, Ethan Moore embarked on a journey to secure a position within a Major League Baseball (MLB) front office, starting as a high school senior with a passion for statistics. His article, “My MLB Job Hunting Experience” chronicles his path from early aspirations to achieving his goal, offering valuable insights for aspiring sports data professionals. Moore emphasizes the importance of developing strong analytical skills, gaining relevant experience through internships, and building a professional network within the sports industry. He also highlights the challenges faced during the job search process and the perseverance required to succeed in this competitive field. This talk will delve into Moore’s experiences, providing practical advice and strategies for students aiming to secure roles in sports analytics, particularly with professional teams.

Bio: Ethan Moore is a data scientist with Nike. In previous roles he served as a data science contractor for the Cincinnati Reds, and an analyst for the Colorado Rockies. He started as the director of analytics for Cal Poly Baseball and had an internship with the Minnesota Twins. With expertise in SQL, R, Python, and Tableau, he continues to use analytics and machine learning to build predictive models and demand forecasting.

Abstract: Cal Poly alum Nate Ngo will be talking about:

• Using VolleyStation and VolleyMetrics to analyze team performance.
• Leveraging RMarkdown and Shiny for interactive data visualization.
• Developing tactics based on serve reception and blocking data.

Bio: Nate Ngo is currently the Technical Coordinator for USA Men's National Volleyball Team. He has helped Team USA secure multiple international medals, including bronze in the 2024 Paris Olympics.

Nate will also be available for a "meet and greet" in 180-321 from 11:10-12pm (with pizza).

Abstract: TBD

Bio: Benjamin S. Baumer is a professor in the Statistical & Data Sciences program at Smith College. Ben is a co-author of The Sabermetric Revolution, Modern Data Science with R, and the second and third editions of Analyzing Baseball Data with R. Ben has received the Waller Education Award from the ASA Section on Statistics and Data Science Education, the Significant Contributor Award from the ASA Section on Statistics in Sports, and the Contemporary Baseball Analysis Award from the Society for American Baseball Research. His research interests include sports analytics, data science, statistics and data science education, statistical computing, and network science.

Bio: Brian Huey enters his eight seasonw ith the Giants where he works on statistical inference and mchine learning to support Baseball Operations. His academic background is in Transportation Studies, including an MS in Civil and Environmental Engineering and MCP in City and Regional Planning from UC Berkeley, after a BS in Economics.

Bio: Dr. Franks is an Associate Professor in the Department of Statistics and Applied Probability at the University of California, Santa Barbara. His research interests include causal inference and sensitivity analysis, covariance estimation, missing data and measurement error, high throughput applications in biology (“omics”), Bayesian statistics, and sports. He is currently a research advisor for Zelus Analytics and former consultant to the Philadelphia 76ers.

Abstract: How coaches use analytics to prepare for weekly opponents in football and opportunities for future research/exploration.

Bio: Jarrod James is an experienced football coach with a strong background in both collegiate and professional football. Currently serving as the Offensive Assistant Coach for the Houston Texans, he has played a pivotal role in managing the offensive line, assisting in-game decision-making, and preparing for weekly opponents. Jarrod was hired as a full-time coach after completing the prestigious Bill Walsh Diversity Coaching Fellowship. His career also includes coaching roles with Michigan State University, the Los Angeles Wildcats in the XFL, and the Arkansas State University Red Wolves.

Abstract: TBD

Bio: Sam Ventura is the Vice President of Hockey Strategy and Research for the Buffalo Sabres of the National Hockey League, and an affiliated faculty member at Carnegie Mellon University’s Department of Statistics & Data Science. Sam has co-authored multiple R packages for open-source data collection and analysis, including nhlscrapr, nflscrapR, and spew, and he co-founded war-on-ice.com. He also co-organizes the annual Carnegie Mellon Sports Analytics Conference.

Abstract: This talk will compare and contrast business analytics and sports analytics, focusing on my experience covering the business intelligence/analytics side of sports with roles at SF 49ers/Seattle Kraken and the player performance side of sports working at MLB clubs (Milwaukee Brewers, Cincinnati Reds). In particular, I will talk about my current work at Swish Analytics that is on the sports analytics/betting side.

Bio:Rus Davtian is a data scientist specializing in sports analytics and machine learning. He currently works as an MLB Data Scientist at Swish Analytics, where he develops machine learning models for pre-game and in-play oddsmaking. Rus has also worked at the Cincinnati Reds, where he focused on player evaluation and in-game strategy. Rus is a graduate of Cal Poly, receiving a Bachelor's of Science in Statistics with a Data Science minor in 2018 and also receiving a Masters of Science in Quantitative Economics in 2021.