BIO: Sam Ventura is the Vice President of Hockey Strategy and Research for the Buffalo Sabres, and an affiliated faculty member at Carnegie Mellon University’s Department of Statistics & Data Science. He also serves as an advisory board member for the University of Pittsburgh’s MS in Quantitative Economics program. Prior to that, he was the Director of Hockey Operations and Director of Hockey Research for the Pittsburgh Penguins; a professor of Statistics at CMU, where he also received his PhD (Statistics, 2015); an assistant coach for Carnegie Mellon’s ice hockey team; and faculty advisor to the CMU Sports Analytics Club. 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 co-organizes the annual Carnegie Mellon Sports Analytics Conference. His current research interests include evaluating in-game athlete decision-making, optimizing human athletic performance, and objective decision-making for professional sports front offices.

BIO: Andrew C. Thomas has served as Vice President of Baseball Analytics for the Detroit Tigers since 2024. From 2019 to 2024 he led Data Science at SportsMEDIA Technology (SMT), building the company's inaugural 12-person multi-sport group, leading the NHL's puck-and-player-tracking eventing partnership, and designing SMT RAZOR, a team-facing interface pairing tracking insights with video and player and team evaluation. He served as Lead Hockey Researcher for the Minnesota Wild from 2016 to 2019, and consulted on baseball operations and executive hiring for several MLB clubs between 2016 and 2024, and taught statistics and data science at Carnegie Mellon University (2009–2014) and the University of Florida (2015) He holds a PhD and MA in Statistics from Harvard University and an SB in Physics from MIT.

BIO: Lauren is an engineer on ESPN’s industry-leading Sports Analytics team. She and the team create analytical storytelling tools, like the Football and Basketball Power Index ratings used across collegiate and professional sports, and develop products and experiences to support insightful and innovative storytelling. Before moving to Connecticut to work at ESPN in 2013, the Oklahoma native and University of Oklahoma mathematics graduate started her career by blending her love of sports and numbers as a high school math teacher and coach. While at OU, she represented on the sidelines with the pom squad allowing her to experience memorable sports moments from the sidelines. Lauren and her husband, John, live in Connecticut with their dog, Watson.

BIO: Alexandre Andorra has spent close to a decade building Bayesian models for questions that resist clean answers -- in pharma, in tech, and in sport. He co-authored the Soccer Factor Model, which borrows the machinery of asset pricing to separate a player's own skill from the team around them, and is now used at professional soccer teams. Earlier, as Senior Applied Scientist at the Miami Marlins, he built forecasting models that fed real roster decisions. Most of his energy, though, goes into making these methods reachable for other people. He is a core contributor to PyMC, where several tutorials he wrote became the library's official documentation, and he co-founded PyMC Labs. In 2019 he started Learning Bayesian Statistics, where he has spent years asking researchers to explain their work in plain language -- a habit that shapes how he teaches.

TITLE: "Improving the aggregation and evaluation of NBA mock drafts" BIO: Jared Fisher is an Assistant Professor of Statistics at Brigham Young University whose research sits at the intersections of Bayesian statistics, causal inference, and sports analytics. His methodological work focuses on Bayesian machine learning and flexible modeling, addressing problems ranging from treatment effect heterogeneity in healthcare to decision-making in sports. His sports analytics research includes work in baseball, volleyball, cross country, and especially basketball. He earned both his B.S. and M.S. degrees in Statistics from BYU before completing his Ph.D. at the University of Texas at Austin. Prior to joining his alma mater as faculty, he was a postdoctoral scholar and lecturer in the Department of Statistics at the University of California, Berkeley.

TITLE: "Bayesian Hierarchical Change-Point Model for Pitcher Biomechanics" BIO: Rose Graves is a 5th year PhD student at Rice University. Her work revolves around developing Bayesian methodologies for sports and environmental applications. Before starting her PhD. she worked for the Houston Astros, and she currently serves as an associate analyst for the San Francisco Giants.