Academic Report of the School of Mathematical Sciences [2025] No. 094  

(High-Level University Construction Series Report No. 1116)  

Lecture Title: The Intersection of Sports and Data Science: Challenges and Opportunities in Statistical Modeling  

Lecturer: Associate Professor Hu Guanyu (Michigan State University)  

Lecture Time: October 9, 2025, 10:00-11:00 (morning)  

Venue: Conference Room 514, Huixing Building, Yuehai Campus, Shenzhen University  

Abstract:  

Sports is one of the most extensive and dynamic fields for statistical applications. With the advancement of data acquisition and processing technologies, sports statistics plays a crucial role in athlete performance analysis, tactical optimization, injury risk assessment, and fan behavior research. Through rational statistical modeling and data analysis, we can not only better understand the process and outcomes of competitions but also provide scientific basis for coaches’ decision-making and athletes’ training. In this lecture, we will introduce several research directions of statistics in sports, such as player performance modeling, team strategy optimization, and visual analysis of sports data, demonstrating the unique value and cutting-edge challenges of statistics in sports science and industry.  

Michigan State University (MSU) has long enjoyed a high reputation in statistics and data science research. In recent years, the Department of Statistics at MSU has launched the Ph.D. in Statistics program and the Master of Science in Data Science (MSDS) program, providing a broad academic and career development platform for students aspiring to pursue further studies. The Ph.D. in Statistics program focuses on in-depth training in theory and methods, cultivating high-level talents capable of conducting original research in academia, industry, and government departments. The MSDS program, on the other hand, emphasizes practice and application, covering areas such as machine learning, big data analysis, artificial intelligence, and statistical modeling, helping students master advanced data science skills and acquire the ability to solve complex practical problems. We welcome students with a strong interest in statistics and data science to apply actively and join MSU’s academic community!  

Lecturer’s Biography:  

Dr. Hu Guanyu is currently an Associate Professor in the Department of Statistics at Michigan State University. His main research directions include Bayesian methods, network point process models, spatiotemporal modeling, and their applications in public health and sports analytics. He has published numerous papers in top international journals in statistics and applied fields, and actively promotes interdisciplinary cooperation and methodological innovation. In terms of academic services, Dr. Hu currently serves as Associate Editor of renowned international journals Biometrics and Annals of Applied Statistics (AOAS), and has long been engaged in reviewing and editorial work for a number of international statistical journals. Meanwhile, he plays an active role in international academic organizations: he has served as Chair of the Statistics in Sports Section of the American Statistical Association (ASA) and Program Chair of the International Society for Bayesian Analysis (ISBA). In addition, Dr. Hu is an Elected Member of the International Statistical Institute (ISI), making important contributions to statistical research and the development of the academic community.  

Faculty and students are welcome to attend!  

Inviter: Zhou Yan  

School of Mathematical Sciences  

October 9, 2025