Faculty Advisor: Lecturer, School of Information, University of Michigan

Program Start Time: TBD (meetings will take place for around one hour per week)

Research Practicum Introduction

Embark on a journey into the theoretical foundations of sports analytics, with basketball serving as the focal point for tracing its evolution and profound impact on sports dynamics. Delve into hands-on exploration with authentic datasets and fundamental analytics methodologies utilized in player assessment and on-court decision-making scenarios. Examine the inherent strengths and limitations of contemporary sports analytics paradigms, fostering a nuanced comprehension of their practical application. 

Students will be equipped with exposure to quantitative and computational methodologies within a domain they are passionate about, fostering a seamless transition into future collegiate pursuits. They will also learn to integrate quantitative data to augment disciplinary knowledge, mastering the art of narrative storytelling through numerical analysis and acquiring proficiency in cutting-edge computational techniques applicable across various career trajectories.

*While the analysis of other sports may be considered, basketball will serve as the primary case study throughout the program.

Possible Topics For Final Project

• Understanding how shot composition strategies effect roster management and win-loss records

• Introductory exploration of the use of computer vision in generating novel basketball  analytics metrics 

• Analyzing the effectiveness of different defensive strategies in basketball using advanced statistical methods.

• Investigating the impact of player positioning and movement on team performance during specific game situations.

• Examining the relationship between player performance metrics and team success over multiple seasons.

• Developing predictive models for player injuries based on historical data and injury risk factors.

• Or other topics in this subject area that you are interested in, and that your professor approves after discussing it with you.

Program Detail

• Cohort Size: 3-5 students

• Duration: 12 weeks

• Workload: Around 4-5 hours per week (including class time and homework time)

• Target Students: 9-12th grade students interested in data science, computer science, sport analytics, quantitative and computational inquiry or other related fields.