Josh Orenstein is currently the NBA’s Senior Director of Basketball Strategy & Analytics and Senior Data Scientist. He has over a decade of experience in the sports industry as a data scientist. He analyzed 3D radar data that transformed performance evaluation and development in Major League Baseball. At the NBA, he uses advanced analytics to improve the competitiveness of the on-court product, evaluation of referees, and evaluation of collegiate basketball players. He is also a Lecturer at Columbia University.
Advanced Sports Analytics Course Curriculum
In this new course, students will learn how data science is used in the sports industry. They will apply analytical techniques, including multiple regression, classification, and machine learning algorithms, to analyze data sets about player performance and business models.
The online course features real-world projects, including making evidence-based recommendations about which free agents to acquire; building machine learning models to predict an athlete’s performance; scraping game performance data to conduct a cluster analysis of game competitiveness; and building a probabilistic hitting model to predict the probability that a batter will hit a home run in a particular at-bat. Students will also use machine learning algorithms to make an evidence-based recommendation on how to spend $3.5 billion to purchase a team or portfolio of teams.
Additionally, the 8-week course will feature a number of special guests, , including a panel of data experts from the NFL and a discussion of careers in sports analytics from NBA, NFL, and NHL industry experts.
M.S. in Data Science Named a Top 10 “Best Value Online Big Data Program”
Merrimack College’s M.S. in Data Science was ranked a Top 10 “Best Value Big Data Programs” of 2022 by ValueColleges.com. The 100% online degree features 8 courses that can be completed in one year, with no background in coding or statistics required.
Designed under the guidance of faculty experts and industry professionals, the innovative curriculum builds a strong foundation of data science skills, beginning with courses in R, Python, statistics, and data visualization. Courses emphasize creating and validating predictive models and using machine learning and artificial intelligence techniques to conduct supervised and unsupervised learning. Students apply their modeling and data analytic skills to real-life applications in healthcare environments, social media/marketing, and sports analytics.
The M.S. in Data Science program has over 125 graduates working at companies such as Capital One, IBM, Indeed.com, Liberty Mutual Insurance, Microsoft, Thermo Fisher Scientific, Vertex Pharmaceuticals, and more.