This course will teach you how statistics and probability can be applied in sports, in order to evaluate team and individual performance, build optimal in-game strategies and ensure fairness between participants. Topics will include examples drawn from multiple sports such as basketball, baseball, soccer, football and tennis. The course is intended to focus on data-based applications, and will involve computations in R with real data sets via tutorial sessions and homework assignments. Prerequisites: No statistical or programming background is assumed, but introductory courses, e.g, Stats STATS 60, Stats STATS 117, or DataSci STATS 112 are recommended. A prior knowledge of Linear Algebra (e.g., Math STATS 51) and basic probability is strongly recommended.
3 units · Letter or Credit/No Credit · GER: WAY-AQR
This course will teach you how statistics and probability can be applied in sports, in order to evaluate team and individual performance, build optimal in-game strategies and ensure fairness between participants. Topics will include examples drawn from multiple sports such as basketball, baseball, soccer, football and tennis. The course is intended to focus on data-based applications, and will involve computations in R with real data sets via tutorial sessions and homework assignments. Prerequisites: No statistical or programming background is assumed, but introductory courses, e.g, Stats 60, Stats 117, or DataSci 112 are recommended. A prior knowledge of Linear Algebra (e.g., Math 51) and basic probability is strongly recommended.
Offered in Winter 2027 at Stanford University.