DSCI 207 - Summer Session
New QSR Option for WWU Students: DSCI 207 - Introduction to Sports Analytics
Is Kevin Durant a better scorer than Lebron James, or vice versa?
Does being sacked during a game affect the number of touchdown passes that Tom Brady throws?
What is the evidence for “clutch hitting” in baseball?
Why does Rafael Nadal win a greater percentage of the games he plays on clay surfaces?
Course Description
Introduced in summer 2021, there is a new option for WWU students needing to satisfy the Quantitative and Symbolic Reasoning GUR: DSCI 207 – Introduction to Sports Analytics. The course may be used as the second course of a two-course sequence under Option 1 or Option 2 for satisfying the QSR requirement.
As broadly defined, “analytics” uses data to reach conclusions and make decisions. The difficulty, of course, is that data are usually “noisy” and it can be difficult to come to the correct conclusions or make the best decisions. Sports data illustrate this challenge in an easily understood framework: everyone knows that the outcome of a sporting event depends to a certain extent on “luck” or “chance” as well as the skills of the participants. How, then, to determine the relative importance of the various factors which do not depend on luck or chance? Identifying these factors, separating them from the luck or chance component, and quantifying their relative importance is the focus of this course. Data from a range of professional sports are used to illustrate the techniques presented in the course.
Course Topics
Topics covered in this course include:
- Types of Sports Data
- Summarizing and Transforming Sports Data
- Sports Events and the Rules of Probability
- Relative Player Performance and Evaluating Streaks
- Sports Statistics and the Margin of Error
- Relationships Between Sports Variables
- Lurking Variables and Patterns Through Time
- Regression to the Mean
- Nonlinear Relationships