Course Format

The class will discuss the theory, development, and application of analytics in sports. Students will learn about the application of analytics in sports for purposes of in-game strategy, player performance, team management, sports operations, and fantasy competitions, among many other topics. The class will consist of lectures, guest speakers from the sports industry and academia, and culminate with a group project.

Rationale

An increasing number of organizations from a variety of industries have discovered the power of analytics to out-think, out-execute, and out-perform the competition [Davenport and Harris, 2007]. Analytics includes the extensive use of data, statistical and quantitative analysis, visualization, explanatory and predictive models, and fact-based management to drive decisions and actions. The application of analytics in sports is particularly significant. Like most aspects of society today, sports and the sports industries are awash in data. Individual athletes, teams, organizations, owners, fantasy league players, and many other people simply interested in sports are all now finding new ways to use data and data analysis to their benefit. Analytics has been used to gain team and player insight, human resource optimization, and game performance management, among many other things. Many new statistics, analysis techniques, and methods to communicate analysis results have emerged in recent years and all contribute to this new area of sports analytics. One of the many examples of the growing interest in sports analytics is the MIT Sloan Sports Analytics Conference, a one-day event which attracted over 1000 attendees from academia and industry in 2010. The annual event features speakers and panels from professional teams, scouting organizations, team ownership, media and press, and sports data companies. The goal of this special topics course is to introduce the student to the plethora of applications of analytics in sports. The course will feature a blend of both theory and practice including guest speakers from academia and the sports industry.

T. H. Davenport and J. G. Harris, Competing on Analytics: The New Science of Winning, Harvard Business School Press, Boston (2007).

Potential Lecture Topics

• Fantasy Football analytics
• Fantasy Baseball analytics
• Baseball analytics
• Football analytics
• Basketball analytics
• Hockey analytics
• Soccer analytics
• Golf analytics
• Tennis analytics
• Auto racing analytics
• Salary cap management
• Coaching analytics
• Player assessment
• Sports data storage and access
• Data presentation and visualization
• Sports business analytics
  
  
  

Course Requirements

The course is designed for students from all backgrounds and degree levels interested in studying sports analytics. There are no pre-requisites except for an appreciation and enthusiam for data analysis and visualization. Students should have some familiarity with basic statistics and data analysis techniques. Specific course requirements include:

• Read all class materials, attend and participate in class discussions.
• Prepare and present a project on a sports analytics related topic

Project

The term project will include the in-depth investigation and presentation of a sports analytics related topic. The focus can be on the use of analytics in a particular sport (e.g. baseball, football, etc.) or a particular technology (e.g. data mining, visualization, etc.). A progress report presentation will be due in class on partway through the term. The final deliverable will include a 20-minute presentation to class.

Attendance

Since this course convenes only once a week, attendance at all class meetings is mandatory. Please do not plan to be absent. We expect you to arrive on time and to be prepared to discuss the session's readings (if applicable). This is not a lecture course, but an active learning opportunity built around guest speakers and readings.

Grading

• Letter Grade and Pass/Fail
• Class Preparation and Participation (50%)
• Project (50%)
  

Honor Code

Each student must read and abide by the Georgia Tech Academic Honor Code (www.honor.gatech.edu).