The sport analytics concentration helps students develop strong data analysis and analytical thinking skills to address important questions in the sport industry. Like many other industries, the sport industry is gathering an unprecedented amount of data on a daily basis. For example, the business office of professional sport teams collects data about fans and sponsors. The front office and coaching staff of major league teams increasingly rely on data to inform their in-game decisions. With the collection of massive data sets, sport organizations need professionals to analyze this data in order to draw useful insights.
The sport analytics concentration under the department of sport management at Rice University provides students rigorous training in areas such as data science, computer science, statistics, and sport management. The interdisciplinary studies will allow students to build solid theoretical foundations in sport management as well as strong data analysis skills. Along the way, students will be challenged to apply these skills to solve practical issues in the sport industry.
The sport analytics concentration also highly values the importance of experiential learning. Students will have opportunities to work with mentors from professional sport teams, college teams, and other industry professionals on problem sets that are critical to sport organizations. Besides, the student-run sport analytics club at Rice University offers plenty of opportunities for students to collaborate on various sports analytics projects, brainstorm new research ideas, and gain experiences in the field of sports analytics.
Not only is analytics widely integrated into decision making by coaches, athletes, and front offices, but it also becomes increasingly important to the business operations of many sport teams. In the sport analytics program, students will have chances to explore the business side of the sport industry through the lens of analytics. In particular, students will learn how to use analytics in areas such as fan engagement, dynamic ticket strategies, sport marketing analytics, etc. With the increasing use of data-driven decision making in today’s sports markets, sport analytics graduates will be ready to use their analytical skills to make a difference.
COMP 140 - COMPUTATIONAL THINKING
SMGT 431 - ADVANCED SPORT ANALYTICS
STAT 315 - PROBABILITY AND STATISTICS FOR DATA SCIENCE
STAT 405 - R FOR DATA SCIENCE
SMGT 490 - SEMINAR IN SPORTS ANALYTICS
Program Learning Outcomes
- Familiar with the process of collecting sports data and managing databases.
- Perform rigorous statistical analysis on sports analytics questions.
- Visualize data analysis results.
- Communicate the models in sport analytics, both written and orally.
- Provide recommendations for business decisions based on data analysis.
- Develop and hone professional skills through classroom learning and experiential learning through a steady progression of internships with added responsibilities.