Sports Analytics

I've compiled some helpful resources in this tab for students interested in research and/or a career in sports analytics. 

If you are looking for sports analytics jobs or internships, I recommend monitoring LinkedIn, TeamWork, and this list curated by Dr. Scott Powers.

To make yourself competitive for sports analytics jobs, I recommend that you do the following:

• Take statistics and data science courses

  • Build your skills in R and/or Python

  • Learn more statistical methods

• If your university offers a sports analytic course(s), take it

• Get involved with statistics, data science, and sports analytics student groups at your university

• Learn more about sports analytics and read others' sports analytics analyses

  • For example, articles on FanGraphs or American Soccer Analysis

• Personal research projects

  • This is the best way to make yourself a competitive applicant for sports analytics jobs. Sports analytics research projects demonstrate your technical skills and your ability to think critically through a sports problem.

  • On your resume, be sure to highlight any sports analytics projects you've completed. I'd recommend creating a separate 'Projects' section where you can describe these projects in detail.

If you are a UT student, I also recommend that you: 

🐂  Take my sports analytics course (SDS 375). Typically several research opportunities emerge from that course.

🐂  Get involved with student sports analytics organizations, such as:

• Business of Sports Student Organization