Interview with a ...
Sports statistical analyst
BLS Fast Facts: Statisticians
- May 2014 employment: 26,970
- 2012–22 projected growth: 27 percent
(much faster than average)
- May 2014 median annual wage: $79,990
(higher than the $35,540 median wage for all workers)
- Education typically required at entry level: Master's degree
- May 2014 top-employing industries: Federal executive branch; scientific research and development services; management, scientific, and technical consulting services; colleges, universities, and professional schools; state government.
Note: Employment, wage, and industry data exclude self-employed workers.
What do you do?
I create mathematical models to evaluate players and teams from lots of different sports so I can project performance. The job starts with collecting data. I build programs that automatically find and extract publicly available data from official and fan sites.
Sometimes I use a paid data service that records, organizes, and cleans the live-game data for me. This makes it easier to compare the data. If I put bad data into the model, I’d get bad predictions.
Next, I use a lot of statistical models to analyze the data and simulate how different changes in the game might affect a team’s chances of success. Then I optimize the model to get better results. For example, I might tell the model to build an optimal roster around a specific player.
Last, I build online tools to empower average users and businesses to play around with the data. They might, for example, rank players’ performance or project the outcome of different team matchups.
How did you prepare for your job?
My background is in statistics and probability. A lot of analysts have a graduate degree in statistics. In college, I majored in math and took some stats courses. But the course that has helped me most was on probability theory.
I also learned to do computer programming, which is not essential, but I highly recommend it. I didn’t know any when I started out, but it has been extremely helpful in making sense of the data.
How did you get started?
I’ve always liked sports and math but never thought about combining them. In a book, I found a footnote about a guy who showed mathematically that, in football, passing was better than running the ball. But all the professional teams were going against that advice.
I found and emailed the guy from the footnote, asking for advice. Fortunately, he had just started working for a pro team, and he gave me some projects to work on while I was still in college. Most of it was menial, but that got my foot in the door.
Talk about how you took initiative to help move your career forward.
I knew that if I could create an opportunity for myself, I could prove my value. Whenever I attended a conference, I’d make a list of people I wanted to meet and offered to help with any extra work. That way, when a new job opened up, they’d think of me.
I contacted people to see if they needed help, even if the work was unpaid. The money didn’t matter, I was just excited to be part of the team. Then someone passed my name to a pro team that was starting a new analytics department, and I started there while still in school.
So networking played a part?
Networking is important. This is a competitive industry, and most people are willing to work for cheap. And sports teams tend to hire internally, asking their employees if they know someone first.
What other skills have helped you?
The ability to communicate information effectively is the most important skill when dealing with anyone outside this field. You have to explain complex mathematical concepts and why they’re important, sometimes face to face and other times through blog posts or articles.
What do you like most about the work?
I’m a huge sports fan and love watching sports for a living. I get to work in something I love, and my work can help a team win. Sometimes, I’ll act as a consultant to a team, helping to come up with best plays, analyze player performance, and assess the dollar value of a player. With that information, the team can make decisions and may improve its chances of winning.
I also like problem solving. You’re building tools that help teams perform better and win more often. Solving those problems is a cool feeling, and I find it exciting to be a part of a team’s decisionmaking process.
Any surprises along the way?
When working with big data, the hard part is not necessarily learning the right technical skills but knowing which questions to ask. There’s so much data that it’s essential you know what you’re looking for.
You also face resistance from the sports community. Many sports teams, especially in football, still don’t understand the benefits of analytics. Some people think that because you didn’t play professionally, you don’t understand the game. It can make you feel like you’ve done all this work and no one cares.
What’s your best advice?
This field is still self-made, self-taught. There are many books and blogs dedicated to the statistical analysis of every sport. And you can use independent study or unpaid opportunities to gain experience and show that you’re interested.
Make an effort to contact the teams and people you’d like to work with. You don’t have to wait for a team to call. The best way to find work is to put yourself out there.
Dennis Vilorio, "Sports statistical analyst," Career Outlook, U.S. Bureau of Labor Statistics, September 2015.