Here at Level, we love it when we hear our graduates are using the skills they acquired in class in their day-to-day life. Jordan Sperber took his love of sports and interest in analytics and turned it into a full-time career. We sat down with Jordan to discuss his journey:

What initially sparked your interest in data analytics?

I first became interested in data analytics after reading the book Moneyball: The Art of Winning an Unfair Game early on in high school. The book covered the story of how the Oakland A’s used analytics to find undervalued MLB players. After reading that, I continued reading about sports analytics on the internet and started doing some of my own research. At that time, I took my first statistics class in high school and applied a lot of what I was learning to sports.

Tell me about your blog. When did you start it? What is it about?

I started my blog, The Hoop Vision as a junior in high school. I put it aside for most of my senior year but then brought it back in college in full force. The blog is centered around college basketball analytics. I write blog posts heavily focused on data and film to analyze college basketball teams, players, and trends. In the last year or so, I have shifted to doing the same type of analysis but in the form of a newsletter instead of on the blog. Through the newsletter, I’ve been able to network with more people in the college basketball world.

Would you attribute your blog as a major part of your success for your data career?

Definitely. Early on in college, I had two Division 1 basketball coaches reach out to me after reading my blog. I stayed in touch with both coaches and even did some consulting while I was still an undergrad. Upon graduation, those coaches gave me my first two jobs in the industry. I started as a Graduate Assistant at the University of Nevada and then moved on to New Mexico State as Video Coordinator. In both cases, the blog enabled me to get my name out there and put myself in a position to get future jobs.

Tell us what a day in your life includes at New Mexico State.

The college basketball world is very seasonal. So from November to March our focus is on how to win games and get better as a team. From a data analytics perspective, that means using data to evaluate our team as a whole and all of our individual players. We also analyze our opponents and put together more effective game plans and scouting reports. Out of season, we use data analytics very heavily in recruiting. Not only do we evaluate potential new players to decide if we want to add them to our roster, but we also use analytics as a major selling point to land them. That means I put together presentations on how we will use data to take the recruit’s (and our team’s) game to the next level.

How did you first hear about Level and why did you take it?

I heard about Level just by googling different data science/analytics boot camps. I saw value in Level because unlike most boot camps, it was tied to a University like Northeastern. I took Level to further enhance my technical skills. The 2-month full-time setting was particularly attractive to me.

What skills from Level do you use on a day-to-day basis?

I have really built off of the R programming portion of Level for use on a daily basis. Those skills have helped me to automate more of my workflow and do things more efficiently. Furthermore, I am still using Tableau for some data visualization and SQL for database work. Both of which were covered during Level.

What is some advice you would give to people that are looking to get started in data?

I think my advice would be centered around the importance of building your technical skills up. A short-term boot camp like Level is a great way to jump-start those skills. For people looking to get into sports data, in particular, starting a blog (or even just a Twitter account) is a great way to network and get your name out. The sports industry is extremely competitive, but also an exciting industry. High-level technical skills in conjunction with good networking are necessary to advance in the field.

A lot of factors played into Jordan’s success. The best part is that Jordan was able to turn something that interested him in a career. He is a prime example of how it is never too early to start building a reputation and a digital data portfolio as he did with his blog. In conjunction with his blog, he was able to use his network from college to land his first two data roles. From there he sought to expand on his preexisting knowledge of data and hone his skills. Through Level, he was able to use what he learned with R streamline his day-to-day processes along with expanding on tools he had worked with previously. We are thrilled to hear Jordan is enjoying a career in a field he loves and that Level helped make that career even stronger.

Follow Jordan on Twitter at @hoopvision68


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