Interview With NFL Network Analyst and Game Theory and Money Podcast Co-Host Cynthia Frelund


Cynthia Frelund joined NFL Network in 2016 as an analytics expert, providing her unique insight into the game on NFL Fantasy LIVE and GameDay Morning. She is also the co-host of the Game Theory and Money podcast. Prior to joining the NFL, Cynthia worked at ESPN and Disney. She graduated with a Masters of Business Administration and Masters in Predicative Analytics from Northwestern University.  

This interview has been edited for clarity and length.

Why do you want to pursue a career at the intersection of sports and analytics?

I am huge sports fan, but my path into the NFL was through Anthony Noto who was the CFO of the NFL (now the COO at Twitter). Before he was at the NFL, I used to read his Goldman Sachs equity research reports and I loved the way he structured his thoughts, and he was smart and it was interesting to listen to what he had to say. Given my background in finance and strategy and my passion for sports, working at the NFL was a great opportunity. 

Why the NFL?

The impact on analytics in baseball is pretty widely accepted. Use of analytics in the NFL is far more nascent. We are kind of geeks in a corner in the NFL. I own that. I like that I could ask larger strategic questions and have the opportunity to be impactful in the space. It is exciting to be a pioneer in a new market.

I saw that I really had an opportunity to focus on bridging the sports performance and business sides in the NFL. The NFL has unique performance valuations. Unlike the MLB or the NBA, the NFL has a hard salary cap. Looking at the on-field product and what coaches have to do to win a game is also very intriguing.

How do fans interact with what you are doing?

I am really lucky in that the work I did at ESPN prior to the NFL and at the NFL I have great support from my executives. I have really good producers that are able to take complex concepts and distill them into good stories. No one needs to read or listen to a PhD dissertation on a pregame show.

Yet, people want to know the significant information. What I provide is the opposite of the hot take. It is a logical argument. There is no Cynthia-bias in it. They are getting their own [Cleveland Browns Chief Strategy Officer] Paul DePodesta. I have seen fans go deeper into the math throughout the years. It is awesome, and my favorite part of the job.

What technology do you use?

I code in everything from Python to R to relational databases. I am pretty good at using new tools to solve problems and answer questions. I also use Open-Source video tools (most familiar with tensorflow). Computer vision models are also great.

In particular, it is cool to use deep learning and video to look at shapes and angles of players in video. It allows me to create the “waist bender” metric for offensive line play. Offensive linemen that can keep hips parallel and stay low are better at protecting quarterbacks because they do not lose leverage on their defensive counterparts. I was able to map NFL performance back to the NFL combine 40-yard dash results to find elite, above average, average, below average, and well below average waist benders. The lowest waist benders are the best at protecting quarterback. If you can keep your center of gravity low for the first ten yards during the 40-yard dash that is good (or a low waist bender) and if not it is bad (a high waist bender). You can see it as they run the 40 in the video and map the results using video. It is almost a continuous variable which shows that the lower you can stay, the better you will be at protection.

How important is communication in what you do?

I would not be able to get my job done without my knowledge of analytics, but I think it is like 60/40 communication. You would like to think that you can just be amazing at this, but it’s not enough. You must be able to tell the story of your findings, but you really need to be able to communicate in order to figure out what answers someone (a coach, etc) wants to explore. Choosing the right questions to explore is the key and you have to ask the people who would need to execute these findings what they care about and why.  

Do you play your own fantasy team? How does it do?

I have a few fantasy teams. The one on is difficult to pay attention to because I have to be on-air right before players lock and games begin. It is more important for other people to get the information than to use the information for my own team. In my one team that is very competitive, I have a bot to sub players in and out because my show is on right before the games start.

What the biggest misconception about what you do?

The biggest misconception is that analytics is like a bunch of listed statistics, and I can read them and they are all equally important or not important. The point is to put situations in context using data and take bias out of it.

Where is analytics in the NFL moving to in the future?

Safety is a big deal. Between the sports science technology with biometrics and training metrics there is a lot going on with each team. There is a lot of cool data showing where we can find situations where safety can be improved. For example, rule changes and information gathered and distributed about when and where injuries occur. It is really cool to see how data has and continues to help.