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Meet ESPN’s Benjamin Alamar

At Parse.ly, we often focus the people who are doing analytics behind the scenes — those trying to understand audiences and find trends in readership. But there are plenty of people doing exciting work using analytics to tell stories. At the top of that list is Benjamin Alamar, Director of Production Analytics at ESPN. Alamar has only been in the media industry since 2014, but there’s no one better for the job of creating metrics for sports fans. As a former NFL and NBA analytics consultant, and the founding editor of the first peer-reviewed journal for research in sports analytics, Alamar certainly has a place at the most valuable sports network.Benjamin_Alamar

Alamar will join some other analytics pros at a panel we’re hosting this week, but since he stands out from the crowd a little, we wanted to take some time to get to know him a little bit more.

1. Tell us about your role at ESPN. What do you do as the Director of Production Analytics?

My role at ESPN is assist my team in developing new metrics that will help our fans learn more about the games, teams, and athletes they love; work with our partners across all of ESPN’s platforms to ensure access to our metrics as well as education around the metrics, and to tell stories on all of our platforms on which our metrics can provide unique insight.

2. In an interview earlier this year, you said that it’s important to convey metrics in a simple, interesting way that audiences will appreciate, and that you want to “tell stories with metrics.” Can you give examples of how you do this?

A great example of this was the NBA Draft Projection model that we developed this year. One of our analysts, Zach Bradshaw, did a great job of building a very sophisticated model that is truly one of the best of its kind. We took all of the projections and probabilities that the model produced and boiled it down into four numbers for each player: odds that each player would be a Superstar, Starter, Role Player, or Bust in the NBA. This profile of each player immediately gives fans a clear idea of what the ceiling and floor for each player is so when their team makes a pick, they get a sense of what the team has done. One example of this is Justice Winslow. The model tells us that Winslow is unlikely to be a Superstar, but has a great chance of being starter in the league for a long time.

3. What are the biggest challenges that your analytics team faces?

Our team is in a great place now where different groups within ESPN are now coming to us and asking for more tools. In the past we have often had to push hard for groups to utilize what we have created, and now, more and more, people are asking us great questions and thinking about new tools that could help us better serve our fans. The challenge in that is that we have to think carefully about how we are prioritizing both these requests and the projects that we believe are important. We have a growing team, but certainly not the size of team that we need to do everything that we want to do right away, so we always have to think through which projects will best serve our fans.

4. You’ve spent the majority of your career outside of the media world. Now that you work for a media conglomerate, how do you use data differently than you did before? Do you need to think about analytics in a different way?

The principles are all the same, the difference is the questions and stories that the different audiences are interested in. For example, one of the first articles I wrote since joining ESPN was a look at Peyton Manning’s TD total throughout his career, compared to other great QBs in history this is not an issue or story any GM or Coach would care about, but the technique (in terms of adjusting TD totals for era to make comparisons valid) is an important tool that can be used in evaluating current players – which is something that GM’s and Coaches care about deeply.

 

Alamar and panelists from The Daily Beast, Vogue and Columbia University’s Tow Center for Digital Journalism will be discussing the many ways in which analytics are applicable to newsrooms and digital media organizations at tomorrow’s Summer Series event. If you can’t make it, be sure to follow the conversation between 6 and 9 p.m. EST on Twitter! #analyticsIRL