11 Questions with Eoin O'Brien

The pursuit of wisdom in any walk of life quickly reveals that what you think you know is not nearly enough to get you to where you want to go. As I'm starting out in my football scouting journey I challenged myself to reach out to those already working in various roles in football to answer a short list of questions. My goal wasn't to get answers but relevant perspectives on the game within the game.

Here is Eoin O'Brien:

How did your first opportunity in football come about?

I haven’t had a role working directly in football at this point. I’ve started producing some of my own work in recent months, but I’ve been following data analytics in football for a long time. I’ve had a few very kind offers that I haven’t been able to accept right now, as I’m focusing on finishing a master’s degree within the next few months. I’d love to take up a role in football afterwards if an opportunity arises.

What attracted you to media/data/scouting? What’s more intriguing now names or numbers?

I’ve always been interested in numbers. Football has been a massive part of my life, so the two just ended up crossing over. My undergrad was a maths degree, so I’d always try to apply things that I learned to football.

I don’t think that you can separate the names from the numbers. For all of the great uses of data in football, you have to be able to recognise it's limitations. The best analysts are the ones who can look at the broader picture.

What type of player fascinates you? What caught your eye?

It fascinates me when the data doesn’t seem to match the eye test for a player. I think that these types of players are particularly interesting because it can either highlight shortcomings in our metrics, or highlight biases that we have when watching players. It’s not always an easy task trying to work out which one it is! Either way, it presents an opportunity to learn more about how we evaluate players. 

What is the biggest misconception you’ve found in this space?

I would say the idea that people who work with data are detached from others areas of the game. There’s an idea in some parts that data people don’t watch games, or consider the tactical side of the game enough. Good analysts can consider the broader picture and draw on the expertise of people in other areas.

If you could start over what skill would you build on first?

I would probably try to persist with R/python earlier. I have a lot of experience with both languages now, but it wasn’t easy to begin with. There is a steep learning curve at the beginning when you’re trying to learn a programming language and source data. I became a bit demoralised and ended up wasting time that I could have spent producing work. I wish that I had known that it gets a lot easier once you’re over that initial hill! 

What is more important domain knowledge or curiosity?

It’s good to have a combination of both and I think that they often overlap. Being curious and exploring new things often leads to a accumulation of domain knowledge. It’s always good to standard out with some original ideas too.

What is your favorite sports moment? Why?

I would have to say the 2005 champions league final in Istanbul. I liked football from an early age but I really fell in love with It and Liverpool as a club around that time. 

What coach or player would you give a lifetime contract to? Why?

That’s a tricky one.. I feel like an obvious answer here is a young Messi or Ronaldo. But a player could also get a serious injury and never be the same again, so plenty of risks to consider. I’d go for Pep as a manager. 

What advice would you give to someone wanting to get into this space?

Don’t be afraid to put your work out there for fear of not being the most knowledgeable or experienced person in the field. You can still make a positive contribution. 

There are plenty of people willing to lend a helping hand. Everyone has to start somewhere. 

Who is your favorite athlete? Why?

Messi. I just think that it’s hard to even grasp how good he is. He can make some of the most phenomenal athletes in the world look incredibly average. I'm delighted I got the chance to see him play live. 

What is your favorite quote or saying?

In keeping with the theme of this.. “All models are wrong. Some models are useful.” - George Box