What working with data analytics taught someone who knew nothing about football
When I interviewed with Track160 for a content writing position, the man who would later accept me into the job noticed a huge gap in my resume. He asked why someone with no real experience with football, no interest in football, and very little interest in the world of sports that were not competitive Starcraft 2, would be interested in this job. My reaction was a confident “I can learn”. I did.
There were a lot of things that made football grow more interesting to me, and it took me some time to understand why. I like to credit Ted Lasso with it. It was definitely very funny when, a few weeks after I asked my boss what a False Nine was, Ted Lasso asked the same question. In general, that show definitely helped me, as a lot of the humor does revolve around a newcomer to football learning about it. I was a less mustachio’d, less irresponsible Ted Lasso (Seriously, how does a football coach know so little about football two years into coaching it?).
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My path into football was very unique, I think. In joining Track160, I started with some access to a highly advanced analytics database, equipped with tools far beyond my comprehension. I had precise measurements before I knew what it meant when a team lacked a natural striker. I was like someone with an Oxford English Dictionary who could only read Mandarin, learning about dangerousity before learning any name other than Messi. But in looking at the world of football analytics, it doesn’t seem all that strange.
What actually created the interest in football?
Every article about a club hiring some scientist as an analyst includes the analyst’s previous profession, and it’s seldom “football player”. Football data analysts these days are astrophysicists, AI experts, financial advisors, and more. My personal favorite is one I recently wrote about, Ashwin Raman, who admitted to not liking math. You don’t need to have a head for numbers to get into football analytics, though I believe that as a doctor of mathematics, Catherine Pfaff has an advantage. Most football analysts are not the people you’d expect to be interested in football - though the idea of making Moneyball with the characters from Green Street Hooligans is very appealing. And somehow, getting all of the data and looking at football as a game with internal data and logic to it, one that isn’t as dissimilar to esports as I’d thought, made it make much more sense to me than it did in my years of seeing people cheer in sports bars.
Does this make me a data analyst? No. I’d need to work much harder to get there, and it’ll be a while until I have the right amount of knowledge. I still have my work checked by people who understand the game. However, as time goes by, they correct me less and I have more knowledge of the game.
"A game with internal data and logic to it". Images from Track160's fully-automated analytics solution
It's not that I have abandoned my love of Starcraft 2; during the recent Pig Sty tournament, watching Maxpax, the upstart player everyone thought was a nobody a year ago, innovate against Reynor, the reigning champion, was wonderful. But I’ve learned the beauty and thrill of watching Mo Salah prove that he is a living legend, and there is no small satisfaction in seeing data analysts say as much. Even more so, I’ve started to look into the information about clubs and trying to do my own armchair analysis, all of it god awful. Maybe one day I’ll be passable.
Football is a beautiful game. As someone who was very much an outsider to it a few months ago, I am glad Track160 took the risk of taking me on. Not just because of the employment, not just because I get to be there with a technology that is revolutionary in its abilities and goals, but because I got an introduction to a sport in a way that made sense to me. Whatever else I take from working here, I’ve got football with me.
Watch Track160's CEO Eyal Ben-Ari's presentation at the SportBiz Europe event