Saidur SikderFounder of GoalPro · The football AI guyConnect on LinkedIn ↗
This isn't a conventional CV. It's the story of how I went from studying computer science to working in technology, leading AI products and founding GoalPro.
I knew I didn't necessarily fit into a specific role, so I created my own.
Back in 2012 and 2013, Liverpool were nowhere near the club they are today. We were fighting for seventh or eighth place, watching City and Chelsea spend money like it grew on trees. Every proven, world-class striker cost fifty or sixty million and wanted Champions League football. We had neither the cash nor the pull.
But I can't just sit in a problem. If we couldn't win the game everyone else was playing, was there a different game we could play? There are thousands of professional footballers in Europe. Scouts can't watch them all. Statistically, there had to be brilliant players nobody was looking at.
So, late one night, I opened Squawka — one of the first sites where a normal fan could filter and compare players by their stats. Instead of searching for a name, I searched for a profile. I took the striker I admired most, Sergio Agüero, and set the filters to a range around his numbers.
What I was really asking the data was: who else in Europe plays like this — that nobody's talking about?
1 · Pick a reference player
2 · Filter to a range around his stats
3 · See who comes back
An illustration of the method, not the original screen.
In his first season at Palermo. The kind of number that makes a traditional scout close the file and move on: “This kid can't finish.”
Touches in the box, shot patterns, finding space in dangerous areas — everything elite strikers do. He just wasn't converting yet. Finishing is often the last thing to click.
Dybala explodes: 13 goals and 10 assists for an average Palermo side.
A big-money move to Juventus, Serie A titles and a brilliant career.
The data wasn't telling me what Dybala was. It was telling me what he was about to become.
It took me years to realise that what I did that night — define a profile, query the data, find the undervalued outlier, and understand why the surface stat was misleading — is the everyday job of a recruitment analyst. Liverpool went on to build one of the best data science departments in football, and it helped take them to Champions League and Premier League titles. I was just a decade early and several pay grades short.
From learning to code, to building products, to leading AI teams, to founding my own start-up — each chapter built on the one before.
City St George's, University of London
Studying the foundations of computing, programming and technology.
Is a CS degree enough? →Developing experience in building products and working across technology organisations.
Leading teams, delivering data and AI products, and solving complex business problems.
Applying those experiences to a problem I'm passionate about: making grassroots football smarter through AI.
Explore GoalPro →How I built it →I want to transform grassroots football through AI research and product development that uses computer vision, machine learning and physics.
What's next for GoalPro →“Your career doesn't have to follow a straight line. You can start by learning to code, move into building products, develop expertise in AI and eventually create something of your own.”
In one decade, analytics went from “that'll never work here” to a core part of every serious club — recruitment, tactics, fitness, set pieces. If a fan with a free website could spot Dybala in 2013, imagine what's possible with the tools we have today.
I was doing data science before I knew the words for it, because curiosity met a problem I cared about. If you're tinkering with something at midnight that feels like “just messing about”, pay attention to it. That might be your career whispering at you. It was for me.