Who am I?
Sport, software, and the search for better decisions
My name is Sigurdur Hallur Jonsson. I'm an Icelandic software engineer living in Norway with a lifelong passion for sports, technology, and data.
Sport has always been a major part of my life. Growing up, I played football and volleyball, and today I spend much of my free time on the golf course. What fascinates me most about sports is not only the competition itself, but the constant search for improvement. Why do some players succeed? Why do some teams consistently outperform others? Which decisions create better outcomes?
Those same questions are what originally drew me toward analytics.
Professionally, I work as a software engineer, primarily with Java, PostgreSQL, APIs, and cloud technologies. Outside of work, I have spent the last several years building sports analytics projects, collecting data, experimenting with machine learning, and exploring how data can support better decision-making.
What started as a hobby gradually became a genuine passion.
Why GoalUnit?
Where football and engineering meet
I first heard about GoalUnit through the Dr. Football podcast.
As soon as I heard people discussing a company operating at the intersection of football, recruitment, analytics, and decision-making, I immediately looked it up. The more I learned about GoalUnit, the more it felt connected to the things I have been interested in for years.
Football has always been one of my biggest interests. Software engineering became my profession. Data became my obsession. GoalUnit seemed like a place where those three worlds meet.
When I saw the opportunity to work with the provided datasets, I knew I wanted to build something.
Why this project?
Recruitment as a decision problem
Many football analytics projects focus on matches, results, and prediction.
For this project, I chose to focus on players and recruitment. I wanted to explore how event data, player data, and club financial data could be combined to support practical football decisions.
Questions such as:
- What type of player is this?
- Which players have similar profiles?
- Which players may be undervalued?
- How can clubs discover alternatives they may not have considered?
- How can recruitment decisions be supported by objective data?
These are the questions that interest me because they sit at the intersection of football knowledge, analytics, and real-world decision making.
Creativity and curiosity
Every dataset contains more opportunities than are immediately visible
The datasets provided for this challenge quickly turned into much more than a single project idea. As I started exploring the event data, player data, and club financial information, I found myself continuously discovering new questions I wanted to answer and new tools I wanted to build.
- Could we identify player archetypes?
- Could we discover undervalued players?
- Could we compare clubs based on recruitment efficiency?
- Could we find replacements for specific player profiles?
- Could we combine football performance with financial data to identify market opportunities?
What started as one idea quickly became ten. The challenge is deciding which ideas are worth pursuing and turning them into something useful.
This project only explores a small subset of the ideas that emerged while working with the data, but that process of exploration is exactly what excites me.
I enjoy taking a dataset, asking questions, experimenting with concepts, and building tools that help people make better decisions.
What excites me about GoalUnit
Helping clubs decide what to do next
Many analytics platforms focus on explaining what happened.
What excites me most is helping clubs decide what to do next. Recruitment, squad planning, talent identification, and resource allocation are areas where good information can create a genuine competitive advantage.
I am not a football analyst who learned to code. I am a software engineer who became fascinated by football data.
What I bring is a combination of technical experience, curiosity, and a genuine interest in understanding the game through data.
This project is therefore more than an application exercise. It is an example of how I approach problems, how I think about football, and the type of work I would genuinely enjoy contributing to.
If nothing else, this challenge gave me an excuse to spend a weekend combining football, software engineering, analytics, and problem-solving, which is probably the clearest description of my interests you could ask for.
Tags
Focus areas
- Football Analytics
- Sports Analytics
- Software Engineer
- Data Engineering
- Data Visualization
- Recruitment Analytics
- Sports Technology
- Java Developer
- Machine Learning
- Sports Enthusiast
