The Backroom Staff - Data Analyst: Shuyao Chen

Data Analyst: Shuyao Chen

Football as art and storytelling through data

Despite data analysis being one of the fastest growing areas in football, it’s still pretty rare to see something actually unique.

Shuyao Chen initially came to my attention through her blog and LinkedIn posts where she often shares analysis on advanced performance and physical metrics - the kind I haven’t seen elsewhere.

Turns out, her background is even more interesting! Her previous work includes success as a game developer - where she created football related games that reached ~100,000 users - and work as a journalist where she interviewed some of football’s biggest names.

In this interview, Shuyao tells me about her career and mission to tell better stories through analysis.

The interview has been condensed and lightly edited for grammar and clarity. 

Read on thebackroomstaff.com 

[ Background ]

I originally studied computer science and was intent on becoming a game developer — or more precisely, an interactive artist. However, my path changed dramatically after watching the 2014 Champions League final. It was then I realised that football itself is the ultimate form of interactive art: dynamic, emotionally charged, and profoundly human. From that moment, I began to explore how I could bring my technical and creative background into the world of football.

[ Your experience as a game/app developer ]

Game development was my first deep creative pursuit: a way to bring joy, emotional resonance, and anticipation to players. I saw it as a powerful storytelling medium that demanded a blend of programming, visual design, music, and systems thinking. These skills still serve me well today. More broadly, I believe gaming has been a major catalyst for technological progress. Just look at Nvidia’s evolution from a graphics card manufacturer to a leading force in AI. It taught me that user experience and interactivity can drive entire industries forward.

[ What are some of the differences between building for football audiences vs a 'normal' gaming audience? ]

This is a fascinating contrast. Gaming audiences typically seek challenge, immersion, and progression. They value finely tuned feedback loops and systems that reward mastery.

In football, the user experience is quite different. Especially depending on whether you’re building for fans, coaches, or decision-makers.

Fans often crave a sense of connection to players, clubs, and moments. They consume content that is emotional, real-time, and narrative-driven: line-ups, live stats, match previews. Clarity and immediacy matter more than complexity. Coaches and analysts, however, require contextualised, scenario-specific data that helps answer tactical or performance-based questions. Football is not just about numbers or flow states; it's about sense, where perception, judgement, and timing converge under pressure.

[ You were also a football journalist with Tencent? ]

It was a remarkable experience. I covered the Premier League, Champions League, and La Liga, interviewing figures like Jürgen Klopp, Pep Guardiola, and most of Liverpool’s first team. I was present at Anfield when Liverpool secured their first Premier League title in 2020, a surreal moment during the pandemic.

That said, I gradually became disillusioned with this job. Many of the responses from interviews felt scripted, lacking depth or genuine insight. I came to realise that traditional journalism often struggles to go beyond surface-level narratives, which deepened my desire to tell better football stories through analysis.

[ Then you started Typewind – your own consultancy? ]

Yes, Typewind started quite organically. While I was working as a journalist, a club owner discovered my background on data science. Then I was asked to advise on recruitment and performance analysis, and that was the beginning. Today, we focus primarily on performance and recruitment analysis for clubs and private clients such as coaches or agents.

We don’t actively market and most clients come through referrals. This allows us to keep our work highly personalised and research-focused. Our long-term aim is to pioneer advanced models of physical performance and contextual analytics, unconstrained by commercial pressures. We believe in illustrating football through data, not in reducing it to spreadsheets, but in exploring the edges of what data can reveal about the game.

[ Why should clients come to you/smaller advisories/freelancers over larger firms? ]

Because we care. In football, you’re not just dealing with results. You’re dealing with the emotional volatility of a high-stakes environment: anxiety, anger, exhaustion, elation, and sometimes despair. We understand that. Our consultancy is built around being responsive, human, and deeply embedded in our clients’ day-to-day needs.

We don’t just deliver reports; we offer reassurance, clarity, and honest partnership. Whether it's helping a coach adapt to a new opponent or giving a director peace of mind over a recruitment shortlist, we bring not just insight, but empathy.

[ A lot of your work focuses on physical and tracking data, this feels pretty niche still? ]

Mainstream football analysis often overlooks physical data, largely because most public datasets only include event-based data. Yet physical performance like distance covered, high-intensity efforts are often the truest reflection of a team's tactical identity and individual readiness. It’s not about the total kilometres; it’s about when, where, and how those kilometres are spent.

The next frontier is tracking data. Its potential to support coaches and recruitment teams is enormous, from spatial occupation to pressing structures and transitional patterns. But tracking data is expensive, technically challenging, and often hard to get access to. Unfortunately, many academic efforts in this area prioritise algorithmic novelty over footballing relevance. Without real football insight, even the most advanced models risk becoming irrelevant.

To truly progress, we need more open access to high-quality tracking data and a stronger bridge between researchers and practitioners. Only then can we fully realise what football data science is capable of.

[ You've recently also joined Angstrom - a betting data company - why? ]

I’m excited to be part of Angstrom, where I’m gaining insight into the mechanics of a sports betting company, from how data-driven models generate live odds across thousands of markets, to how customer behaviour is monitored for integrity and risk. It’s a fascinating world where latency, precision, and prediction meet. It also gives me a sharper sense of how football data is used outside the performance domain.

[ What do your future goals look like? ]

Remain curious. Keep exploring. Stay close to the pitch. I want to continue blending creativity, high quality, and empathy to tell better football stories, support better decisions, and push this industry in a more human direction in the AI era.

Follow Shuyao on LinkedIn and let her know you enjoyed the interview!

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