About

I’m a data scientist with a PhD in statistics and a background in elite sport.

Most of my professional work has been in Bayesian modelling and applied statistics — building models, designing experiments, and figuring out what data can actually tell us. I’ve spent a lot of time thinking about uncertainty, individual variation, and why averages so often mislead.

I’m also an athlete. I competed in sprint kayaking at an elite level for several years, and training remains a central part of my life. Sport has shaped how I think about data: I’m less interested in what works on average and more interested in what works for a specific person, in a specific context, adapting over time.

These days I’m focused on sports performance analytics — particularly periodisation, load management, and single-subject methods. I’m interested in how athletes and coaches can use data without being buried by it, and how statistical thinking can sharpen intuition rather than replace it.

This site is where I write about those ideas.