Tennis AI, live at the Grand Slams
Real-time analytics powering broadcast and coaching insight across the ATP/WTA tours and Grand Slam events.
I love data science, and I love sport — tennis and football especially. What drives me is building systems that bring both together in live settings: infrastructure that runs during a match, processes tracking data in real time, and turns it into products people actually use. The mathematical foundation came through a diploma in maths and a PhD in inverse problems, but the past eight years have been about one thing — shipping.
LLM applications, RAG systems and AI assistants that turn complex analytics into language teams can actually use.
Shot-quality models, win probability and tactical analysis — turning every rally into actionable intelligence.
The research core behind it all — recovering causes from data, using differentiable optimization like backpropagating through PDE solvers.
Real-time analytics powering broadcast and coaching insight across the ATP/WTA tours and Grand Slam events.
The foundational work on cognitive biases and dual-process theory — System 1 vs System 2 thinking.
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Why variability in human judgment causes errors across medicine, law and business decisions.
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How we mistake luck for skill. Essential reading on probability and risk perception.
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A poker champion’s guide to making better decisions under uncertainty — separating outcomes from process.
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The friendship between Kahneman and Tversky that revolutionized how we understand the mind.
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How the Oakland A’s used data analytics to compete against bigger budgets. Changed sports forever.
View on Amazon ↗A running list of the books and conversations that shape how I think about decision-making, probability and modelling the world.
Browse the full list →Interested in ML, generative AI, or sports analytics? I’m always happy to compare notes.