This post explores the Training Adaptation Predictability Problem & its implications for monitoring athlete training programmes effectively

This post explores the potential for screening tests to predict sports injury and how they fit into an injury risk minimization framework.

This post explores how sports science practitioners can navigate the tension between complexity and simplicity in their communication.

This post provides sports practitioners with an introduction to artificial intelligence and machine learning in sport.

This article delves into the science behind Myocene and its potential application in athlete monitoring programmes.

How do moderators and mediators shed light on the complex interplay between workload and injury in sports science?

This blog post discusses the importance of proactive training load management in times of fixture congestion in professional team sports.

This post takes you to my new podcast episode with One Track Mind, talking about maximising impact as a sports performance practitioner.

Our new publication is out in SCJ now: Selection of Key Performance Indicators for Your Sport and Program: Proposing a Complementary Process

My comment on Zone7’s white paper: The Importance of Workload, Strength, Recovery and Environmental Context Data in Injury Risk Forecasting

Adam Grant's book, Think Again, delves into rethinking and is important for sports science to consider how they think.

The book "Risk: A User's Guide" highlights that we cannot eliminate risk but must focus our energies on boosting our “Risk Immune System”.

Here you'll find a link to my new free report with Zone7, entitled Applications of Artificial Intelligence within High Performance Sport.

Is it Man vs Machine when it comes to using artificial intelligence with athlete training load management, or can we use a hybrid approach?

Sports scientists want to unpack the black box in sports technology but how can this work with artificial intelligence (AI) data science?

Why context is key in sports science data, and therefore any AI system too. But we should beware when our so-called context becomes bias.

Is the 'Big Data' collected in sports science big enough to train Artificial Intelligence models? Is the data quality clean enough?

Terms like AI & Machine Learning are poorly understood. With Zone7, we have put together an AI dictionary for sport science practitioners.

When a measure becomes a target, it ceases to be a good measure. As sport is overflowing with measures and targets, this requires exploring.

Thanks to everyone who responded to my appeal to canvas industry opinion on artificial intelligence (AI) in high performance sport. I...