In this post, guest author Scott McLean explains the characteristics of a complex systems and how systems thinking can be utilised in the...

This post is based on a recent VALD online workshop on Preseason Preparation and the VALD eBook 'Practitioner's Guide to Preseason',...

This post delves into the research on the Acute Chronic Workload Ratio and if it can be used to predict injury.

This PhD Pinboard article by Paolo Perna explores how staff can better structure hamstring injury RTP decisions using a multi-phase,...

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

This excerpt is taken from the VALD eBook 'Practitioner's Guide to Preseason', which covers the fundamentals of planning preseason.

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 explores how AI-driven analytics of MRI scans enables more detailed insights into body composition and musculoskeletal health.

Here we discuss the Premier League Festive football calendar and consider the recovery and travel demands for each club.

This post discusses how to use the VALD Performance ForceFrame to measure shoulder strength in internal and external rotation.

This video will show you how to use the VALD Performance ForceFrame to measure strength in the hip and groin area.

In this video, we're going to discuss hamstring testing, and specifically the Nordic Hamstring Exercise (Russian Leans) strength test.

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

According to the Pareto Principle, 80% of results will come from 20% of the inputs. So what does this mean in sports science & performance?

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

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

AI providers in sports science need to intentionally craft their data visualisation designs to provide explainable & actionable outputs.

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.