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

This video discussing how the relationship between internal and external training load can be used to assess athlete fitness fatigue status

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

In this Sports Science Guide, we'll look at some of the key factors for sports science staff preparing for the NFL Super Bowl LVII.

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

With the 2022 FIFA Men's World Cup in Qatar over, we discuss how Premier League sports science staff can reintegrate their players.

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

In this video, we discuss athlete load monitoring & specifically, player tracking technologies, such as GPS, IMU, LPS, & Optical tracking.

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.

This post explains why athlete self report wellness questionnaires are a critical component of a load monitoring system, and how to implement them with your athletes and coaches.

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.

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

This post provides three action steps to help practitioners feel less overwhelmed by big data when monitoring athlete training load.

I'm excited to share a new review: Tracking Systems in Team Sports: A Narrative Review of Applications of the Data &Sport Specific Analysis

The Precision Practicality Tradeoff describes the compromise between these two factors. Here we discuss how practitioners can optimise this.

One group propose the terms load and training load breach “principles of science”, including the SI, & should be abandoned in sports science

No matter the constraints (opponents, time, turnarounds, locations), there is always an opportunity to put the team in a position to perform

The worst case scenario stemmed from practitioners & researchers seeking to understanding the most demanding passages of play. Is it valid?

This post outlines our new publication in the International Journal of Sports Medicine on how training load is used for athlete...