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From PIRI (The Performance Intelligence Research Initiative)

A Machine Learning Perspective on the Relationships Between Training Doses and Match Injury Trends

This study explores the link between high-speed running (HSR), sprinting, and injuries in elite football. With data from 12 European and MLS teams, we reveal key insights into training and injury prevention.

Using machine learning (ML) and explainable AI techniques, we were able to uncover, and interpret, the non-linear relationship between training dose and match injury occurrence

Some of the key findings include:

  • HSR and sprint distances peak mid-turnaround, particularly with 6+ day intervals.

  • High HSR and sprint distances, comparable to single-match demands, occur in longer turnarounds.

  • Notable differences among teams in HSR and sprinting loads.

  • New evidence that HSR and sprinting distances between 0.6 to 1.1 times the match load correlate with fewer injuries

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Factors Associated with Match Outcomes in Elite European Football – Insights from Machine Learning Models

This study examines the key factors influencing match results in European football, analyzing over 61,000 matches using Artificial intelligence (AI).

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Announcement

Kitman labs expands global collegiate partnerships with Loughborough University deal

The Loughborough Sport Athletic Department will now be able to integrate all medical and performance data into a single operating system.

This move aims to drive collaboration and eliminate information silos while also providing coaches, practitioners, and relevant stakeholders with a real-time, 360-degree view of each student-athlete.

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