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From PIRI (The Performance Intelligence Research Initiative)

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).

Some of the key findings include:

  • Travel Matters: Distance matters as much as home advantage. Trips over 100 km significantly impact match results.

  • Quality of the Opposition: The Elo gap between a team’s level (as measured via the Elo ranking) and the opposition’s is important.

  • Recent Form Rules: The last five matches & overall season performance matter—a team’s momentum shapes each game.

  • Managerial Impact: Manager tenure influences performance. There’s a sweet spot before diminishing returns kick in.

  • Rest is Important: Less than three days rest affects the top team’s edge. It’s a strategic factor, not just a break.

  • Squad Stability: Frequent rotations affect outcomes—cohesion matters. Balancing rotation with consistency is critical.

RECENT STUDY

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

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

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Announcement

Kitman Labs Joins ‘More than Equal’ Quest To Develop First Female Formula 1 Champion

More than Equal’s mission is to close the gender gap in motor sports and find and develop the first female Formula 1 world champion. They will now have an advanced operating system to centralize data for female drivers participating in More than Equal’s pioneering Development Programme.

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