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The analytics-practice gap: why sports data fails to translate into coaching decisions
1Department of Physical Education, Sports Technology Laboratory, Seoul National University, Seoul, Republic of Korea.
Frontiers in Sports and Active Living
|July 22, 2026
Summary
Sports analytics can improve coaching decisions by bridging the analytics-practice gap. Focusing on actionable insights, rather than just data, is key for effective training and player management.
Area of Science:
- Sports Science
- Performance Analysis
- Coaching Science
Background:
- Data-rich environments in sport are expanding due to advanced tracking and analytical systems.
- Coaching decisions often still rely on experience and intuition, despite available data.
Purpose of the Study:
- To examine the disconnect between sports analytics and coaching practice (the analytics-practice gap).
- To argue that the gap stems from limited actionability and usability of analytical outputs, not insufficient data.
Main Methods:
- Conceptual analysis of the analytics-practice gap.
- Examination of the limitations of current sports analytics outputs for coaches.
- Proposal of a 'decision-first' analytics approach.
Main Results:
- The analytics-practice gap is not due to a lack of data, but the way data is presented and its limited actionability.
- Performance indicators often describe events but don't guide coaching actions.
- A shift towards 'decision-first' analytics is needed.
Conclusions:
- Addressing the analytics-practice gap requires defining coaching problems before selecting metrics.
- Integrating contextual, technical, tactical, and physical data is crucial.
- Effective communication of analytics to support practical interventions enhances value.
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