Advances in Performance Analysis and Monitoring in Sport and Exercise: Bridging the Research–Practice Gap
A special issue of Journal of Functional Morphology and Kinesiology (ISSN 2411-5142). This special issue belongs to the section "Athletic Training and Human Performance".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 1821
Editor
Interests: soccer; sports performance analysis; research methodology; biostatistics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Rapid advancements in event data collection technologies, tracking systems, wearable sensors, and analytical approaches have positioned performance analysis and monitoring as central components of contemporary sport and exercise science. These developments have enabled the capture of large-volume, multidimensional data across physical, technical, tactical, and psychological domains, offering unprecedented opportunities for research to understand and optimize performance.
Despite the exponential growth in relevant scientific publications, a persistent gap remains between research and practice. This can be attributed to several factors, including the use of overly simplified performance indicators in a multifactorial context, limited translation of findings into actionable guidelines, conflicting evidence across studies without a systematic explanation, and insufficient control or integration of contextual variables.
This Special Issue aims to bridge the research–practice gap by promoting integrative, methodologically rigorous, and practically relevant approaches. In particular, we encourage contributions that achieve the following:
- Apply multivariable statistical models and machine learning methods while ensuring interpretability and practical relevance;
- Incorporate contextual variables into performance models;
- Develop integrated frameworks that account for technical, tactical, physical, and psychological dimensions of performance;
- Translate findings into actionable insights for coaches and practitioners;
- Utilize quantitative, qualitative, and mixed-methods research designs;
- Provide in-depth analyses through case studies of unique or rare performance scenarios;
- Employ randomized controlled trials to support decision-making processes;
- Synthesize evidence through systematic reviews and meta-analyses;
- Adopt narrative approaches that go beyond description to critically develop theoretical frameworks.
Topics of interest include, but are not limited to:
- Explanation and enhancement of individual and team performance;
- Monitoring of training load in relation to performance and injury risk reduction;
- Athlete well-being;
- Complex systems and ecological dynamics;
- Performance profiling of athletes and teams;
- Applications of performance analysis and monitoring in coaching and applied sport settings.
To further support the goal of bridging the research–practice gap, authors are strongly encouraged to enhance the practical accessibility and applicability of their work. Specifically, submissions should aim to include a dedicated section outlining clear practical implications for coaches, analysts, and applied sport scientists. Where appropriate, the inclusion of applied examples, case-based interpretations, or implementation guidelines is highly recommended, ensuring that research findings can be more readily translated into real-world practice. Finally, authors are encouraged to provide a graphical abstract (infographic) to facilitate effective communication of key findings to non-academic audiences.
By encouraging interdisciplinary perspectives and emphasizing both scientific rigor and practical relevance, this Special Issue seeks to bridge the research–practice gap by promoting actionable, context-sensitive, and methodologically robust approaches to performance analysis and monitoring. In doing so, it aims to support more effective decision-making in real-world sport and exercise settings, while also identifying key directions for future research.
Dr. Spyridon Plakias
Guest Editor
Manuscript Submission Information
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Keywords
- sport analytics
- performance monitoring
- training load monitoring
- injury risk reduction
- contextual variables
- ecological dynamics
- multivariable statistical models
- machine learning methods
- mixed-methods research
- performance profiling
- data-driven coaching
- applied sport science
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