Performance assessment using wearable sensors in tennis: a systematic literature review
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Published: July 22, 2026
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Page: 903-927
Abstract
Tennis is a high-intensity intermittent sport requiring accurate workload monitoring to optimize performance and reduce injury risk. However, evidence regarding wearable-sensor applications remains fragmented across sport science, biomechanics, and engineering disciplines. This systematic literature review synthesizes current evidence on wearable-sensor technologies, validation, analytical methods, and practical applications for real-time monitoring in tennis. The review followed the PRISMA 2020 guidelines. A structured Boolean search of the Scopus database identified 130 records published between 2016 and 2026. After screening by two independent reviewers (Cohen's κ = 0.87), 15 studies met the predefined eligibility criteria and were included in the qualitative synthesis. Methodological quality was evaluated using the FICO framework to ensure structured assessment of study focus, reporting quality, contextual relevance, and outcomes. Thematic synthesis revealed four principal findings: (1) inertial measurement units demonstrated the strongest validity for stroke detection compared with video reference standards; (2) machine-learning algorithms achieved stroke-classification accuracies ranging from 93% to 98%; (3) wearable sensors effectively differentiated stroke and locomotor workloads across playing conditions; and (4) physiological and positioning technologies showed greater measurement error than inertial systems. Overall, wearable sensors demonstrate substantial potential for performance monitoring, although further longitudinal validation, multisensor integration, and broader athlete representation are required before widespread implementation in coaching and injury-prevention practice.
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