Evolving landscapes of artificial intelligence in sports: Insights from scientometric and altmetric analyses

Abstract

The rapid advancement of artificial intelligence (AI) has revolutionised various domains, including sports science. This study presents comprehensive scientometric and altmetric analyses of AI applications in sports research, providing insights into the field’s scholarly impact and online visibility. Beyond conventional descriptive mapping, this work integrates scientometric, altmetric, and sentiment analyses to develop a multidimensional framework for understanding how AI-driven sports research evolves, diffuses, and resonates across academic and societal domains. Scopus was systematically searched using title-based keywords related to “artificial intelligence” and “sports”. The search was restricted to English-language journal articles published between 2015 and 2024 and yielded 1469 records after rigorous screening. Methodologically, the study advances bibliometric practice by integrating citation indicators and keyword networks with altmetric analyses of online visibility and Python-based sentiment analysis, capturing scholarly impact, societal engagement, and public perceptions (positive, neutral, and negative) of AI in sports. Scientometric findings revealed sustained publication growth, with China emerging as the most productive country and the Journal of Intelligent and Fuzzy Systems and Computational Intelligence and Neuroscience identified as core publication outlets. The most cited article focused on sport-specific movement recognition using machine learning. An altmetric analysis demonstrated that X (formerly Twitter) serves as the primary channel for disseminating AI-in-sports research, whereas a sentiment analysis indicated a predominantly positive discourse, reflecting optimism regarding AI-enabled performance analysis, injury prevention, and decision support. The observed divergence between countries leading to scholarly output and those attracting greater online attention highlights structural gaps between knowledge production and societal uptake. Collectively, these findings contribute theoretically by clarifying impact asymmetries, methodologically by proposing an integrative evaluative approach, and practically by informing researchers, practitioners, and policymakers on strategies to enhance interdisciplinary collaboration, methodological rigour, and science communication in AI-driven sports research. • AI-related sports research has steadily increased from 2015 to 2024, with the highest publication peak occurring in 2022. • China was the top publishing country, and journal of Intelligent and Fuzzy systems was among influential outlets. • The most cited study focused on sport-specific movement recognition using machine and deep learning methods. • Social media especially X played a major role in sharing research, with the United States leading altmetric attention. • Sentiment analysis shows mostly positive views, indicating optimism for AI in sports science and strong engagement.

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