Harnessing Artificial Intelligence in Sports Training: Evidence from Romanian Professionals Using SEM Analysis

Digital technologies, including artificial intelligence (AI) and machine learning (ML), are reshaping the landscape of athletic training and performance assessment. Despite growing global interest, empirical research on AI adoption in sports remains limited in Central and Eastern Europe. This study investigates how Romanian sports professionals perceive and integrate AI-based applications and digital technologies into their training practices, and how these tools influence performance outcomes. Data were collected through a structured questionnaire distributed to 293 athletes, coaches, and sports academics. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), we found that perceived AI benefits significantly predict the use of AI applications (β = 0.211, p < 0.001), which in turn strongly predicts the adoption of digital sports technologies (β = 0.708, p < 0.001). The use of digital technologies was positively associated with higher self-reported performance outcomes (β = 0.268, p < 0.001). Group comparisons using ANOVA revealed significant differences in AI adoption by sport (football > basketball, p < 0.05) and education level (p = 0.007). These findings contribute to the literature on sports technology adoption by offering one of Eastern Europe’s first empirical, model-based studies. The study provides practical insights for coaches, policymakers, and sports technologists aiming to foster AI integration and digital innovation in high-performance athletic environments.

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Publication Details

Journal
Applied Sciences
Published
2025-08-11
DOI
https://doi.org/10.3390/app15168853
Citations
1
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
3.13
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article

Harnessing Artificial Intelligence in Sports Training: Evidence from Romanian Professionals Using SEM Analysis

Monica Stănescu, Andreea Trușcă, Rocsana Bucea-Manea-Țoniş, Luciela Vasile
1 citations
Applied Sciences
Sports Analytics and Performance
3.13
article

Harnessing Artificial Intelligence in Sports Training: Evidence from Romanian Professionals Using SEM Analysis

Monica Stănescu, Andreea Trușcă, Rocsana Bucea-Manea-Țoniş, Luciela Vasile
article en
1 citations

Abstract

Digital technologies, including artificial intelligence (AI) and machine learning (ML), are reshaping the landscape of athletic training and performance assessment. Despite growing global interest, empirical research on AI adoption in sports remains limited in Central and Eastern Europe. This study investigates how Romanian sports professionals perceive and integrate AI-based applications and digital technologies into their training practices, and how these tools influence performance outcomes. Data were collected through a structured questionnaire distributed to 293 athletes, coaches, and sports academics. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), we found that perceived AI benefits significantly predict the use of AI applications (β = 0.211, p < 0.001), which in turn strongly predicts the adoption of digital sports technologies (β = 0.708, p < 0.001). The use of digital technologies was positively associated with higher self-reported performance outcomes (β = 0.268, p < 0.001). Group comparisons using ANOVA revealed significant differences in AI adoption by sport (football > basketball, p < 0.05) and education level (p = 0.007). These findings contribute to the literature on sports technology adoption by offering one of Eastern Europe’s first empirical, model-based studies. The study provides practical insights for coaches, policymakers, and sports technologists aiming to foster AI integration and digital innovation in high-performance athletic environments.

Applied SciencesVol. 15(16)
Universitatea Națională de Educație Fizică și Sport București (RO)
Openalex Percentile: Top 7%
Sports Analytics and Performance
3.13
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Harnessing Artificial Intelligence in Sports Training: Evidence from Romanian Professionals Using SEM Analysis — Monica Stănescu, Andreea Trușcă, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS