2771-1463ISSN (Online)
2771-1471ISSN (Print)
Volume 9 , Issue 2 , PP: 34-43, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
A. V. Adlin Grace 1 * , Sanjay Kumar S. 2 , Rajesh S. 3 , Ragul Doss R. 4
Doi: https://doi.org/10.54216/JCHCI.090205
Cricket is a physically demanding sport that exposes players to various acute and chronic injuries. Preventing these injuries is crucial for maintaining peak performance and prolonging careers. This project leverages artificial intelligence (AI) and machine learning (ML) to analyze key player data, including biomechanics, workload, fatigue, and mental stress, to assess and mitigate injury risks. Wearable sensors and tracking systems continuously monitor player movements, workload, and physiological parameters, providing real-time insights into their physical condition. By detecting patterns that indicate potential injury risks, the AI model enables early intervention through personalized training modifications and recovery programs. This proactive approach minimizes injuries, optimizes player fitness, and enhances performance. Ultimately, integrating AI-driven injury prevention strategies in cricket ensures better player management, increased longevity, and improved overall team efficiency.
Cricket Injury Prediction , AI in Sports , Machine Learning , Wearable Sensors , Biomechanics Analysis
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