Affiliations:
1Department of Service Courses, Faculty of Arts, Isra University, Amman, Jordan
2Department of IT, College of Information Technology and Communications, Tafila Technical University, Tafila, Jordan
3Department of Computer Science, Faculty of Information Technology, Isra University, Amman, Jordan
The rapid development of modern technologies, particularly artificial intelligence (AI), has significantly influenced the sports industry by improving athlete performance and reducing injury risks. AI is now widely applied in areas such as performance evaluation, referee decision-making, fan engagement, and injury diagnosis. These advancements have enabled the creation of predictive models for player performance, injury prevention, and match analysis, as well as new algorithms for talent identification and performance assessment. Although AI offers substantial benefits, relying solely on data also carries risks, making informed judgment and proper training essential for coaches and athletes. This study proposes and evaluates a hybrid model that integrates deep learning methods (LSTM, DNN) with machine learning techniques (SVM, RF) to predict the probability of sports injuries. Using a manually collected real-world dataset from sports websites, the model achieved an accuracy of 81%. The findings provide valuable insights for injury prevention strategies and support more effective decision-making in the sports industry.
Artificial intelligence, Sports performance, Injury prediction, Machine learning, Deep learning
https://doi.org/10.21833/ijaas.2026.02.009
Nashwan, N. A., Tarawneh, M., & Alzyoud, F. Y. (2026). Artificial intelligence in sports: Enhancing athlete performance and injury prevention. International Journal of Advanced and Applied Sciences, 13(2), 81–88. https://doi.org/10.21833/ijaas.2026.02.009