Application and Evaluation of Artificial Intelligence Technology in Collegiate Soccer Sports

[1] McFadden, B. A., Walker, A. J., Bozzini, B. N., Sanders, D. J., & Arent, S. M. (2020). Comparison of internal and external training loads in male and female collegiate soccer players during practices vs. games. The Journal of Strength & Conditioning Research, 34(4), 969-974. Search in Google Scholar

[2] Favero, T. G., & White, J. (2018). Periodization in college soccer. Strength & Conditioning Journal, 40(3), 33-44. Search in Google Scholar

[3] Benjamin, C. L., Curtis, R. M., Huggins, R. A., Sekiguchi, Y., Jain, R. K., McFadden, B. A., & Casa, D. J. (2020). Sleep dysfunction and mood in collegiate soccer athletes. Sports Health, 12(3), 234-240. Search in Google Scholar

[4] Manore, M. M., Patton-Lopez, M. M., Meng, Y., & Wong, S. S. (2017). Sport nutrition knowledge, behaviors and beliefs of high school soccer players. Nutrients, 9(4), 350. Search in Google Scholar

[5] Howard, N., & Stavrianeas, S. (2017). In-season high-intensity interval training improves conditioning in high school soccer players. International journal of exercise science, 10(5), 713. Search in Google Scholar

[6] Khodaee, M., Currie, D. W., Asif, I. M., & Comstock, R. D. (2017). Nine-year study of US high school soccer injuries: data from a national sports injury surveillance programme. British journal of sports medicine, 51(3), 185-193. Search in Google Scholar

[7] Svaldi, D. O., McCuen, E. C., Joshi, C., Robinson, M. E., Nho, Y., Hannemann, R., ... & Talavage, T. M. (2017). Cerebrovascular reactivity changes in asymptomatic female athletes attributable to high school soccer participation. Brain imaging and behavior, 11, 98-112. Search in Google Scholar

[8] Rathi, K., Somani, P., Koul, A. V., & Manu, K. S. (2020). Applications of artificial intelligence in the game of football: The global perspective. Researchers World, 11(2), 18-29. Search in Google Scholar

[9] García-Aliaga, A., Marquina Nieto, M., Coterón, J., Rodríguez-González, A., Gil Ares, J., & Refoyo Román, I. (2023). A longitudinal study on the evolution of the four main football leagues using artificial intelligence: analysis of the differences in English Premier League teams. Research Quarterly for Exercise and Sport, 94(2), 529-537. Search in Google Scholar

[10] Fialho, G., Manhães, A., & Teixeira, J. P. (2019). Predicting sports results with artificial intelligence–a proposal framework for soccer games. Procedia Computer Science, 164, 131-136. Search in Google Scholar

[11] Wang, T. (2022). Exploring intelligent image recognition technology of football robot using omnidirectional vision of internet of things. The Journal of Supercomputing, 78(8), 10501-10520. Search in Google Scholar

[12] Li, D., & Zhang, J. (2021). Computer Aided Teaching System Based on Artificial Intelligence in Football Teaching and Training. Mobile Information Systems. Search in Google Scholar

[13] Tuyls, K., Omidshafiei, S., Muller, P., Wang, Z., Connor, J., Hennes, D., ... & Hassabis, D. (2021). Game Plan: What AI can do for Football, and What Football can do for AI. Journal of Artificial Intelligence Research, 71, 41-88. Search in Google Scholar

[14] Yang, Y. (2020, October). Evaluation model of soccer training technology based on artificial intelligence. In Journal of Physics: Conference Series (Vol. 1648, No. 4, p. 042085). IOP Publishing. Search in Google Scholar

[15] Li, H., Cui, C., & Jiang, S. (2022). Strategy for improving the football teaching quality by AI and metaverse-empowered in mobile internet environment. Wireless Networks, 1-10. Search in Google Scholar

[16] Liu, J., Wang, L., & Zhou, H. (2021). The application of human–computer interaction technology fused with artificial intelligence in sports moving target detection education for college athlete. Frontiers in Psychology, 12, 677590. Search in Google Scholar

[17] Wang, J. A., Liu, S., & Zhang, X. (2021). Application of artificial intelligence in university sports risk recognition and identification. Journal of Intelligent & Fuzzy Systems, 40(2), 3361-3372. Search in Google Scholar

[18] Olimjon Mirzaev,Sobirjon Radjabov,Nomaz Mirzaev,Ilyos Rabbimov & Jasur Baratov. (2024). Construction of statistical recognition algorithms based on two-dimensional threshold functions. Procedia Computer Science123-130. Search in Google Scholar

[19] Jianxiao Bian,Jiarui Wang & Qian Yece. (2024). A novel study on power consumption of an HVAC system using CatBoost and AdaBoost algorithms combined with the metaheuristic algorithms. Energy131841-. Search in Google Scholar

[20] Zehra Özdemir & Hazal Ceyhan. (2024). Multiplicative hyperbolic split quaternions and generating geometric hyperbolical rotation matrices. Applied Mathematics and Computation128862-. Search in Google Scholar