[
Abdelrasoul, E., Mahmoud, I., Stergiou, P., & Katz, L. (2015). The accuracy of a real time sensor in an instrumented basketball. Procedia Engineering, 112, 202-206.
]Search in Google Scholar
[
Abulrub, A. H. G., Attridge, A. N., & Williams, M. A. (2011, April). Virtual reality in engineering education: The future of creative learning. In 2011 IEEE global engineering education conference (EDUCON) (pp. 751-757). IEEE.
]Search in Google Scholar
[
Appelbaum, L. G., & Erickson, G. (2018). Sports vision training: A review of the state-of-theart in digital training techniques. International Review of Sport and Exercise Psychology, 11(1), 160-189.
]Search in Google Scholar
[
Baek, S., & Kim, M. (2013). Flight trajectory of a golf ball for a realistic game. International Journal of Innovation, Management and Technology, 4(3), 346.
]Search in Google Scholar
[
Barnhart, S. A., Narayanan, B., & Gunasekaran, S. (2021). Blown wing aerodynamic coefficient predictions using traditional machine learning and data science approaches. In AIAA Scitech 2021 Forum (p. 0616).
]Search in Google Scholar
[
Brock, H., & Ohgi, Y. (2017). Development of an inertial motion capture system for kinematic analysis of ski jumping. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, 231(4), 275-286.
]Search in Google Scholar
[
Cannavò, A., Pratticò, F. G., Ministeri, G., & Lamberti, F. (2018, February). A movement analysis system based on immersive virtual reality and wearable technology for sport training. In Proceedings of the 4th international conference on virtual reality (pp. 26-31).
]Search in Google Scholar
[
Cao, C., Yu, H., & Liu, Y. (2021). Automatic Tracking Method of Basketball Flight Trajectory Based on Data Fusion and Sparse Representation Model. Complexity, 2021(1), 9568753.
]Search in Google Scholar
[
Carré, M. J., Asai, T., Akatsuka, T., & Haake, S. J. (2002). The curve kick of a football II: flight through the air. Sports Engineering, 5(4), 193-200.
]Search in Google Scholar
[
Chakraborty, B., & Meher, S. (2013). A real-time trajectory-based ball detection-and-tracking framework for basketball video. Journal of optics, 42, 156-170.
]Search in Google Scholar
[
Che, Y., & Keir, M. Y. A. (2021). Study on the training model of football movement trajectory drop point based on fractional differential equation. Applied Mathematics and Nonlinear Sciences, 7(1), 425-430.
]Search in Google Scholar
[
Chen, L. H., Chang, H. W., & Hsiao, H. A. (2017, August). Player trajectory reconstruction from broadcast basketball video. In Proceedings of the 2nd International Conference on Biomedical Signal and Image Processing (pp. 72-76).
]Search in Google Scholar
[
Chen, M., & Su, F. (2022). A basketball game prediction system based on artificial intelligence. The Journal of Supercomputing, 78(10), 12528-12552.
]Search in Google Scholar
[
Cheng, C. Y., Chen, Y. J., & Lin, S. Y. (2005, July). Design and implementation of a vision-based basketball shooting robot. In IEEE International Conference on Mechatronics, 2005. ICM 05. (pp. 113-117). IEEE.
]Search in Google Scholar
[
Cohan, A., Schuster, J., & Fernandez, J. (2021). A deep learning approach to injury forecasting in NBA basketball. Journal of Sports Analytics, 7(4), 277-289.
]Search in Google Scholar
[
Covaci, A., Olivier, A. H., & Multon, F. (2014, November). Third person view and guidance for more natural motor behaviour in immersive basketball playing. In Proceedings of the 20th ACM Symposium on Virtual Reality Software and Technology (pp. 55-64).
]Search in Google Scholar
[
Covaci, A., Olivier, A. H., & Multon, F. (2015). Visual perspective and feedback guidance for VR free-throw training. IEEE computer graphics and applications, 35(5), 55-65.
]Search in Google Scholar
[
Covaci, A., Postelnicu, C. C., Panfir, A. N., & Talaba, D. (2012). A virtual reality simulator for basketball free-throw skills development. In Technological Innovation for Value Creation: Third IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2012, Costa de Caparica, Portugal, February 27-29, 2012. Proceedings 3 (pp. 105-112). Springer Berlin Heidelberg.
]Search in Google Scholar
[
Fan, J., Bi, S., Wang, G., Zhang, L., & Sun, S. (2021). Sensor fusion basketball shooting posture recognition system based on CNN. Journal of Sensors, 2021(1), 6664776.
]Search in Google Scholar
[
Fan, J., Bi, S., Xu, R., Wang, L., & Zhang, L. (2022). Hybrid lightweight Deep-learning model for Sensor-fusion basketball Shooting-posture recognition. Measurement, 189, 110595.
]Search in Google Scholar
[
Fontanella, J. J. (2006). The physics of basketball. JHU Press.
]Search in Google Scholar
[
Fu, X. B., Yue, S. L., & Pan, D. Y. (2021). Camera-based basketball scoring detection using convolutional neural network. International Journal of Automation and Computing, 18(2), 266-276.
]Search in Google Scholar
[
Gao, B., Zhao, Z. L., & Zhang, M. M. (2014). The application of basketball zone defense tactics. Advanced Materials Research, 989, 5193-5196.
]Search in Google Scholar
[
Greco, P., Memmert, D., & Morales, J. C. (2010). The effect of deliberate play on tactical performance in basketball. Perceptual and motor skills, 110(3), 849-856.
]Search in Google Scholar
[
Hamilton, G. R., & Reinschmidt, C. (1997). Optimal trajectory for the basketball free throw. Journal of sports sciences, 15(5), 491-504.
]Search in Google Scholar
[
Hao, W. (2021, August). Auxiliary basketball training system based on big data. In 2021 World Automation Congress (WAC) (pp. 61-64). IEEE.
]Search in Google Scholar
[
Honma, H., Iida, Y., Okumura, Y., Fujii, K., & Umehira, M. (2021, October). Evaluation of 3D Virtualization Accuracy for VR-Based Personal Basketball Team-Practice System. In 2021 IEEE 10th Global Conference on Consumer Electronics (GCCE) (pp. 709-710). IEEE.
]Search in Google Scholar
[
Huang, P., Wang, F., Fu, A., & Gu, M. (2016). Numerical simulation of 3-D probabilistic trajectory of plate-type wind-borne debris. Wind Struct, 22(1), 17-41.
]Search in Google Scholar
[
Huston, R. L., & Grau, C. A. (2003). Basketball shooting strategies the free throw, direct shot and layup. Sports Engineering, 6, 49-64.
]Search in Google Scholar
[
Inaba, Y., Hakamada, N., & Murata, M. (2017, October). Influence of Selection of Release Angle and Speed on Success Rates of Jump Shots in Basketball. In icSPORTS (pp. 48-55).
]Search in Google Scholar
[
Inaba, Y., Hakamada, N., & Murata, M. (2019). Computation of optimal release parameters of jump shots in basketball. In Sport Science Research and Technology Support: 4th and 5th International Congress, icSPORTS 2016, Porto, Portugal, November 7-9, 2016, and icSPORTS 2017, Funchal, Madeira, Portugal, October 30-31, 2017, Revised Selected Papers 4 (pp. 164-175). Springer International Publishing.
]Search in Google Scholar
[
Iskurniawan, M. A., Sugiharto, S., & Mukarromah, S. B. (2020). The Development of Virtual Reality-Based Basketball Arbitration Simulation Tools. Journal of Physical Education and Sports, 9(2), 159-165.
]Search in Google Scholar
[
Jain, S., & Kaur, H. (2017, September). Machine learning approaches to predict basketball game outcome. In 2017 3rd International Conference on Advances in Computing, Communication & Automation (ICACCA)(Fall) (pp. 1-7). IEEE.
]Search in Google Scholar
[
Jerald, J. (2015). The VR book: Human-centered design for virtual reality. Morgan & Claypool.
]Search in Google Scholar
[
Ji, R. (2020). Research on basketball shooting action based on image feature extraction and machine learning. IEEE Access, 8, 138743-138751.
]Search in Google Scholar
[
Jung, A., Staat, M., & Müller, W. (2014). Flight style optimization in ski jumping on normal, large, and ski flying hills. Journal of biomechanics, 47(3), 716-722.
]Search in Google Scholar
[
Kakimpa, B., Hargreaves, D. M., & Owen, J. S. (2012). An investigation of plate-type windborne debris flight using coupled CFD RBD models. Part I: model development and validation. Journal of Wind Engineering and Industrial Aerodynamics, 111, 95-103.
]Search in Google Scholar
[
Kakimpa, B., Hargreaves, D. M., & Owen, J. S. (2012). An investigation of plate-type windborne debris flight using coupled CFD RBD models. Part II: Free and constrained flight. Journal of wind engineering and industrial aerodynamics, 111, 104-116.
]Search in Google Scholar
[
Khaustov V, Mozgovoy M. Recognizing events in spatiotemporal soccer data[J]. Applied Sciences, 2020, 10(22): 8046.
]Search in Google Scholar
[
Kolias, P., Stavropoulos, N., Papadopoulou, A., & Kostakidis, T. (2022). Evaluating basketball player’s rotation line-ups performance via statistical markov chain modelling. International Journal of Sports Science & Coaching, 17(1), 178-188.
]Search in Google Scholar
[
Kuhlman, N., & Min, C. H. (2021, January). Analysis and classification of basketball shooting form using wearable sensor systems. In 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 1478-1482). IEEE.
]Search in Google Scholar
[
Kumar, N. P. (2014). Effect of basketball specific footwork training protocol on selected offensive and defensive skills in basketball. International Journal of Physical Education, Fitness and Sports, 3(2), 60-67.
]Search in Google Scholar
[
Lee, D. J., & Page, G. L. (2021). Big Data in Sports: Predictive Models for Basketball Player’s Performance.
]Search in Google Scholar
[
Li, J., Du, X., & Martins, J. R. (2022). Machine learning in aerodynamic shape optimization. Progress in Aerospace Sciences, 134, 100849.
]Search in Google Scholar
[
Li, R. T., Kling, S. R., Salata, M. J., Cupp, S. A., Sheehan, J., & Voos, J. E. (2016). Wearable performance devices in sports medicine. Sports health, 8(1), 74-78.
]Search in Google Scholar
[
Li, S. (2018). Application of virtual environment in the teaching of basketball tactics. International Journal of Emerging Technologies in Learning (Online), 13(7), 174.
]Search in Google Scholar
[
Lissaman, P., & Hubbard, M. (2010). Maximum range of flying discs. Procedia Engineering, 2(2), 2529-2535.
]Search in Google Scholar
[
Liu, P. X., Pan, T. Y., Lin, H. S., Chu, H. K., & Hu, M. C. (2022, October). Bettersight: Immersive vision training for basketball players. In Proceedings of the 30th ACM International Conference on Multimedia (pp. 6979-6981).
]Search in Google Scholar
[
Loeffelholz, B., Bednar, E., & Bauer, K. W. (2009). Predicting NBA games using neural networks. Journal of Quantitative Analysis in Sports, 5(1).
]Search in Google Scholar
[
Luo, S., Soh, K. G., Zhao, Y., Soh, K. L., Sun, H., Nasiruddin, N. J. M., ... & Ma, L. (2023). Effect of core training on athletic and skill performance of basketball players: A systematic review. Plos one, 18(6), e0287379.
]Search in Google Scholar
[
Ma, Z., Wang, F., & Liu, S. (2020). Feasibility analysis of VR technology in basketball training. IEEE Access.
]Search in Google Scholar
[
Mahmood, Z., Daud, A., & Abbasi, R. A. (2021). Using machine learning techniques for rising star prediction in basketball. Knowledge-Based Systems, 211, 106506.
]Search in Google Scholar
[
Metulini, R. (2016). Spatio-temporal movements in team sports: a visualization approach using motion charts. arxiv preprint arxiv:1611.09158.
]Search in Google Scholar
[
Metulini, R., Manisera, M., & Zuccolotto, P. (2017). Sensor analytics in basketball. arxiv preprint arxiv:1707.01430.
]Search in Google Scholar
[
Metulini, R., Manisera, M., & Zuccolotto, P. (2017). Space-time analysis of movements in basketball using sensor data. arxiv preprint arxiv:1707.00883.
]Search in Google Scholar
[
Miljković, D., Gajić, L., Kovačević, A., & Konjović, Z. (2010, September). The use of data mining for basketball matches outcomes prediction. In IEEE 8th international symposium on intelligent systems and informatics (pp. 309-312). IEEE.
]Search in Google Scholar
[
Miller, S., & Bartlett, R. (1996). The relationship between basketball shooting kinematics, distance and playing position. Journal of sports sciences, 14(3), 243-253.
]Search in Google Scholar
[
Miller, S., & Bartlett, R. M. (1993). The effects of increased shooting distance in the basketball jump shot. Journal of sports sciences, 11(4), 285-293.
]Search in Google Scholar
[
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ (Online), 339(7716), 332–336.
]Search in Google Scholar
[
Montgomery, P. G., Pyne, D. B., & Minahan, C. L. (2010). The physical and physiological demands of basketball training and competition. International journal of sports physiology and performance, 5(1), 75-86.
]Search in Google Scholar
[
Neumann, D. L., Moffitt, R. L., Thomas, P. R., Loveday, K., Watling, D. P., Lombard, C. L., ... & Tremeer, M. A. (2018). A systematic review of the application of interactive virtual reality to sport. Virtual Reality, 22, 183-198.
]Search in Google Scholar
[
Nguyen, L. N. N., Rodríguez-Martín, D., Català, A., Pérez-López, C., Samà, A., & Cavallaro, A. (2015, September). Basketball activity recognition using wearable inertial measurement units. In Proceedings of the XVI international conference on Human Computer Interaction (pp. 1-6).
]Search in Google Scholar
[
Nikhilesh, T. R., & Kulkarni, P. (2015). Numerical Analysis of the Trajectory of a Basketball Considering Lift and Drag. Applied Mechanics and Materials, 798, 493-499.
]Search in Google Scholar
[
Okazaki, V. H. A., & Rodacki, A. L. F. (2012). Increased distance of shooting on basketball jump shot. Journal of sports science & medicine, 11(2), 231.
]Search in Google Scholar
[
Okubo, H., & Hubbard, M. (2010). Identification of basketball parameters for a simulation model. Procedia Engineering, 2(2), 3281-3286.
]Search in Google Scholar
[
Okubo, H., & Hubbard, M. (2012). Defense for basketball field shots. Procedia Engineering, 34, 730-735.
]Search in Google Scholar
[
Okubo, H., & Hubbard, M. (2015). Rebounds of basketball field shots. Sports Engineering, 18, 43-54.
]Search in Google Scholar
[
Ozkan, I. A. (2020). A novel basketball result prediction model using a concurrent neuro-fuzzy system. Applied Artificial Intelligence, 34(13), 1038-1054.
]Search in Google Scholar
[
Pagé, C., Bernier, P. M., & Trempe, M. (2019). Using video simulations and virtual reality to improve decision-making skills in basketball. Journal of sports sciences, 37(21), 2403-2410.
]Search in Google Scholar
[
Pai, P. F., ChangLiao, L. H., & Lin, K. P. (2017). Analyzing basketball games by a support vector machines with decision tree model. Neural Computing and Applications, 28, 4159-4167.
]Search in Google Scholar
[
Pan, Y. H. (2014). Numerical Simulation of the Basketball Flight Trajectory Based on FLUENT Fluid Solid Coupling Mechanics. Applied Mechanics and Materials, 651, 2347-2351.
]Search in Google Scholar
[
Pechlivanos, R. G., Amiridis, I. G., Anastasiadis, N., Kannas, T., Sahinis, C., Duchateau, J., & Enoka, R. M. (2024). Effects of plyometric training techniques on vertical jump performance of basketball players. European Journal of Sport Science.
]Search in Google Scholar
[
Peng, M., Zhang, Z., & Zhou, Q. (2020, August). Basketball footwork recognition using smart insoles integrated with multiple sensors. In 2020 IEEE/CIC International Conference on Communications in China (ICCC) (pp. 1202-1207). IEEE.
]Search in Google Scholar
[
Petilla, C. A. B., Yap, G. D. G., Zheng, N. Y., Yuson, P. L. L., & Ilao, J. P. (2018). Single player tracking in multiple sports videos. Mechatronics and Machine Vision in Practice 3, 73-89.
]Search in Google Scholar
[
Pratama, R. R., Arisman, A., Marta, I. A., Okilanda, A., & Putra, D. D. (2022). Zig-Zag Run in Improving Basketball Dribbling Skills. Halaman Olahraga Nusantara(HON), 5, 405-413.
]Search in Google Scholar
[
Ramirez-Campillo, R., García-Hermoso, A., Moran, J., Chaabene, H., Negra, Y., & Scanlan, A. T. (2022). The effects of plyometric jump training on physical fitness attributes in basketball players: A meta-analysis. Journal of Sport and Health Science, 11(6), 656-670.
]Search in Google Scholar
[
Rein, R., & Memmert, D. (2016). Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science. SpringerPlus, 5, 1-13.
]Search in Google Scholar
[
Richards, P. J. (2010, December). Steady aerodynamics of rod and plate type debris. In Proceedings of the Seventeenth Australasian Fluid Mechanics Conference, Auckland, New Zealand (Vol. 9).
]Search in Google Scholar
[
Rochim, A. F., Eridani, D., & Rustam, P. J. (2023, November). Basketball Arm Shooting Robot Design by Implementing Parabolic Motion. In 2023 6th International Conference on Information and Communications Technology (ICOIACT) (pp. 1-4). IEEE.
]Search in Google Scholar
[
Sagiroglu, S., & Sinanc, D. (2013, May). Big data: A review. In 2013 international conference on collaboration technologies and systems (CTS) (pp. 42-47). IEEE.
]Search in Google Scholar
[
Saiki, H., Hirokawa, M., Hassan, M., & Suzuki, K. (2024). A Large-Scale Mixed Reality Stadium for Training Combination Tactics in Basketball.
]Search in Google Scholar
[
Santhosh, P. K., & Kaarthick, B. (2019). An Automated Player Detection and Tracking in Basketball Game. Computers, Materials & Continua, 58(3).
]Search in Google Scholar
[
Sarlis, V., Chatziilias, V., Tjortjis, C., & Mandalidis, D. (2021). A data science approach analysing the impact of injuries on basketball player and team performance. Information Systems, 99, 101750.
]Search in Google Scholar
[
Savas, S., Yüksel, M. F., & Uzun, A. (2018). The Effects of Rapid Strength and Shooting Training Applied to Professional Basketball Players on the Shot Percentage Level. Universal Journal of Educational Research, 6(7), 1569-1574.
]Search in Google Scholar
[
Seo, K., Murakami, M., & Yoshida, K. (2004). Optimal flight technique for V-style ski jumping. Sports Engineering, 7, 97-103.
]Search in Google Scholar
[
Seo, K., Shimoyama, K., Ohta, K., Ohgi, Y., & Kimura, Y. (2014). Optimization of the size and launch conditions of a discus. Procedia Engineering, 72, 756-761.
]Search in Google Scholar
[
Silverberg, L., Tran, C., & Adcock, K. (2003). Numerical analysis of the basketball shot. J. Dyn. Sys., Meas., Control, 125(4), 531-540.
]Search in Google Scholar
[
Soltani, P., & Morice, A. H. (2023). A multi-scale analysis of basketball throw in virtual reality for tracking perceptual-motor expertise. Scandinavian Journal of Medicine & Science in Sports, 33(2), 178-188.
]Search in Google Scholar
[
Taniguchi, A., Watanabe, K., & Kurihara, Y. (2012, August). Measurement and analyze of jump shoot motion in basketball using a 3-D acceleration and gyroscopic sensor. In 2012 Proceedings of SICE Annual Conference (SICE) (pp. 361-365). IEEE.
]Search in Google Scholar
[
Taylor, M., Nagle, E. F., Goss, F. L., Rubinstein, E. N., & Simonson, A. (2018). Evaluating energy expenditure estimated by wearable technology during variable intensity activity on female collegiate athletes. International journal of exercise science, 11(7), 598.
]Search in Google Scholar
[
Tedesco, S., Scheurer, S., Brown, K. N., Hennessy, L., & O’Flynn, B. (2022, July). A survey on the use of Artificial Intelligence for injury prediction in sports. In 2022 IEEE International Workshop on Sport, Technology and Research (STAR) (pp. 127-131). IEEE.
]Search in Google Scholar
[
Tran, C. M., & Silverberg, L. M. (2008). Optimal release conditions for the free throw in men’s basketball. Journal of sports sciences, 26(11), 1147-1155.
]Search in Google Scholar
[
Tsai, W. L. (2018, June). Personal basketball coach: Tactic training through wireless virtual reality. In Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval (pp. 481-484).
]Search in Google Scholar
[
Tsai, W. L., Chung, M. F., Pan, T. Y., & Hu, M. C. (2017, October). Train in virtual court: Basketball tactic training via virtual reality. In Proceedings of the 2017 ACM Workshop on Multimedia-based Educational and Knowledge Technologies for Personalized and Social Online Training (pp. 3-10).
]Search in Google Scholar
[
Tsai, W. L., Pan, T. Y., & Hu, M. C. (2020). Feasibility study on virtual reality based basketball tactic training. IEEE Transactions on Visualization and Computer Graphics, 28(8), 2970-2982.
]Search in Google Scholar
[
Tsai, W. L., Pan, T. Y., & Hu, M. C. (2022, September). Improve Immersion in Virtual Reality-Based Basketball Training By Haptic Feedback. In Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers (pp. 524-528).
]Search in Google Scholar
[
Tsai, W. L., Su, L. W., Ko, T. Y., Yang, C. T., & Hu, M. C. (2019, March). Improve the decision-making skill of basketball players by an action-aware VR training system. In 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) (pp. 1193-1194). IEEE.
]Search in Google Scholar
[
Ward, M., Passmore, M., Spencer, A., Tuplin, S., & Harland, A. (2019). Characterisation of football trajectories for assessing flight performance. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, 233(1), 16-26.
]Search in Google Scholar
[
Wu, W. (2020). Injury Analysis Based on Machine Learning in NBA Data. Journal of Data Analysis and Information Processing, 8(4), 295-308.
]Search in Google Scholar
[
Xu, X., Zhang, M., & Yi, Q. (2022). Clustering performances in elite basketball matches according to the anthropometric features of the line-ups based on big data technology. Frontiers in Psychology, 13, 955292.
]Search in Google Scholar
[
Yasuda, K., Tsuboi, K., Tanaka, K., & Miyazaki, T. (2014). Estimation of aerodynamic coefficients for a ball by using characteristics of trajectory. Trans. JSME, 80(814), 1-10.
]Search in Google Scholar
[
Yoon, Y., Hwang, H., Choi, Y., Joo, M., Oh, H., Park, I., ... & Hwang, J. H. (2019). Analyzing basketball movements and pass relationships using realtime object tracking techniques based on deep learning. IEEE Access, 7, 56564-56576.
]Search in Google Scholar
[
Zamzami, M. (2020). The effectiveness of using virtual reality technology on learning the jump-shot skill in basketball. Jurnal MensSana, 5(2), 191-201.
]Search in Google Scholar
[
Zdravevski, E., & Kulakov, A. (2009, September). System for Prediction of the Winner in a Sports Game. In International conference on ICT innovations (pp. 55-63). Berlin, Heidelberg: Springer Berlin Heidelberg.
]Search in Google Scholar
[
Žemgulys, J., Raudonis, V., Maskeliūnas, R., & Damaševičius, R. (2020). Recognition of basketball referee signals from real-time videos. Journal of Ambient Intelligence and Humanized Computing, 11, 979-991.
]Search in Google Scholar
[
Zhiwen, W., Pengtao, W., Lianyuan, J., Bowen, T., Canlong, Z., & Zhenghuan, H. (2017, November). Analysis of influencing factors of shooting rate based on trajectory prediction of the basketball. In 2017 14th Web Information Systems and Applications Conference (WISA) (pp. 176-180). IEEE.
]Search in Google Scholar
[
Zhong, S. (2022). Application of Artificial Intelligence and Big Data Technology in Basketball Sports Training. Wireless Communications and Mobile Computing, 2022(1), 8424303.
]Search in Google Scholar
[
Zindulka, T., Bachynskyi, M., & Müller, J. (2020, April). Performance and experience of throwing in virtual reality. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-8).
]Search in Google Scholar
[
Zuccolotto, P., Manisera, M., & Sandri, M. (2018). Big data analytics for modeling scoring probability in basketball: The effect of shooting under high-pressure conditions. International journal of sports science & coaching, 13(4), 569-589.
]Search in Google Scholar
