A Review on the Application of Artificial Intelligence in Basketball Sports
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References
- 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. - 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. - 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. - 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. - 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). - 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. - 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). - 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. - 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. - Chakraborty, B., & Meher, S. (2013). A real-time trajectory-based ball detection-and-tracking framework for basketball video.
Journal of optics, 42 , 156-170. - 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. - 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). - Chen, M., & Su, F. (2022). A basketball game prediction system based on artificial intelligence.
The Journal of Supercomputing, 78 (10), 12528-12552. - 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. - 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. - 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). - 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. - 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. - 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. - 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. - Fontanella, J. J. (2006).
The physics of basketball . JHU Press. - 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. - Gao, B., Zhao, Z. L., & Zhang, M. M. (2014). The application of basketball zone defense tactics.
Advanced Materials Research, 989 , 5193-5196. - 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. - Hamilton, G. R., & Reinschmidt, C. (1997). Optimal trajectory for the basketball free throw.
Journal of sports sciences, 15 (5), 491-504. - Hao, W. (2021, August). Auxiliary basketball training system based on big data. In
2021 World Automation Congress (WAC) (pp. 61-64). IEEE. - 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. - 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. - Huston, R. L., & Grau, C. A. (2003). Basketball shooting strategies the free throw, direct shot and layup.
Sports Engineering, 6 , 49-64. - 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). - 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. - 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. - 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. - Jerald, J. (2015). The VR book:
Human-centered design for virtual reality. Morgan & Claypool. - Ji, R. (2020). Research on basketball shooting action based on image feature extraction and machine learning.
IEEE Access, 8 , 138743-138751. - 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. - 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. - 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. - Khaustov V, Mozgovoy M. Recognizing events in spatiotemporal soccer data[J].
Applied Sciences, 2020, 10 (22): 8046. - 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. - 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. - 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. - Lee, D. J., & Page, G. L. (2021). Big Data in Sports: Predictive Models for Basketball Player’s Performance.
- Li, J., Du, X., & Martins, J. R. (2022). Machine learning in aerodynamic shape optimization.
Progress in Aerospace Sciences, 134 , 100849. - 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. - Li, S. (2018). Application of virtual environment in the teaching of basketball tactics.
International Journal of Emerging Technologies in Learning (Online), 13 (7), 174. - Lissaman, P., & Hubbard, M. (2010). Maximum range of flying discs.
Procedia Engineering, 2 (2), 2529-2535. - 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). - Loeffelholz, B., Bednar, E., & Bauer, K. W. (2009). Predicting NBA games using neural networks.
Journal of Quantitative Analysis in Sports, 5 (1). - 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. - Ma, Z., Wang, F., & Liu, S. (2020). Feasibility analysis of VR technology in basketball training.
IEEE Access. - Mahmood, Z., Daud, A., & Abbasi, R. A. (2021). Using machine learning techniques for rising star prediction in basketball.
Knowledge-Based Systems, 211 , 106506. - Metulini, R. (2016). Spatio-temporal movements in team sports: a visualization approach using motion charts.
arxiv preprint arxiv:1611.09158. - Metulini, R., Manisera, M., & Zuccolotto, P. (2017). Sensor analytics in basketball.
arxiv preprint arxiv:1707.01430. - Metulini, R., Manisera, M., & Zuccolotto, P. (2017). Space-time analysis of movements in basketball using sensor data.
arxiv preprint arxiv:1707.00883. - 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. - Miller, S., & Bartlett, R. (1996). The relationship between basketball shooting kinematics, distance and playing position.
Journal of sports sciences, 14 (3), 243-253. - 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. - 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.
- 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. - 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. - 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). - 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. - 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. - Okubo, H., & Hubbard, M. (2010). Identification of basketball parameters for a simulation model.
Procedia Engineering, 2 (2), 3281-3286. - Okubo, H., & Hubbard, M. (2012). Defense for basketball field shots.
Procedia Engineering, 34 , 730-735. - Okubo, H., & Hubbard, M. (2015). Rebounds of basketball field shots.
Sports Engineering, 18 , 43-54. - Ozkan, I. A. (2020). A novel basketball result prediction model using a concurrent neuro-fuzzy system.
Applied Artificial Intelligence, 34 (13), 1038-1054. - 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. - 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. - 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. - 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 . - 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. - 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. - 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. - 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. - Rein, R., & Memmert, D. (2016). Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science.
SpringerPlus, 5 , 1-13. - 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). - 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. - Sagiroglu, S., & Sinanc, D. (2013, May). Big data: A review. In
2013 international conference on collaboration technologies and systems (CTS) (pp. 42-47). IEEE. - Saiki, H., Hirokawa, M., Hassan, M., & Suzuki, K. (2024). A Large-Scale Mixed Reality Stadium for Training Combination Tactics in Basketball.
- Santhosh, P. K., & Kaarthick, B. (2019). An Automated Player Detection and Tracking in Basketball Game.
Computers, Materials & Continua, 58 (3). - 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. - 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. - Seo, K., Murakami, M., & Yoshida, K. (2004). Optimal flight technique for V-style ski jumping.
Sports Engineering, 7 , 97-103. - 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. - Silverberg, L., Tran, C., & Adcock, K. (2003). Numerical analysis of the basketball shot.
J. Dyn. Sys., Meas., Control, 125 (4), 531-540. - 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. - 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. - 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. - 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. - 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. - 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). - 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). - 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. - 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). - 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. - 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. - Wu, W. (2020). Injury Analysis Based on Machine Learning in NBA Data.
Journal of Data Analysis and Information Processing, 8 (4), 295-308. - 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. - 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. - 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. - Zamzami, M. (2020). The effectiveness of using virtual reality technology on learning the jump-shot skill in basketball.
Jurnal MensSana, 5 (2), 191-201. - 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. - 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. - 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. - Zhong, S. (2022). Application of Artificial Intelligence and Big Data Technology in Basketball Sports Training.
Wireless Communications and Mobile Computing, 2022 (1), 8424303. - 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). - 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.
DOI: https://doi.org/10.2478/ijcss-2024-0013 | Journal eISSN: 1684-4769
Language: English
Page range: 62 - 90
Published on: Oct 18, 2024
Published by: International Association of Computer Science in Sport
In partnership with: Paradigm Publishing Services
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© 2024 Zhang Chenyi, Zhu Weijian, Li Bo, Zhu Zhiyong, Zhu Feng, published by International Association of Computer Science in Sport
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