Application of Artificial Intelligence in Basketball Sport
Keywordsbasketball, artificial intelligence, wearable electronic devices
AbstractBasketball is among the most popular sports in the world, and its related industries have also produced huge economic benefits. In recent years, the application of artificial intelligence (AI) technology in basketball has attracted a large amount of attention. We conducted a comprehensive review of the application research of AI in basketball through literature retrieval. Current research focuses on the AI analysis of basketball team and player performance, prediction of competition results, analysis and prediction of shooting, AI coaching system, intelligent training machine and arena, and sports injury prevention. Most studies have shown that AI technology can improve the training level of basketball players, help coaches formulate suitable game strategies, prevent sports injuries, and improve the enjoyment of games. At the same time, it is also found that the number and level of published papers are relatively limited. We believe that the application of AI in basketball is still in its infancy. We call on relevant industries to increase their research investment in this area, and promote the improvement of the level of basketball, making the game increasingly exciting as its worldwide popularity continues to increase.
Russell SJ, Norvig P. Artificial Intelligence: A Modern Approach. 3rd ed. Upper Saddle River (NJ) Prentice Hall; 2010.
Rodrigues ACN, Pereira AS, Mendes RMS, Araújo AG, Couceiro MS, Figueiredo AJ. Using Artificial Intelligence for Pattern Recognition in a Sports Context. Sensors (Basel). 2020; 20(11):3040. doi: 10.3390/s20113040.
Claudino JG, Capanema DO, de Souza TV, Serrão JC, Machado Pereira AC, Nassis GP. Current Approaches to the Use of Artificial Intelligence for Injury Risk Assessment and Performance Prediction in Team Sports: a Systematic Review. Sports Med Open. 2019;5(1):28. doi: 10.1186/s40798-019-0202-3.
Nadikattu RR. Implementation of New Ways of Artificial Intelligence in Sports. Journal of Xidian University. 2020;14(5):5983-5997.
Beal R, Norman T, Ramchurn S. Artificial intelligence for team sports: A survey. The Knowledge Engineering Review. 2019;34:E28. doi: 10.1017/S0269888919000225
Roy B. AI Augmented Sports Revolution. https://baijayanta.medium.com/ai-augmented-sports-revolution-5c0727ba7004 (dostep: 2021.05.05).
Joshi N. Here's How AI Will Change The World Of Sports! https://www.forbes.com/sites/cognitiveworld/2019/03/15/heres-how-ai-will-change-the-world-of-sports/?sh=66c0f409556b (dostep: 2021.05.05).
Perse M, Kristan M, Perˇs J, Kovacic S. Automatic Evaluation of Organized Basketball Activity using Bayesian Networks. Computer Vision Winter Workshop; 2007 Feb 6-8; St. Lambrecht, Austria.
Wu L. The participating team’s technical analysis of women’s basketball in the 30th Olympic Games based on neural network. J Chem Pharma Res. 2013;5:152-158.
Kempe M, Grunz A, Memmert D. Detecting tactical patterns in basketball: comparison of merge self-organising maps and dynamic controlled neural networks. Eur J Sport Sci. 2015;15(4):249-55. doi: 10.1080/17461391.2014.933882.
Çene E. What is the difference between a winning and a losing team: insights from Euroleague basketball. International Journal of Performance Analysis in Sport. 2018;18(1):55-68. doi: 10.1080/24748668.2018.1446234.
Leicht AS, Gómez MA, Woods CT. Explaining Match Outcome During The Men's Basketball Tournament at The Olympic Games. J Sports Sci Med. 2017;16(4):468-473.
Leicht AS, Gomez MA, Woods CT. Team Performance Indicators Explain Outcome during Women's Basketball Matches at the Olympic Games. Sports (Basel). 2017;5(4):96. doi: 10.3390/sports5040096.
Tian C, De Silva V, Caine M, Swanson S. Use of Machine Learning to Automate the Identification of Basketball Strategies Using Whole Team Player Tracking Data. Appl. Sci. 2020;10(1):24. doi: 10.3390/app10010024.
Xing J, Ai H, Liu L, Lao S. Multiple player tracking in sports video: a dual-mode two-way bayesian inference approach with progressive observation modeling. IEEE Trans Image Process. 2011;20(6):1652-1667. doi: 10.1109/TIP.2010.2102045.
Hojo M, Fujii K, Inaba Y, Motoyasu Y, Kawahara Y. Automatically recognizing strategic cooperative behaviors in various situations of a team sport. PLoS One. 2018;13(12):e0209247. doi: 10.1371/journal.pone.0209247.
Yoon Y, Hwang H, Chio Y, Joo M, Oh H, Park I, Lee K, Hwang J. Analyzing Basketball Movements and Pass Relationships Using Realtime Object Tracking Techniques Based on Deep Learning. IEEE Access. 2019;7:56564-56576. doi: 10.1109/ACCESS.2019.2913953.
Sarlis V, Tjortjis C. Sports Analytics - Evaluation of Basketball Players and Team Performance. Information systems (Oxford). 2020; 93:101562. DOI:10.1016/j.is.2020.101562.
Lu G. Evaluation model of young basketball players’ physical quality and basic technique based on RBF neural network. BioTechnol Indian J. 2013;8(9):1193-1198.
Huo D. Evaluation of the value of basketball players based on wireless network and improved Bayesian algorithm. J Wireless Com Network. 2020;236.
Kannan A, Kolovich B, Lawrence B, Rafiqi S. Predicting National Basketball Association Success: A Machine Learning Approach. SMU Data Science Review. 2018;1(3):7.
Miljković D, Gajić L, Kovačević A, Konjović Z. The use of data mining for basketball matches outcomes prediction. IEEE 8th International Symposium on Intelligent Systems and Informatics; 2010 Sep 10-11; Subotica, Serbia, IEEE Xplore; 2010.
Cao, C. Sports data mining technology used in basketball outcome prediction. Masters Dissertation. 2012 Aug 31; Technological University Dublin, Dublin, Ireland.
Pai PF, ChangLiao LH, Lin KP. Analyzing basketball games by a support vector machines with decision tree model. Neural Computing and Applications. 2016; 12:4159-4167. doi: 10.1007/s00521-016-2321-9.
Horvat T, Havaš L, Srpak D. The Impact of Selecting a Validation Method in Machine Learning on Predicting Basketball Game Outcomes. Symmetry. 2020; 12(3): 431. doi: 10.3390/sym12030431.
Ozkan IA. A Novel Basketball Result Prediction Model Using a Concurrent Neuro-Fuzzy System. Applied Artificial Intelligence. 2020;34(13):1038-1054. doi: 10.1080/08839514.2020.1804229.
Skinner B, Guy SJ. A Method for Using Player Tracking Data in Basketball to Learn Player Skills and Predict Team Performance. PLoS One. 2015;10(9):e0136393. doi: 10.1371/journal.pone.0136393.
Zimmermann A, Moorthy S, Shi Z. Predicting college basketball match outcomes using machine learning techniques: some results and lessons learned (originally in “MLSA13”, workshop at ECML/PKDD 2013). 2013; arXiv:1310.3607.
Li C. Predict the neural network mathematical model of basketball team scores based on improved BP algorithm. BioTechnol Indian J. 2013;8(5):628-633.
Cai W, Yu D, Wua Z, Du X, Zhou T. A hybrid ensemble learning framework for basketball outcomes prediction. Physica A: Statistical Mechanics and its Applications. 2019; 528:121461. doi: 10.1016/j.physa.2019.121461.
Schmidt A. Movement pattern recognition in basketball free-throw shooting. Hum Mov Sci. 2012;31(2):360-82. doi: 10.1016/j.humov.2011.01.003.
Ji R. Research on Basketball Shooting Action Based on Image Feature Extraction and Machine Learning. IEEE Access. 2020;8:138743-138751. doi: 10.1109/ACCESS.2020.3012456.
Yu S, Liu J. Automatic Detection of Image Features in Basketball Shooting Teaching Based on Artificial Intelligence. e-Learning, e-Education, and Online Training. 2020;340:165-175. doi:10.1007/978-3-030-63955-6_15
Shah R, Romijnders R. Applying Deep Learning to Basketball Trajectories. 2016; arXiv:1608.03793.
Zhao Y, Yang R, Chevalier G, Shah R, Romijnders R. Applying Deep Bidirectional LSTM and Mixture Density Network for Basketball Trajectory Prediction. 2017; arXiv:1708.05824.
Przednowek K, Krzeszowski T, Przednowek KH, Lenik P. A System for Analysing the Basketball Free Throw Trajectory Based on Particle Swarm Optimization. Applied Sciences. 2018;8(11):2090. doi:10.3390/app8112090.
Nakai M, Tsunoda Y, Hayashi H, Murakoshi H. Prediction of Basketball Free Throw Shooting by OpenPose. W: Kojima K, Sakamoto M, Mineshima K, Satoh K, (red.). New Frontiers in Artificial Intelligence. Basel: Springer; 2019. p. 435-446.
Li T. Research on the Intelligent Teaching System of College Basketball Based on Artificial Intelligence. Revista Ibérica de Sistemas e Tecnologias de Informação. 2016; 18B:49-60. doi: 10.17013/risti.18B.49-60.
Zhao Y, Xie J. Artificial Intelligence, Computer Assisted Instruction in Basketball Training. International Journal of Information Studies. 2017;9(1):7-13.
Yang Z. Research on Basketball Players' Training Strategy Based on Artificial Intelligence Technology. Journal of Physics: Conference Series. 2020;1648:042057. doi: 10.1088/1742-6596/1648/4/042057.
Liu H, Li N. Research on the Technology of Intelligent Basketball Shooting Training Vehicle. Journal of Physics: Conference Series. 2020;1648:042091. doi: 10.1088/1742-6596/1648/4/042091.
Xu T, Tang L. Adoption of Machine Learning Algorithm-Based Intelligent Basketball Training Robot in Athlete Injury Prevention. Front Neurorobot. 2021;14:620378. doi: 10.3389/fnbot.2020.620378.
Liu W, Yan CC, Liu J, Ma H. Deep learning based basketball video analysis for intelligent arena application. Multimedia Tools and Applications. 2017;76:24983-25001. doi: 10.1007/s11042-017-5002-5.
Fu, XB., Yue, SL. & Pan, DY. Camera-based Basketball Scoring Detection Using Convolutional Neural Network. International Journal of Automation and Computing. 2021;18:266-276. doi: 10.1007/s11633-020-1259-7.
Žemgulys J, Raudonis V, Maskeliūnas R, Damaševičius R. Recognition of basketball referee signals from real-time videos. Journal of Ambient Intelligence and Humanized Computing. 2020;11:979-991. doi: 10.1007/s12652-019-01209-1.
Wu W. Injury Analysis Based on Machine Learning in NBA Data. Journal of Data Analysis and Information Processing. 2020;8(4):295-308. doi: 10.4236/jdaip.2020.84017.
Jauhiainen S, Kauppi JP, Leppänen M, Pasanen K, Parkkari J, Vasankari T, Kannus P, Äyrämö S. New Machine Learning Approach for Detection of Injury Risk Factors in Young Team Sport Athletes. Int J Sports Med. 2021;42(2):175-182. doi: 10.1055/a-1231-5304.
Sarlis V, Chatziilias V, Tjortjis C, Mandalidis D. A Data Science approach analysing the Impact of Injuries on Basketball Player and Team Performance. Information Systems. 2021;99:101750. doi: 10.1016/j.is.2021.101750.
Li RT, Kling SR, Salata MJ, Cupp SA, Sheehan J, Voos JE. Wearable Performance Devices in Sports Medicine. Sports Health. 2016;8(1):74-8. doi: 10.1177/1941738115616917.
Montgomery PG, Pyne DB, Minahan CL. The physical and physiological demands of basketball training and competition. Int J Sports Physiol Perform. 2010;5(1):75-86. doi: 10.1123/ijspp.5.1.75.
Taylor M, Nagle EF, Goss FL, Rubinstein EN, Simonson A. Evaluating Energy Expenditure Estimated by Wearable Technology During Variable Intensity Activity on Female Collegiate Athletes. Int J Exerc Sci. 2018;11(7):598-608.
Allen J. Six Pieces of Wearable Sports Technology Every Basketball Player Should Know. https://teamsoftomorrow.com/six-pieces-wearable-sports-technology-every-basketball-player-know/ (dostep: 2021.05.05).
Metulini R, Manisera M, Zuccolotto P. Space-Time Analysis of Movements in Basketball using Sensor Data. 2017; arXiv:1707.00883.
Metulini R, Metulini R, Manisera M, Zuccolotto P. Sensor Analytics in Basketball - PROCEEDINGS OF MATHSPORT INTERNATIONAL 2017. https://www.academia.edu/33677895/Sensor_Analytics_in_Basketball_PROCEEDINGS_OF_MATHSPORT_INTERNATIONAL_2017 (dostep: 2021.05.05).
Nguyen LNN, Rodríguez-Martín D, Català A, Pérez-López C, Samà A, Cavallaro A. Basketball activity recognition using wearable inertial measurement units. Proceedings of the XVI international conference on human computer interaction; 2015 Sep 7; Vilanova i la Geltru, Spain.
Bai L, Efstratiou C, Ang CS. weSport: Utilising Wrist-Band Sensing to Detect Player Activities in Basketball Games. WristSense 2016: Workshop on Sensing Systems and Applications Using Wrist Worn Smart Devices (co-located with IEEE PerCom 2016); 2016 Mar 14; Sydney, Australia.
Mangiarotti M, Ferrise F, Graziosi S, Tamburrino F, Bordegoni M. A Wearable Device to Detect in Real-Time Bimanual Gestures of Basketball Players During Training Sessions. Journal of Computing and Information Science in Engineering. 2019;19(1):011004. doi: 10.1115/1.4041704.
Maslakovic M. Smart basketball tracker: connected tech for aspiring players. https://gadgetsandwearables.com/2019/11/13/wearables-basketball/ (dostep: 2021.05.05).
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