Variation Factors and Dynamic Modeling Analysis of Tennis Players’ Competitive Ability Based on Big Data Mining Algorithm

• Published in: Journal of sensors Vol. 2022; pp. 1 - 8
• Main Authors: Xie, Yanan, Bai, Bing, Zhao, Yunpeng
• Format: Journal Article
• Language: English
• Published: New York Hindawi 09.07.2022; John Wiley & Sons, Inc
• Subjects: Algorithms; Athletes; Big Data; Competition; Data mining; Dynamic models; Physical factors; Physical fitness; Players; Self control; Sports training; Tactics; Tennis; Training
• ISSN: 1687-725X; 1687-7268; 1687-7268
• DOI: 10.1155/2022/3880527

In order to fully tap the potential of tennis players, speed, strength, and endurance are further improved in physical factors. Improve the overall competitiveness of tennis to a higher level and further improve the scientific level of tennis training. This paper truly reflects the adaptability of athletes’ functional state to training load. At the same time, the data mining algorithm is used to analyze the correlation between athletes and athletes in the application of techniques and tactics. The results show that timely adjustment of training plan and training load can provide a scientific and objective basis for improving the guidance of combat readiness training. At the same time, adjusting the training plan and training load provides a scientific and objective basis for further improving the guidance of combat readiness training. This paper improves the metacognitive level of athletes’ participation, accurately and timely adjusts the athletes’ personal goals and realistic positioning, and timely feeds back the relevant information of the competition. Only by being good at creating a competition environment can athletes give full play to their advantages and actively seek and pursue improvement in the stage of competitive ability.