Abstract
In table tennis competitions, the movement data of table tennis players plays an important role in daily training. In recent years, artificial intelligence technology has been widely used in sports competitions. With the development of artificial intelligence, how to use artificial intelligence to analyze sports video to obtain sports data of athletes has become more and more important. This paper is to use artificial intelligence to research and analyze the athletes in the table tennis competition, and then obtain the sports data of the athletes. This has important guiding significance for athletes and coaches in their daily training. Table tennis is a widely developed sport in China, and as China’s “national ball”, table tennis has always been in a leading position in the world table tennis competitions. It is widely loved by the public for its simple and easy access to sports facilities, low site requirements and sports methods. In this study, mathematical statistics and experimental methods were used. Combined with the application of the functional sports screen function test, 20 table tennis players from Shandong Sport University were selected as the test objects, and their sports performance was tested. The total score of 10 first-level athletes was 162 points, and the average score was 16.2 points. The total score of the 10 second-level athletes was 144 points, and the average score was 14.4 points. The performance of the first-level athletes was significantly higher than that of the second-level athletes. It showed that the first-level athletes were generally better than the second-level athletes in all aspects.
Published Version
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