Shooting action training method

Abstract

The invention relates to a shooting action training method. The shooting action training method comprises the following steps: obtaining the shooting association data of a shooting action and a basketball moving state as well as shooting average by combining the basketball moving state information which is fed back by a basketball, the shooting actions of arms which are fed back by arm sleeves when the basketball is shot, and the shooting average which is fed back by a basket; comparing the shooting association data with a preset shooting action model which serves as a training standard, and finding and feeding back the difference between the shooting association data and the shooting action model to obtain training data, wherein the basketball moving state information comprises shooting trajectory, flying speed, rotating speed, and shooting angle; the shooting action comprises muscle power strength, power generating order, the postures of arms and fingers, and the action trajectory of the arms. The method is used for analyzing the coherent postures and muscle effectiveness of a basketball player in a shooting practice exercise, and giving posture correction and muscle power generation suggestions.

Description

technical field [0001] The present invention relates to physical education teaching technology, more specifically, relates to a shooting action training method. Background technique [0002] Traditional shooting training includes theoretical study and practical exercises. [0003] Theoretical learning is usually just to guide players through experience, including learning from textbooks, coaches and other objects. When learning through textbooks, the shortcomings are that it is basically a purely theoretical teaching, and it is impossible to "teach by example", and the process of transforming obscure theoretical texts into actual combat skills through the players' own learning and comprehension ability Relatively large. Moreover, it is almost impossible for the players themselves to verify whether the results of the learning are correct. When learning through coaches, compared with textbooks, it solves the problem of "teaching by example", but there is still a shortcoming...

AI Technical Summary

Problems solved by technology

When learning through textbooks, the shortcomings are that it is basically a purely theoretical teaching, and it is impossible to "teach by example", and the process of transforming obscure theoretical texts into actual combat skills through the players' own learning and comprehension ability Relatively large

And for the results of learning, it is almost impossible for the players themselves to verify whether they are correct

When learning through coaches, compared with textbooks, it solves the problem of "teaching by example", but there is still a shortcoming that coaches can only observe players' movements and training results from the surface, and the correlation between teaching quality and coaching level is very high. Large, and the number of players guided by an excellent coach is also very limited, which is not conducive to large-scale training and guidance, and the efficiency is extremely low

[0004] For practical exercises, there is a shooting training device disclosed in the prior art, but it can only count the level of shooting results, and cannot give suggestions or analysis to players

Players can only train with the method of "practice makes perfect"

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