Construction of measurement index system of basketball players’ specific physical fitness training based on AI intelligence and neural network

The development of modern basketball has improved the ability of basketball to compete, and the competition is becoming increasingly intense. Both in attack and defense, they are more active and fiercer. Therefore, higher requirements have been put forward for the physical fitness of basketball players. If good physical fitness cannot be guaranteed, the development of various sports skills will become very difficult. In the actual training of basketball, the specialized physical training of basketball players has received widespread attention and is regarded as the main purpose and way to develop basketball. The status and role of specialized physical training for basketball players in physical education are receiving increasing attention, and specialized physical training has also attracted the attention of coaches. It is necessary to use a sports measurement index system as an objective basis for the testing and evaluation of athletes’ specialized physical training. It is particularly important to improve the training level and establish a scientific and reasonable comprehensive quality evaluation index system for basketball players. Based on neural networks, this article constructs a specialized physical training index system for basketball players and studies the measurement of specialized physical training for basketball players. The experimental data was collected from 100 outstanding basketball players and analyzed using a neural network model. Based on a combination of agility, strength, and endurance tests, the model successfully predicted a 6.68% improvement in performance for special physical training. The method used in this article employs advanced machine learning techniques, and the results demonstrate the potential of neural networks in sports science research.