Volleyball training apparel, a crucial aspect of sports equipment, must not only cater to the functional requirements of athletes but also exhibit an alluring and attention-grabbing aesthetic design, and proposes a method of generative adversarial network-based automatic generation of decorative patterns for volleyball training apparel. Design the generative adversarial network model structure, train the model, construct the clothing pattern feature data set, provide sample material for clothing pattern feature extraction, preprocess the clothing pattern based on generative adversarial network, and finally realize the reconstruction of the volleyball training clothing pattern. The experimental outcomes demonstrate that, in comparison to conventional pattern design methodologies, this approach enables the realization of a stylized design for the pattern, offering a unique and creative alternative, and not only ensure the completeness of pattern elements, but also ensure the integrity of pattern elements, and the quality of pattern design.