This study classified and analyzed groups of spectators of professional baseball through market segmentation and predicted the sports consumer behavior by using artificial neural networks model and logistic regression model. The results of hierarchical cluster analysis, K-means cluster analysis, cross-tabulation analysis and one-way ANOVA using PASW 18.0 and AMOS 18.0 suggest five clusters of consumer segments and by using Modeler 14.1, artificial neural networks model was made to predict the data. By using artificial neural networks model and logistic regression model, hit ratio was grasped about the spectator satisfaction and future consumption behavior. The results are as follow: The hit ratio were high in ‘cluster 5’ for artificial neural networks model(spectator satisfaction: 71.3%, future consumption behavior: 99.3%) and logistic regression(spectator satisfaction: 71.8%, future consumption behavior: 96.5%). Furthermore, cross-tabulation and one-way ANOVA was performed to understand the cluster's characteristic which had highest hit ratio about the spectator satisfaction and future consumption behavior. And through this marketing strategy was suggested.
