The study first constructed a system of evaluation indicators, including five secondary and 21 tertiary indicators such as financial resources, site facilities and human resources. The weights were calculated using the combination assignment method, combining subjective weights based on the G1 method and objective weights from the projection seeking model algorithm, emphasizing the importance of human resources. The cloud model was applied to grade governance effectiveness, and most indicators were in the medium and high levels. The complexity and diversity of governance were revealed through quantitative and qualitative comparative Analysis (QCA) of a sample of 10 communities in H city. The results of the study showed that the similarity of community sports facilities as a percentage of expenditures in the 10 community samples in City H reached the high performance level (0.8601), while the similarity of the indicators of sports training and instruction, percentage of human resources in sports, public demand, and management of social organizations was at a lower level. To improve the effectiveness, it is recommended to strengthen the introduction and training of human resources, the construction of hardware facilities and publicity and promotion, and to optimize the organizational security. At the same time, modern technologies such as big data are utilized to establish a more efficient governance system to fully implement the concept.