The building sector is considered a leading contributor to global greenhouse gas emissions. Low-carbon buildings, which are vital to meeting climate change targets, must also emphasize human health and comfort, especially in sports buildings related to the general public’s well-being and health. Building envelope is one of the main factors that affect the energy required for building heating and cooling, indoor comfort, and daylight utilization. This research conducts a multi- objective optimization (MOO) of the sports building envelope, comprehensively considering embodied greenhouse gas emission, thermal load, and daylight performance. The parametric model of a sports building was built with Grasshopper in Rhino, and the performance was simulated by Ladybug and Honeybee plug-ins. Then the multi-objective optimization was conducted using Octopus with the target of maximizing Useful Daylighting Illuminance (UDI), minimizing the Thermal Load and Embodied Greenhouse Gas Emission, and considering design variables about material properties and window-to-wall ratio. The Pareto front solution set with the corresponding design parameters and performance results is obtained by Non-dominated Sorting Genetic Algorithm II (NSGA-II), and the three objectives are evaluated with the same weights. This approach will provide a reference for the sustainable design of sports buildings.