Forecasting Sustainable Mega-Event Host Cities Using a Random-Forest Composite Index

Abstract

Large-scale sporting events such as the Super Bowl and the NBA All-Star Weekend generate substantial social and economic value, but they also impose significant environmental pressures through energy consumption, transportation emissions, and urban infrastructure demands. As sustainability becomes an increasingly important criterion in event planning, host-city evaluation requires data-driven, multi-factor analysis rather than reliance on economic indicators alone. This study develops a quantitative sustainability assessment framework based on a Random Forest model, using multi-dimensional data from U.S. cities between 2019 and 2023. The model predicts 2029 environmental indicators and computes feature-importance weights for key sustainability determinants, including climate conditions, transportation capacity, carbon emissions, energy structure, economic strength, and urban density. These results are integrated into a composite sustainability index to evaluate host-city suitability. The dataset incorporates official statistics on climate, emissions, energy use, transportation infrastructure, and socioeconomic conditions. Results indicate that transportation systems, economic capacity, and emissions intensity are the dominant drivers of sustainable hosting potential. Application to NBA All-Star host-city analysis further reveals event-specific differences in factor importance. Overall, the framework provides an interpretable and scalable tool for sustainable mega-event planning.