The integration of renewable energy generation into the power grid has become crucial for reducing carbon emissions and promoting environmental sustainability. However, uncertainties associated with renewable generation and electricity demand necessitate accurate netload forecasting to ensure reliable operation of the power system. In this work, we focus on the electricity balancing market, consisting of a system operator and multiple market participants. Market participants submit day-ahead bids based on forecast results to meet demand requirements, while the system operator determines the imbalance penalty based on the total imbalance across all participants. This generates a non-convex game among market participants, prompting an examination of equilibrium existence and uniqueness. Then, we demonstrate that, if an equilibrium exists, it supports maximal social welfare and, under certain conditions, minimizes total mismatch. Furthermore, we explore the local and global impacts of forecast errors under mild conditions, and conduct a robustness analysis. These findings provide mechanism design guidelines to enable data sharing and forecast method sharing among market participants in the balancing market.