The paper presents a new subgrid-scale stress model for Large Eddy Simulations (LES) in complex geometries, based on the square of the velocity gradient tensor. This model accounts for both strain and rotation rates of the smallest resolved turbulent fluctuations, and recovers the proper $y^3$ near-wall scaling for the eddy viscosity without requiring dynamic procedures. The model is validated through a periodic turbulent pipe flow computation, demonstrating its ability to handle transition. The WALE (Wall-Adapting Local Eddy-viscosity) model is defined with four key properties: invariance to coordinate translations or rotations, ease of assessment on any computational grid, consideration of both strain and rotation rates, and natural zeroing at the wall. The model is shown to be well-conditioned numerically and effective in reproducing the expected features of turbulent flows, such as natural transition to turbulence and proper near-wall scaling. The WALE model is particularly promising for LES in complex geometries due to its simplicity and robustness.The paper presents a new subgrid-scale stress model for Large Eddy Simulations (LES) in complex geometries, based on the square of the velocity gradient tensor. This model accounts for both strain and rotation rates of the smallest resolved turbulent fluctuations, and recovers the proper $y^3$ near-wall scaling for the eddy viscosity without requiring dynamic procedures. The model is validated through a periodic turbulent pipe flow computation, demonstrating its ability to handle transition. The WALE (Wall-Adapting Local Eddy-viscosity) model is defined with four key properties: invariance to coordinate translations or rotations, ease of assessment on any computational grid, consideration of both strain and rotation rates, and natural zeroing at the wall. The model is shown to be well-conditioned numerically and effective in reproducing the expected features of turbulent flows, such as natural transition to turbulence and proper near-wall scaling. The WALE model is particularly promising for LES in complex geometries due to its simplicity and robustness.