Accurate diagnosis of systematic errors affecting wind turbine operation is fundamental to maximize the energy capture. Based on this, this work deals with the systematic yaw error, occurring when the wind vane sensor is incorrectly aligned with the rotor shaft. The objective is formulating a method for individuating the presence and estimating the amount of systematic yaw error, based solely on Supervisory Control And Data Acquisition (SCADA) data analysis. The state of the art is based on inferring the presence of the static yaw error by detecting an under-performance. Therefore, there is a gap as regards the estimation of how much the static yaw error really is. The proposed method introduces major methodological novelties for tackling such issue. Indeed, nacelle wind speed measurements are used in this work because the presence of the systematic yaw error has a detectable effect on them and they are not influenced by the control system. Furthermore, this work is the first in the literature employing measurements collected with wind turbine stopped, which allows circumventing the presence of the assembly angle induced by the rotor rotation. The proposed method is based on the idea that, if two nacelle anemometers are present, the ratio between the two wind speed measurements should change in presence of a static yaw error. Through a test case discussion, it is shown that with the proposed method it is possible to estimate the static yaw error as reliably as with LiDAR measurements.