Background: Brugada syndrome (BrS) is an inherited arrhythmia characterised by distinctive and variably expressed ECG features more commonly seen in the context of fever or specific drug challenge. Higher placement of right precordial leads, 2nd/3rd intercostal space (ICS), improves diagnostic yield due to localisation of substrate changes to epicardial right ventricular outflow tract (RVOT), but morphological manifestations due to this elevated configuration remain poorly characterised. Aims: To assess how electrode placement affects the detection of BrS phenotypes in simulated ECGs. Methods: A CT-derived biventricular model was generated from a patient with BrS, parameterised with fibres and universal ventricular coordinates (UVCs) using CARPentry Studio. Simulations were run in CARPentry (NumeriCor GmbH, Graz, Austria). Baseline activation used a fascicular model with a fast-conducting subendocardial layer. Activation sites were optimised via Sobol sampling (~1400 reaction-Eikonal simulations) to maximise correlation with an average ECG from ~51,000 UK Biobank participants. Apicobasal heterogeneity was applied via a slow delayed rectifier potassium channel conductance gradient. Brugada phenotypes were induced with transient outward potassium channel conductance upregulation (epi×5.5,mid×2.25) in the RVOT via monodomain simulations. To quantify spatial variability in ECG morphology, a grid of virtual electrodes was constructed on a CT-based torso reconstruction, centred around typical locations of V1-3 at ICS4/3. Using the phie-recovery method, extracellular potentials were recovered to compute the ECGs. Results: A characteristic BrS phenotype was successfully produced with a saddleback (Type II) pattern in V2 (ICS4), while a near-coved (Type I) pattern in V2 (ICS3), demonstrating diagnostic-grade changes without provocation. More superiorly located electrodes showed increasing J-point elevation and T-wave inversion, linking altered electrode-substrate spatial relationship to diagnostic ECG feature changes. Conclusion: Diagnostic ECG patterns changed solely based on a spatial shift. This positional dependence of the phenotype observed acts as a surrogate of how anatomical variability can alter diagnostic ECG classification.