This paper presents a performance comparison between two validation methods developed specifically for the Computational Electromagnetics purposes: the Feature Selective Validation (FSV) and the Feature Selective Normalized Mutual Information (FSNMI) index. To achieve this goal, a statistical analysis of 40 different cases of study (pairs of data sets) is carried out covering a wide range of real-life applications, such as, frequency domain, noisy and transient data, among others. The results provided an insight of the relationships between each method, showing that more effort is required to achieve generally coherent validation results between the FSV and the FSNMI.