The Marine Predators Algorithm, known for its simplicity and efficiency, is a widely used optimization method. However, it is prone to structural bias, which can cause the algorithm to favor specific areas in the search space without considering the objective function. This bias can hinder exploration, leading to the population repeatedly visiting certain locations without gaining new information, resulting in increased computational burden. In this study, we extensively investigated the occurrence and types of structural bias in the Marine Predators Algorithm. We also assessed newly developed algorithm variants, such as the Opposition-based Local Escaping Marine Predator Algorithm, to determine their susceptibility to structural bias. To detect and analyze structural bias and its types, we employed a straightforward yet effective methodology called the signature test. Through a comprehensive analysis, we have identified algorithms that exhibit unbiased behavior. We believe that our analysis will serve as a valuable resource for practitioners interested in analyzing the theoretical aspects of their algorithms.