Nowadays, digital media allows important facts to be turned and twisted both knowingly and unknowingly, leading to the spread of misinformation to a continuously growing audience with little or no consequences. Thus, it has become crucial to verify (or fact-check) the authenticity of the shared information. One of the critical tasks in such verification process is determining which statements could be fact-checked. The automatization of this task would reduce human bias in the selection of checkable statements and save valuable time, thus helping to increase the coverage of the verification, and, potentially, their effectiveness. Although detecting checkable statements has received attention in the literature, most techniques have focused only on English. In this context, this study evaluates the performance of different approaches for detecting checkable statements in Spanish. Experimental evaluation showed promising results, achieving similar performance to the state-of-the-art techniques for the English language.