Classical optimization algorithms are insufficient to solve non-linear problems. Even if it is an existing solution, it takes too much time to use it. Therefore, intelligent metaheuristic algorithms are used. General purposed intelligent metaheuristic techniques are evaluated in ten groups: Plant-based, biology-based, social-based, music-based, physicsbased, chemical-based, sports-based, mathematics-based, water-based, swarm-based, and hybrid methods. Sine Cosine Algorithm (SCA) is a mathematics based intelligent optimization algorithm that simulates a based on sine and cosine functions for general optimization. League Championship Algorithm (LCA) is a sports based intelligent optimization algorithm and simulates a championship for general optimization with artificial league and artificial teams for several weeks. In this article, LCA and SCA have been compared under equal conditions. Comparative analysis of these intelligent algorithms have been examined in complex benchmark functions. According to the simulation results, SCA has better performance within multi-modal functions than LCA while LCA has better results within unimodal functions under the same conditions according to the selected problem and algorithm parameters.