The subject of this thesis is to investigate whether the Cerebellar Model Articulation Controller (CMAC) can be used to anticipate controller corrections and increase performance by reducing delays in humanoid robots. This question can be divided into two subquestions. Firstly, whether the CMAC is a suitable architecture for the prediction of controller actions for a humanoid soccer robot. Using a 2D model of a robotic leg, the results of this thesis show that the CMAC can indeed learn to anticipate a corrective control signal 30 ms ahead. Secondly, whether the architecture of the aforementioned setup can increase the performance of adequately passing a ball by reducing delays. The experiments show that the use of a CMAC can increase the performance of the robotic setup.