Robot soccer competitions have been around for a while and have been a great environment to develop AI algorithms in. One of these environments is the AI world cup. The AI world cup environment is a virtual environment where two teams with five robots each play a soccer match. This paper focuses on defending the attacker that is carrying the ball in the AI world cup environment. This is achieved by comparing two approaches, a rule-based algorithm, and a Deep Deterministic Policy Gradient rein- forcement learning algorithm. The two algorithms are based on a coaching framework build by the TU Delft. This framework implements the actions of the robots, such as moving, jumping, and kicking the ball, and the communication between the robots. The two approaches have been evaluated and the rule-based outperforms the reinforce- ment learning algorithm. Furthermore, a teamwork strategy between the goalkeeper and defender has been developed, where this teamwork is a significant improvement over the non-teamwork algorithm.