To push the boundaries of technology, the world cup football for robots, RoboCup, is organized on a yearly basis since 1997. To push the boundaries of artificial intelligence, a simulated version of the RoboCup, AI World Cup Football, is arranged yearly from 2017. This requires skillful attackers, defenders and goalkeeper. A large part of having a competent goalkeeper, is having a well-anticipating goalkeeper. This research will improve the goalkeeper’s level of anticipation by finding its own weak spots. By training an attacker against this goalkeeper, the weak spots can be determined. Based on this data the goalkeeper can estimate in which region of the goal a real opponent is likely to score and decrease that scoring chance by making a move. Heuristics and a deep neural network are used to estimate how likely the attacker is to make a goal. The results show that the attacker that uses the deep neural network has a chance of scoring a goal which is about 10 to 15 percentage points higher than a random shooting attacker. The deep neural network attacker is however outperformed by the heuristic based player by about 15 to 20 percentage points. Taking that into account, embedding the heuristic based attacker into the goalkeeper gives the goalkeeper a good sense of what areas of the goal it should cover to decrease the likelihood of conceding a goal.