Micro-management is a very important aspect of RTS games. It involves moving single units or groups of units effectively on the battle field, targeting the most threatening enemy units and use the unit's special abilities when they are the most harmful for the enemy or the most beneficial for the player. Designing good micro-management is a challenging task for AI bot developers. In this paper we address the micro-management sub-task of positioning units effectively in combat situations. Two different approaches are evaluated, one based on potential fields and the other based on flocking algorithms. The results show that both the potential fields version and the flocking version clearly increases the win percentage of the bot, but the difference in wins between the two is minimal. The results also show that the more flexible potential fields technique requires much more hardware resources than the more simple flocking technique.