In this paper we tackle a problem of tile-based combat in the turn-based strategy (space 4X) video game Children of the Galaxy (CotG). We propose an improved version of Monte Carlo tree search (MCTS) called MCTS considering hit points (MCTS_HP). We show MCTS_HP is superior to Portfolio greedy search (PGS), MCTS and NOKAV reactive agent in small to medium combat scenarios. MCTS_HP performance is shown to be stable when compared to PGS, while it is also more time-efficient than regular MCTS. In smaller scenarios, the performance of MCTS_HP with 100 millisecond time limit is comparable to MCTS with 2 seconds time limit. This fact is crucial for CotG as the combat outcome assessment is precursor to many strategical decisions in CotG game. Finally, if we fix the amount of search time given to the combat agent, we show that different techniques dominate different scales of combat situations. As the result, if search-based techniques are to be deployed in commercial products, a combat agent will need to be implemented with portfolio of techniques it can choose from given the complexity of situation it is dealing with to smooth gameplay experience for human players.