A new Monte Carlo sampling method narrows the five-order-of-magnitude gap in Shogi's state-space complexity. Researchers used a reverse search toward "King-King only" positions to identify legally reachable board configurations. This statistical approach provides a high-precision estimate of the game's total positions. The result helps AI developers better calibrate search algorithms for complex board games.