In the classical context, it is well known that, sometimes, if the search does not find its target, it is better to start the process anew again, known as resetting. The quantum counterpart of resetting also indicates speeding up the detection process by eliminating the dark states, i.e., situations where the particle avoids detection. In this work, we introduce a most probable position resetting (MPR) protocol in which we reset the particle in a position where the probability of finding the particle could have been maximum, provided one would let the system evolve unitarily in a given time window. In a tight-binding lattice model, there exists a 2-fold degeneracy (left and right) of the positions of maximum probability. The survival probability with optimal restart rate approaches zero (detection probability approaches one) when the particle is reset with equal probability on both sides. This protocol significantly reduces the optimal mean first-detected-passage time (FDT) and performs better even if the detector is far apart compared to the usual resetting protocols where the particle is brought back to the initial position. We propose a modified protocol, adaptive MPR, by making the associated probabilities of resetting to the right and left a function of resetting steps. In this protocol, we see a further reduction of the optimal mean FDT and improvement in the search process when the detector is far apart.