Existing work repeatedly addresses that the ubiquitous positioning devices will start to generate an unprecedented stream of time-stamped positions leading to storage and computation challenges. Hence the need for trajectory compression arises. The goal of this paper is to estimate the effect of compression in spatiotemporal querying; towards this goal, we present an analysis of this effect and provide a model to estimate it in terms of average false hits per query. Then, we propose a method to deal with the model's calculation, by incorporating it in the execution of the compression algorithm. Our experimental study shows that this proposal introduces a small overhead in the execution of trajectory compression algorithms, and also verifies the results of the analysis, confirming that our model can be used to provide a good estimation of the effect of trajectory compression in spatiotemporal querying.