Singular causation queries require an assessment of whether a singular co-occurrence of two events c and e was causal or simply coincidental. The current study builds on our previous research (Stephan & Waldmann, 2018) in which we proposed a computational model of singular causation judgments. The model highlights that singular causation judgments need to take into account the power of the target cause C and of alternative causes A, as well as the possibility of preemption. What was missing was a detailed model allowing us to estimate the probability of preemption of a target cause by the alternative causes. The present research fills this gap by elaborating the temporal assumptions that might enter assessments of singular causation. We focus on assumptions about temporal precedence between target and alternative causes, with a specific focus on assumptions about causal latency. We report the results of two new experiments supporting the model.