The holy grail in process mining is a process discovery algorithm that, given an event log, produces fitting, precise, properly generalizing and simple process models. Within the field of process mining, conformance checking is considered to be anything where observed behaviour, e.g., in the form of event logs or event streams, needs to be related to already modelled behaviour. In the conformance checking domain, the relation between an event log and a model is typically quantified using fitness, precision and generalization. In this paper, we present metrics for fitness, precision and generalization, based on alignments and the newer concept named anti-alignments.