Measuring molecular evolution in bacteria typically requires estimation of the rate at which mutations accumulate in strains sampled at different times that share a common ancestor. This approach has been useful for dating ecological and evolutionary events that coincide with the emergence of important lineages, such as outbreak strains and obligate human pathogens. However, in multi-host (niche) transmission scenarios, where the pathogen is essentially an opportunistic environmental organism, sampling is often sporadic and rarely reflects the overall population, particularly when concentrated on clinical isolates. This means that approaches that assume recent common ancestry are not applicable. Here we present a new approach to estimate the molecular clock rate in Campylobacter that draws on the popular probability conundrum known as the ‘birthday problem’. Using large genomic datasets and comparative genomic approaches, we identify isolate pairs where common ancestry is inferred within the sample time-frame – analogous to a shared birthday. Identifying synonymous and non-synonymous substitutions, both within and outside of recombinant regions of the genome, we quantify clock-like diversification to estimate mutation rates for the common pathogenic species Campylobacter coli (2.4 x 10-6 s/s/y) and Campylobacter jejuni (3.4 x 10-6 s/s/y). Finally, using estimated mutation rates we assess the rate of turnover of lineages in our sample set over short evolutionary timescales. This provides a generalisable approach to calibrating mutation rates in populations of environmental bacteria and shows that multiple lineages are maintained, implying that large-scale clonal sweeps may take hundreds of years or more in these species.