Objective: To investigate the association between the acute:chronic workload ratio (ACWR) and running-related injuries (RRI). Methods: This is a secondary analysis using a database composed of data from three studies conducted with the same RRI surveillance system. Longitudinal data comprising running exposure (workload) and RRI were collected biweekly during the respective cohorts’ follow-up (18–65 weeks). ACWR was calculated as the most recent (i.e., acute) external workload (last 2 weeks) divided by the average external (i.e., chronic) workload of the last 4, 6, 8, 10 and 12 weeks. Three methods were used to calculate the ACWR: uncoupled, coupled and exponentially weighted moving averages (EWMA). Bayesian logistic mixed models were used to analyse the data. Results: The sample was composed of 435 runners. Runners whose ACWR was under 0.70 had about 10% predicted probability of sustaining RRI (9.6%; 95% credible interval [CrI] 7.5–12.4), while those whose ACWR was higher than 1.38 had about 1% predicted probability of sustaining RRI (1.3%; 95% CrI 0.7–1.7). The association between the ACWR and RRI was significant, varying from a small to a moderate association (1–10%). The higher the ACWR, the lower the RRI risk. Conclusions: The ACWR showed an inversely proportional association with RRI risk that can be represented by a smooth L-shaped, second-order, polynomial decay curve. The ACWR using hours or kilometres yielded similar results. The coupled and uncoupled methods revealed similar associations with RRIs. The uncoupled method presented the best discrimination for ACWR strata. The EWMA method yielded sparse and non-significant results.