The evidence base of surgical fracture care is extremely sparse with only few sound RCTs available. It is hypothesized that anthropometric factors relevantly influence mechanical conditions in the fracture gap, thereby interfering with the mechanoinduction of fracture healing. Development of a finite element model of a tibia fracture, which is the basis of an in silico population (n = 300) by systematic variation of anthropometric parameters. Simulations of the stance phase and correlation between anthropometric parameters and the mechanical stimulus in the fracture gap. Analysis of the influence of anthropometric parameters on statistical dispersion between in silico trial cohorts with respect to the probability to generate two, with respect to anthropometric parameters statistically different trial cohorts, given the same power assumptions. The mechanical impact in the fracture gap correlates with anthropometric parameters; confirming the hypothesis that anthropometric factors are a relevant entity. On a cohort level simulation of a fracture trial showed that given an adequate power the principle of randomization successfully levels out the impact of anthropometric factors. From a clinical perspective these group sizes are difficult to achieve, especially when considering that the trials takes advantage of a „laboratory approach “, i.e. the fracture type has not been varied, such that in real world trials the cohort size have to be even larger to level out the different configurations of fractures gaps. Anthropometric parameters have a significant impact on the fracture gap mechanics. The cohort sizes necessary to level out this effect are difficult or unrealistic to achieve in RCTs, which is the reason for sparse evidence in orthotrauma. New approaches to clinical trials taking advantage of modelling and simulation techniques need to be developed and explored.