Can evolution paths be explained by chance alone?

We propose a purely probabilistic model to explain the evolution path of a population maximum fitness. We show that after n births in the population there are about ln n upwards jumps. This is true for any mutation probability and any fitness distribution and therefore suggests a general law for the number of upwards jumps. Simulations of our model show that a typical evolution path has first a steep rise followed by long plateaux. Moreover, independent runs show parallel paths. This is consistent with what was observed by Lenski and Travisano (1994) in their bacteria experiments.