In this paper we propose a novel probabilistic broadcast protocol that reduces the average end-to-end latency by dynamically adapting to network topology and traffic conditions. It does so by using an unique strategy that consists in adjusting the fanout and preferred targets for different gossip rounds as a function of the properties of each node. Node classification is light-weight and integrated in the protocol membership management. Furthermore, each node is not required to have full knowledge of the group membership or of the network topology. The paper shows how the protocol can be configured and evaluates its performance with a detailed simulation model.