The abuse of online games by automated programs, known as game bots, for gaining unfair advantages has plagued millions of participating players with escalating severity in recent years. The current methods for distinguishing bots and humans are based on human interactive proofs (HIPs), such as CAPTCHAs. However, HIP-based approaches have inherent drawbacks. In particular, they are too obtrusive to be tolerated by human players in a gaming context. In this paper, we propose a non-interactive approach based on human observational proofs (HOPs) for continuous game bot detection. HOPs differentiate bots from human players by passively monitoring input actions that are difficult for current bots to perform in a human-like manner. We collect a series of user-input traces in one of the most popular online games, World of Warcraft. Based on the traces, we characterize the game playing behaviors of bots and humans. Then, we develop a HOP-based game bot defense system that analyzes user-input...