A Markov chain is a probabilistic model that generates a sequence of outcomes such that the probability of the next term in the sequence only depends on the current term. Even though the study of finite Markov chains applies elementary ideas from linear algebra and probability theory, the topic is rarely taught in either class. This is a shame because the ideas are straightforward and the applications are varied, compelling, and accessible. In this talk, the fundamentals of Markov chains—including the fundamental matrix, regular chains, absorption times, etc.—will be introduced through applications including the Super Bowl box pool, the Penney Ante game (made popular by Martin Gardner), the television game show The Chase, and Chutes and Ladders.