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Today increasingly large volumes of TV and video are distributed over IP-networks and over the Internet. It is therefore essential for traffic and cache management to understand TV program popularity and access patterns in real networks. In this paper we study access patterns in a large TV-on-Demand system over four months. We study user behaviour and program popularity and its impact on caching. The demand varies a lot in daily and weekly cycles. There are large peaks in demand, especially on Friday and Saturday evenings, that need to be handled. We see that the cacheability, the share of requests that are not first-time requests, is very high. Furthermore, there is a small set of programs that account for a large fraction of the requests. We also find that the share of requests for the top most popular programs grows during prime time, and the change rate among them decreases. This is important for caching. The cache hit ratio increases during prime time when the demand is the highest, and aching makes the biggest difference when it matters most. We also study the popularity (in terms of number of requests and rank) of individual programs and how that changes over time. Also, we see that the type of programs offered determines what the access pattern will look like.