A substantial amount of work has recently gone into localizing BitTorrent traffic within an ISP in order to avoid excessive and often times unnecessary transit costs. Several architectures and systems have been proposed and the initial results from specific ISPs and a few torrents have been encouraging. In this work we attempt to deepen and scale our understanding of locality and its potential. Looking at specific ISPs, we consider tens of thousands of concurrent torrents, and thus capture ISP-wide implications that cannot be appreciated by looking at only a handful of torrents. Secondly, we go beyond individual case studies and present results for the top 100 ISPs in terms of number of users represented in our dataset of up to 40K torrents involving more than 3.9M concurrent peers and more than 20M in the course of a day spread in 11K ASes. We develop scalable methodologies that allow us to process this huge dataset and get concrete quantitative answers rather than qualitative speculations to questions like: "what is the minimum and the maximum transit traffic reduction across hundreds of ISPs?", "what are the win-win boundaries for ISPs and their users?", "what is the maximum amount of transit traffic that can be localized without requiring fine-grained control of inter-AS overlay connections?".