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Traffic congestion has worsened noticeably in San Francisco (SF) and other major cities over the past few years. Part of this change could reasonably be explained by strong economic growth or other standard factors such as road and transit network changes. It also corresponds to the emergence of Transportation Network Companies (TNCs), such as Uber and Lyft, raising the question whether the two may be related. The authors' research incrementally decomposes the contributors to increased congestion in SF between 2010 and 2016, namely, road and transit network changes, population growth, employment growth, TNC-volumes, and the effect of TNC pick-ups and drop-offs. The authors do so through a series of controlled travel demand model runs, supplemented with observed TNC-data collected from the Application Programming Interfaces of Uber and Lyft. The authors' results show road and transit network changes over this period have only a small effect on congestion. Socioeconomic factors contribute about a quarter of the congestion increase, and that TNCs are the biggest contributor to growing congestion over this period, contributing about half of the increase in vehicle hours of delay, worsening travel-time reliability. This study is more data rich and spatially detailed than past studies, providing a better understanding of where and when TNCs add to congestion. It gives transportation planners a better understanding of the causes of growing congestion, allowing them to more effectively craft strategies to mitigate or adapt to it.