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Physical networks are networks composed of volume-occupying objects embedded in three-dimensional space. For example, a biological neural network is composed of neurons that are physical objects, which also have a corresponding connectome network that encodes their synaptic connections. Due to technological advances, data describing the full three-dimensional structure of physical networks are becoming increasingly available, providing an opportunity to ask fundamental questions about the relationship between physical objects and network structures. We investigate the influence of volume exclusion by introducing several link-based measures that capture different aspects of their physicality, such as their shape or size. Afterward, the relationship between these physical link measures and standard network centralities is investigated for each empirical network. Finally, we create model physical networks and compare them to empirical networks in order to achieve a better understanding of these relations. For many physical networks, the most physically confined links tend to have important network roles, which could provide additional perspectives on physical network growth processes and their evolved function.