Rockfall events attract significant attention and adverse reaction from the public, especially near highways and residential areas. Reliable hazard mapping and management require reliable predictions of rockfall kinematics and trajectories. However, the uncertainty related to rockfall behavior and model input parameters turns this task significantly difficult. Research conducted at the University of New Hampshire (USA) over the last decade developed Smart Rock (SR) sensors capable of instrumenting rockfall experiments while embedded in test blocks (natural rocks or fabricated concrete blocks). The latest SRs are small capsules 58.0 mm in length and 25.4 mm in diameter, equipped with a ±400 g and a ±16 g 3-axis accelerometer, a ±4000 dps high-rate gyroscope, and an altimeter. This paper summarizes the results of small-scale tests to determine coefficients of restitution of a granite block lying at angles ranging between 0° and 45°. One-kilogram concrete blocks reinforced with steel fibers were released under controlled conditions, and video and SR data were used to calculate coefficients of restitution from block translation and rotation. This research aims to enhance input parameters in rockfall modeling, which often disregards the contribution of block rotation in energy estimates. It was demonstrated that different surface inclinations produce distinct energy restitution responses. For surfaces inclined at 0° and 45°, the results show that block rotational kinetic energy increases from 0% to up to 40% of the translational energy after impact.