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Driving at large angles of sideslip does not necessarily indicate terminal loss of control, rather, it is the fundamental objective of the sport of drifting. Drift racing challenges drivers to navigate a course in a sustained sideslip by exploiting coupled nonlinearities in the tire force response. The current study explores some of the physical parameters affecting drift motion, both in simulation and experiment. Combined-slip tire models are used to develop nonlinear models of a drifting vehicle in order to illustrate the conditions necessary for stability. Experimental drift testing is conducted to observe the dynamics featured in the track data. An accelerometer array on the test vehicle measures the acceleration vector field in order to estimate the vehicle states throughout the drift testing. Neural networks are used to identify the patterns in the accelerations that correspond to sideslip excursions during drifts.