The Theory of Reinvestment argues that automated motor processes are disrupted when task-related declarative knowledge is used to control movement execution. Electroencephalographic (EEG) based high-alpha band (10-12 Hz) connectivity between the left temporal (verbal/analytic processing) area and the frontal (motor planning) area has been endorsed as a neurophysiological marker of the propensity for conscious processing of declarative knowledge during movement preparation. Our study investigated the utility of left temporal to frontal connectivity in characterizing optimal golf putting performance. Ten expert and ten novice right-handed male golfers putted 120 golf balls on a flat mat to a 2.4 m distant hole while the EEG was continuously recorded. Conscious processing was assessed by a putting-specific reinvestment scale. Functional connectivity in preparation to golf putts was computed as high-alpha inter site phase clustering (ISPC), and analyzed as a function of expertise (expert, novice), performance outcome (holed, missed) and psychological pressure (low, high). We found that left (but not right) temporal-frontal ISPC was lower in experts compared to novices (M experts = .39; M novices = .48). The experts also reported lower conscious processing compared to the novices (M experts = 2.80; M novices = 3.50). Furthermore, left temporal-frontal ISPC was higher in missed versus holed putts for experts (M holed= .37; M misses = .41) and novices (M holed = .44; M misses = .51). No pressure effect was revealed (M low = .42; M high = .45). Our findings suggest that experts engage in less conscious processing compared to novices, and, in line with the Theory of Reinvestment, suggest that errors in motor performance can be prompted by excessive conscious verbal/analytic interference with movement preparation and execution. Our study findings suggest that diminished communication between the left temporal (verbal/analytic) and the frontal (pre-motor) cortical areas during movement preparation and execution is a feature of skilled motor performance. This knowledge can now be used to design connectivity-based neurofeedback training protocols to expedite motor learning and improve motor skills.