In golf, it is crucial that unintended shots, such as slices, be minimized. However, it has proven rather difficult to improve golf performance via investigations of the causes of slicing, as this particular phenomenon is induced by a cooperative effect by each segment of the body, rather than by a single postural anomaly. Thus, the objective of this study was to isolate and characterize the factors causing slicing, and to present possibilities for the improvement of golf performance via the minimization of the number of slices executed, using a three dimensional motion capture system, combined with multiple regression analysis, artificial neural network, and fuzzy logic techniques. This study obtained some interesting results, such as the following: (1) We isolated 9 slice-inducing factors, using a stepwise method. (2) Our artificial neural network (ANN) accurately separated 'slice' from 'normal' shots (classification rate: 100%). (3)We could present the possibility of reducing the number of slice using the fuzzy logic. We expect that our data might be eventually used to improve golf performance.