The purpose the study was to produce a multiple linear regression model for predicting pitching accuracy of softball pitcher. The information may provide an assisted tool for pitching training and selecting potential pitcher. There are twenty female softball players participated this study. Each subject performed 15 softball pitches, and the outcome of the accuracy was recorded. Finger strength was measured by standardized strength-grape procedure according to William and Wilkins's method. We found that 1) accuracy of pitching is associated with the finger strength of opposing muscle strength of median finger, opposing muscle strength of little finger, and length of player's training history; 2) Significant difference was found in finger strength when compared between the group with two different accuracy levels; 3) the regression model was generated as Y=0.427X1+1.105X2+0.517X3+3.850, (R square=0.583, Y: accuracy; X1: opposing muscle strength of median finger; X2: opposing muscle strength of third finger; X3: opposing muscle strength of little finger); 4) the pitch accuracy appears to be related to the time of player's professional experience; 5) the psychological factor may accounted for the remaining variability of the prediction model.
The purpose the study was to produce a multiple linear regression model for predicting pitching accuracy of softball pitcher. The information may provide an assisted tool for pitching training and selecting potential pitcher. There are twenty female softball players participated this study. Each subject performed 15 softball pitches, and the outcome of the accuracy was recorded. Finger strength was measured by standardized strength-grape procedure according to William and Wilkins's method. We found that 1) accuracy of pitching is associated with the finger strength of opposing muscle strength of median finger, opposing muscle strength of little finger, and length of player's training history; 2) Significant difference was found in finger strength when compared between the group with two different accuracy levels; 3) the regression model was generated as Y=0.427X1+1.105X2+0.517X3+3.850, (R square=0.583, Y: accuracy; X1: opposing muscle strength of median finger; X2: opposing muscle strength of third finger; X3: opposing muscle strength of little finger); 4) the pitch accuracy appears to be related to the time of player's professional experience; 5) the psychological factor may accounted for the remaining variability of the prediction model.
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