TY - THES
AU - Moyls, Peter William
PY - 1981
TI - Relationships between the velocity of the ice hockey wrist shot and selected human factors
KW - Thesis/Dissertation
LA - eng
M3 - Text
AB - The main purpose of this study was to investigate the relationships between the velocity of the ice hockey wrist shot and selected human factors in order to be able to predict the velocity of the wrist shot. A second objective was to identify the modifiable human factors most highly related with puck velocity in order to guide further research investigating the causal factors of a high speed wrist shot. Thirty-five subjects were selected from junior, intermediate, collegiate, senior and professional leagues to take part in the study. Their ages ranged from seventeen to twenty-nine. Forty-eight- strength, flexibility, muscle ratio, and anthropometric variables were measured in the Buchanan Fitness Centre at U.B.C. Puck velocity was measured by the use of a radar gun at the Thunderbird arena. Each subject shot a minimum of five shots and the top three scores were averaged to give the puck velocity score. With this data, Stepwise Regression and All Possible Subsets Regression techniques were used to find the best possible regression equation for predicting puck velocity. The product-moment correlations of puck velocity with each variable were tested for significance at the .05 level. The following correlations were significant: arm adduction at the shoulder of the lower arm, forearm supination of the upper arm, wrist strength in extension of the upper arm, wrist strength in flexion of the lower arm, and diagonal arm strength of the lower arm. The best linear regression equation found for predicting puck velocity was: [equations not included] Several transformations were performed on the data in an attempt to reduce the amount of uncertainty in the prediction equation. It was found that cubing the strength variables led to a new regression equation which accounted for more of the uncertainty and used fewer variables. The best regression equation using transformed data was: [equations not included] This equation had a multiple R of .871 and a standard error of estimate of 3.74. The transformed data equation reduced the uncertainty by 10% with one fewer variable being required. It is recommended that the variables with a significant correlation with puck velocity and the variables in the untransformed data equation be investigated further by implementing them into a training program for hockey players. In this way it might be empirically verified that these factors are the causes of a fast shot.
N2 - The main purpose of this study was to investigate the relationships between the velocity of the ice hockey wrist shot and selected human factors in order to be able to predict the velocity of the wrist shot. A second objective was to identify the modifiable human factors most highly related with puck velocity in order to guide further research investigating the causal factors of a high speed wrist shot. Thirty-five subjects were selected from junior, intermediate, collegiate, senior and professional leagues to take part in the study. Their ages ranged from seventeen to twenty-nine. Forty-eight- strength, flexibility, muscle ratio, and anthropometric variables were measured in the Buchanan Fitness Centre at U.B.C. Puck velocity was measured by the use of a radar gun at the Thunderbird arena. Each subject shot a minimum of five shots and the top three scores were averaged to give the puck velocity score. With this data, Stepwise Regression and All Possible Subsets Regression techniques were used to find the best possible regression equation for predicting puck velocity. The product-moment correlations of puck velocity with each variable were tested for significance at the .05 level. The following correlations were significant: arm adduction at the shoulder of the lower arm, forearm supination of the upper arm, wrist strength in extension of the upper arm, wrist strength in flexion of the lower arm, and diagonal arm strength of the lower arm. The best linear regression equation found for predicting puck velocity was: [equations not included] Several transformations were performed on the data in an attempt to reduce the amount of uncertainty in the prediction equation. It was found that cubing the strength variables led to a new regression equation which accounted for more of the uncertainty and used fewer variables. The best regression equation using transformed data was: [equations not included] This equation had a multiple R of .871 and a standard error of estimate of 3.74. The transformed data equation reduced the uncertainty by 10% with one fewer variable being required. It is recommended that the variables with a significant correlation with puck velocity and the variables in the untransformed data equation be investigated further by implementing them into a training program for hockey players. In this way it might be empirically verified that these factors are the causes of a fast shot.
UR - https://open.library.ubc.ca/collections/831/items/1.0077228
ER - End of Reference