Abstract
The main aim of this study was to evaluating the various relationships of the identified biomechanical variables towards the performance of spin bowling and evaluating the contribution of identified biomechanical variables and construction of predictive model. Five interuniversity level leg-spin bowlers were recruited from LNIPE, India, and their bowling actions were captured by three video cameras, in a field setting. A value of α = 0.05 was used for all tests as the criterion to determine the presence or absence of significance. Pearson’s product moment correlation coefficient (r) was used for evaluating the various relationships of the selected variables towards the performance of spin bowling. Significant relationship was found between the Angle of Release (r = 0.965, P < 0.05), Average Velocity (r = 0.541, P < 0.05), Elbow joint Right (r = -0.392, P < 0.05), Hip Joint left (r = 0.402, P < 0.05), and Shoulder joint left (r = -0.383, P < 0.05). Multiple Linear Regression was used for evaluating the contribution of identified biomechanical variables and construction of predictive model. The regression equation was reliable as the value of R 2 was 0.945. The two variables selected in that regression equation explain 94.5% of the total variability in lateral deviation of ball was good. Since F-value for that regression model was highly significant, the model was reliable. This study provides further understanding of the biomechanical variables are associated with skilled performance in cricket leg-spin bowling, which coaches should consider when training less-skilled performers. Article visualizations:
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