Impact of Anthropometric Factor on Serve Velocities Evaluation Tennis Match at The 2019 US Open Grandslam Tournament

The purpose of this study is to analyze (a) anthropometric factor as multivariant regression model to predict the serves velocities of elite tennis player that compete in Roland Garros 2017. The athropometric factor was describe as, player height, player weight, age, and the Body Mass Index (BMI) of player. (b) this study also determind the significant level from the model to predict the serves speed. The data were collected from MATCH DETAILS BY IBM SLAMTRACKER. Results show that correlation between each independent variable (i.e, age, height, weight, BMI) to serves speed of the player respectively are -0.0094, 0.7457, 0.7135, and 0.1944. The data show us that variable Height and Weight have the most correlated predictors of tennis serves speed. More over the correlation level (R2) from the model was 0.5767 or 57.67 % it indicate that the model can predict 57.67% the dependent variable, i.e serve speed and the other 42.33% was determind by the other factor not included in model. The present finding underline the importance of player height and weight to determind the serves speed of the players that play in Roland Garros 2017.

Correlation Between Transabdominal Sonographically Measured Prostate Volume with Anthropometric Factor in Normal Healthy Subjects

To investigate the relationship between total prostate volume with anthropometric factor like age, height, weight and BMI. This can be useful in assessing the normality of prostate gland.Method: In 42 normal healthy subjects the length, anteroposterior and transverse diameters of prostate gland were measured & prostate volumes were calculated by using prolate ellipse formula. Age, height, weight of the subjects were recorded and body mass index calculated accordingly.Result: Correlation co-efficient or r test was used to find out the relationship between the variables. P value <0.05 was considered as statistically significant. Total prostatic volume correlation coefficient with age, weight and BMI were 0.907, 0.883 and 0.352 (p<0.001) respectively, but no significant correlation (r=0.133; p>0.05) was found between prostatic volume and height.Conclusion: Total prostate volume has a strong significant linear relationship & age, weight & BMI. But height does not correlate significantly with total prostate volume. Thus anthropometric factors like age, weight, BMI can therefore be used to predict prostate volume prior to ultrasound. DOI: http://dx.doi.org/10.3329/birdem.v2i1.12359 Birdem Med J 2012; 2(1) 29-32