Selected Anthropometric and Physical Fitness Variables Relationship With
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Selected Anthropometric and Physical Fitness Variables Relationship with Performance of Sprinters, Middle and Long Distance Runners of Ethiopian Athletics Training Centers Amensisa Kebede, Daniel Kibrom, Woldegebreal Mezgebo, Sirak Habtemariam (Ph.D) & Samson Wondirad Abstract Similar studies of the present for Ethiopian junior running athletes are definitely lacking or even none. Therefore, cross-sectional study design was employed to explore the anthropometric and physical fitness profile of junior athletes aged 15 to 18 in Ethiopia. Sprinters, middle distance and Long distance runners from were included from Machew, Hagerselam, Bekoji, Deberberhan and Ethiopian sport academy training centers using available sample selection technique .Pearson correlation reveals that male sprinters best time is significantly correlated with BMI and also correlated with total leg length mean On the other hand Physical fitness variable of female sprinters speed and sit and reach are correlated with best time. Male middle distance athletes‘ best time is significantly correlated with male leg and female athletes‘ middle best time with leg length. Total age middle distance athletes are also positively correlated with the middle distance athletes. Height of male long distance total height and total leg length are also significantly correlated with athletic performance of long distance runners. The Physical fitness variables revealed that male wall sit total 5 power female are also correlated with long distance runner athletic performance. Paired t test indicates a statistically significant improvement in performance time to best time. For female athletes there was a statistically significant difference at the in score of female. Sprinters have greater agility score. There was a statistically significant difference in score of female BMI for the three groups. Similarly, for male athletes there was a statistically significant difference in score of male BMI. There was a statistically significant difference in score of male Speed for the events. More over there was a statistically significant difference in score of male leg power. There was also a statistically significant difference in score of male training age. A one way analysis of variance conducted also indicates that Performance change of male athletes‘ is significantly different across .Pair wise comparison between events and sex on performance change indicates significant difference in long distance whereas no difference was found either between or across sprinters or middle distance athletes. Stepwise multiple regressions indicate that sit and reach test explained 24.1% of the variance in female middle distance performance. Secondly, endurance test (1500m) explained 50.8 % of the variance in female long distance performance. And finally, height explained 33.9% of the variance in male middle distance performance:. However, no valuable indicator of sprinters performance is seen from the regression output. Keywords: Anthropometry, Athlete, Performance, Physical fitness, Speed and Sprint 1 Introduction Talent detection refers to the discovery of potential performers who are currently not involved in the sport in question. Talent identification refers to the process of recognizing current participants with the potential to become elite players. It entails predicting performance over various periods of time by measuring physical, physiological, psychological and sociological attributes as well as technical abilities either alone or in combination (Régnier, G., Salmela, J.H. and Russell, S.J., 1993). Talent selection involves the ongoing process of identifying athletes at various stages that demonstrates prerequisite levels of performance for inclusion in a given squad or team. Selection involves choosing the most appropriate individual or group of individuals to carry out the task within a specific context (Borms, 1996). In literature suggestions are made about the determinant factors in sports which can predict success and should be used for talent identification (Gemser, 2005). Selecting children for appropriate sport is the most demanding and the most responsible task for sport experts and kinesiology in general. Different sports are determined by authentic kinesiological structures and specific anthropological characteristics of an individual (Abernethy, 2005; Chapman, 2008). The success of an individual in a particular sport activity is predominantly determined by the compatibility of his/her anthropological characteristics (Morrow & James, 2005). Identifying potential athletes at an early age ensures that athletes receive specialized coaching and training to accelerate the talent development process. The reliable identification of future elite athletes permits clubs to focus their expenditure on more effective management of their resources. Thus, the researchers spotlighted in athletic training centres of Ethiopia focusing on selected anthropometric and physical fitness variables. Objectives of the Study The general objective of the study was to explore some factors of talent identification, detection and development profiles of Ethiopian athletic training centres. Methodology Research design The research design of this study was cross sectional study design. This design has a number of advantages, such as, collecting data at once, time saving and minimizing energy cost (Creswell, 2012). Results and Discussion Descriptive statistics of sprinters, middle and long distance runners Short distance, middle distance and long distance athletes‘ BMI, height, power, leg length, agility, age, speed, wall sit, sit and reach test, endurance test, entry time, current time and performance change was computed using descriptive statistics: Line chart, histograms, Pearson product moment correlation coefficient, paired t-test, one way ANOVA, two way ANOVA and stepwise multiple regression followed by interpretation and discussion. 2 Table 1. Study Participants Selected across Training Centre TRAINING CENTER Sex and Events Number F 17 SEX M 19 Sprint 11 ACADEMY EVENT Middle 15 Long 10 Total 36 F 10 SEX M 15 Sprint 10 BEKOJI EVENT Middle 11 Long 4 Total 25 F 9 SEX M 7 M 1 DEBR.BERHAN Sprint 4 EVENT Middle 6 Long 7 Total 17 F 6 SEX M 15 Sprint 8 HAGERSELAM EVENT Middle 7 Long 6 Total 21 F 16 SEX M 19 SPRINT 12 MACHEW EVENT MIDDLE 13 LONG 10 Total 35 Antropometric and physical fitness tests Short distance result : The results of this study showed that the average age of sprinters was 17yrs old. This is at the good level set for most athletes with such age. The mean age value of both male and female athletes is 17 with a deviation of less than 1 year. Mostly the athletes were expected to join the training centres for under 17 yrs old. As the table indicates, most of the athletes are found with the required age mean deviations. In the above table both female and male sprinters mean leg length is 88cm with 12cm variation for males and less than 8cm variation for females. The BMI score for male sprinters is also 20.7 and 20 for females. A considerable difference between gender sit and reach test mean result of male 10.6 and 15.9 with similar deviation of 8 and 7.5 consequatively is shown. The score is at Excellent for 3 Figure 1. Sprinters Field Test Results sit&reach wall sit dash board 50m shuttle run Standing Long jump 0 2 4 6 8 10 12 14 Standing dash board shuttle run wall sit sit&reach Long jump 50m Mean 2 10.29 6.55 3.51 12.59 Std 0.34 0.61 0.66 2.34 7.47 female and above average for males scale while rated according to most norm standards set for the test. However less mean results are observed for female speed, agility and power tests compared to males. Huston & Wojtys (1996) concluded that neuromuscular performance was different in females, causing females to fire hamstring muscles later than the males. The body may be compensating in different areas to achieve analogous ground reaction forces to remain competitive in sport-based actions, while stressing other components of the lower body kinematic system. On the other hand, the long broad jump or power score of sprinters is excellent when it is compared to the 16 year old athletes norm standard put for the test which is also quite similar with middle distance athletes mean score.But much below the average while compared with adults norm standard.The muscular streangth endurance wall sit test mean score of female middle and short distance athletes are quite surprisingly greater than their male associates. In addition, Kale et al. (2009) stated that jump power is the best indicator of sprinting ability. Results of Middle Distance Athletes. The mean height value of the long distance athletes is less than both male and female athletes of sprinters and middle distance runners. The power test score is also less than the average norm standards of the test. Siris (1986) indicated that the medium height of world elite sprinters is 177.9cm. However, Niels (2005) stated that there is no optimal height for sprinters, but there are an optimal range exclude sprinters who are very tall or very short in stature. However, the endurance mean test scores are quite similar with middle distance athletes result. Results of long distance athletes A paired – samples repeated measures T-test was conducted to evaluate the effect of the test of entrance time and their last best time. There was a statistically significant improvement in performance time 1(M=425.95, SD=520.94) to best time (M=413.13, SD=506.94), t (129) =4.05, p<.00 (two tailed). The mean decrease was 12.82 with 95% confidence interval ranging from 6.56 to 19.09. The eta squared statistics (0.34) indicated a large effect size. 4 Results for the Comparison of Main Effects on the Variables One way between event groups with split of female was conducted to explore the impact of selected anthropometric and physical fitness variables on female athletes‘ best performance. The female athletes were divided into three according to their events (sprint, middle and long). There was a statistically significant difference at the p<0.05 level in score of female agility for the three groups: [F (2, 55) = 10.42, P = 0.00].