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Ann Appl Sport Sci 2020, 8(1): 0-0 |
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Uzomba G C, Oladipo G S, Anugweje K C, Ogugua E A. The Regression Modelling of Kinanthropometric and Kinematic Variables in Relation to Ball Velocity of Nigerian Female Tennis Players. Ann Appl Sport Sci 2020; 8 (1)
URL: http://aassjournal.com/article-1-758-en.html
URL: http://aassjournal.com/article-1-758-en.html
1- Department of Anatomy, Faculty of Basic Medical Sciences, Alex Ekwueme Federal University, Ndufu-Alike, Ikwo, Ebonyi State, Nigeria , uzombagodwinchinedu@yahoo.com
2- Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, University of Port Harcourt, Port Harcourt, Rivers State, Nigeria
3- Institute of Sports Science, University of Port Harcourt, Port Harcourt, Rivers State, Nigeria
4- Department of Anatomy, Faculty of Basic Medical Sciences, Alex Ekwueme Federal University, Ndufu-Alike, Ikwo, Ebonyi State, Nigeria
2- Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Sciences, University of Port Harcourt, Port Harcourt, Rivers State, Nigeria
3- Institute of Sports Science, University of Port Harcourt, Port Harcourt, Rivers State, Nigeria
4- Department of Anatomy, Faculty of Basic Medical Sciences, Alex Ekwueme Federal University, Ndufu-Alike, Ikwo, Ebonyi State, Nigeria
Abstract: (3921 Views)
Background. Kinanthropometric and Kinematic variable are important in the understanding of performance in various sports. These variables have not been explored among Tennis players in Nigeria.
Objectives. An exploration to establish a regression model for kinanthropometric and kinematic variables in relation to ball velocity of Nigerian Female Tennis Players.
Methods. Data were collected through direct standard anthropometric protocol and kinematic videographic technique with four Vicon MX 13 cameras. Subjects for the study were drawn from Nigerian female tennis players who participated in the 14th West African University Games and 19th National Sports Festival. Forty-six (46) of the athletes gave their consent to participate in the study, which took place between October to December, 2018. Data were analyzed using SPSS version 23 to obtain mean, standard deviation, range, Pearson correlation Moment Coefficients and Regression linear analysis which was used to test the hypotheses at 0.05 significant levels.
Results. Results from this study revealed that there was 60% prediction of interactions of the kinanthropometric and kinematic variables to ball velocity. The results further revealed statistically significant difference in the predicted variables (kinanthropometric and kinematic) to ball velocity at p<0.05. The study recommends that during selection processes, coaches should strictly ensure that only athletes with suitable anthropometric features specific for each sport are recruited. Also, the relevant outcome of the analysis should be employed in developing tennis sports as it will contribute to improving performance and increasing accuracy.
Conclusion. Using standard anthropometric protocols and videographic techniques to establish typical performance profile for Nigerian players would ensure a more reasonable assessment of match performances and assist to set practical training and match targets for coaches and athletes.
Objectives. An exploration to establish a regression model for kinanthropometric and kinematic variables in relation to ball velocity of Nigerian Female Tennis Players.
Methods. Data were collected through direct standard anthropometric protocol and kinematic videographic technique with four Vicon MX 13 cameras. Subjects for the study were drawn from Nigerian female tennis players who participated in the 14th West African University Games and 19th National Sports Festival. Forty-six (46) of the athletes gave their consent to participate in the study, which took place between October to December, 2018. Data were analyzed using SPSS version 23 to obtain mean, standard deviation, range, Pearson correlation Moment Coefficients and Regression linear analysis which was used to test the hypotheses at 0.05 significant levels.
Results. Results from this study revealed that there was 60% prediction of interactions of the kinanthropometric and kinematic variables to ball velocity. The results further revealed statistically significant difference in the predicted variables (kinanthropometric and kinematic) to ball velocity at p<0.05. The study recommends that during selection processes, coaches should strictly ensure that only athletes with suitable anthropometric features specific for each sport are recruited. Also, the relevant outcome of the analysis should be employed in developing tennis sports as it will contribute to improving performance and increasing accuracy.
Conclusion. Using standard anthropometric protocols and videographic techniques to establish typical performance profile for Nigerian players would ensure a more reasonable assessment of match performances and assist to set practical training and match targets for coaches and athletes.
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APPLICABLE REMARKS
APPLICABLE REMARKS
- Relevance of Videographic approach and kinematic software in tracing kinematic angles which were used for the combination of anthropometric variables in improving Nigerian female tennis performance.
- Determination of extent of relationship between kinematic and anthropometric variables of female tennis players using multiple linear regression analysis.
- Determination of extent of relationship between kinematic and anthropometric variables of female tennis players using multiple linear regression analysis.
Type of Study: Original Article |
Subject:
Sport Biomechanics and its related branches
Received: 2019/06/22 | Accepted: 2019/09/22
Received: 2019/06/22 | Accepted: 2019/09/22
References
1. Saxton J. Exercise and chronic disease: an evidence-based approach: Taylor & Francis; 2011. [DOI:10.4324/9780203877043]
2. Kovacs M, Ellenbecker T. An 8-stage model for evaluating the tennis serve: implications for performance enhancement and injury prevention. Sports Health. 2011;3(6):504-13. [DOI:10.1177/1941738111414175] [PMID] [PMCID]
3. Martin C, Bideau B, Ropars M, Delamarche P, Kulpa R. Upper limb joint kinetic analysis during tennis serve: Assessment of competitive level on efficiency and injury risks. Scand J Med Sci Sports. 2014;24(4):700-7. [DOI:10.1111/sms.12043] [PMID]
4. Wong F, Keung JH, Lau NM, Ng DK, Chung JW, Chow DH. Effects of body mass index and full body kinematics on tennis serve speed. J Hum Kinet. 2014;40:21-8. [DOI:10.2478/hukin-2014-0003] [PMID] [PMCID]
5. Girard O, Micallef JP, Millet GP. Influence of restricted knee motion during the flat first serve in tennis. J Strength Cond Res. 2007;21(3):950-7.
https://doi.org/10.1519/R-20876.1 [DOI:10.1519/00124278-200708000-00049] [PMID]
6. Groppel JL, Roetert EP. Applied physiology of tennis. Sports Med. 1992;14(4):260-8. [DOI:10.2165/00007256-199214040-00004] [PMID]
7. Bahamonde RE. Changes in angular momentum during the tennis serve. J Sports Sci. 2000;18(8):579-92. [DOI:10.1080/02640410050082297] [PMID]
8. Hassan A. The launch angle of the ball and its relationship to the rectum serving accuracy of the Iraqi National Team players of Tennis: University of Baghdad; 2012.
9. Vaverka F, Cernosek M. Association between body height and serve speed in elite tennis players. Sports Biomech. 2013;12(1):30-7. [DOI:10.1080/14763141.2012.670664] [PMID]
10. Signorile JF, Sandler DJ, Smith WN, Stoutenberg M, Perry AC. Correlation analyses and regression modeling between isokinetic testing and on-court performance in competitive adolescent tennis players. J Strength Cond Res. 2005;19(3):519-26.
https://doi.org/10.1519/00124278-200508000-00007 [DOI:10.1519/R-15514.1] [PMID]
11. Goktepe A, Ak E, Sogut M, Karabork H, Korkusuz F. Joint angles during successful and unsuccessful tennis serves kinematics of tennis serve. Eklem Hastalik Cerrahisi. 2009;20(3):156-60.
12. Sanchis-Moysi J, Idoate F, Dorado C, Alayon S, Calbet JA. Large asymmetric hypertrophy of rectus abdominis muscle in professional tennis players. PLoS One. 2010;5(12):e15858. [DOI:10.1371/journal.pone.0015858] [PMID] [PMCID]
13. Elliott B. Biomechanics and tennis. Br J Sports Med. 2006;40(5):392-6. [DOI:10.1136/bjsm.2005.023150] [PMID] [PMCID]
14. Landlinger J, Lindinger S, Stoggl T, Wagner H, Muller E. Key factors and timing patterns in the tennis forehand of different skill levels. J Sports Sci Med. 2010;9(4):643-51. [DOI:10.1080/14763141.2010.535841] [PMID]
15. Swainson MG, Batterham AM, Tsakirides C, Rutherford ZH, Hind K. Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables. PLoS One. 2017;12(5):e0177175. [DOI:10.1371/journal.pone.0177175] [PMID] [PMCID]
16. Wagner H, Buchecker M, von Duvillard SP, Muller E. Kinematic description of elite vs. Low level players in team-handball jump throw. J Sports Sci Med. 2010;9(1):15-23.
17. Richtsmeier JT, Paik CH, Elfert PC, Cole TM, Dahlman HR. Precision, Repeatability, and Validation of the Localization of Cranial Landmarks Using Computed Tomography Scans. Cleft Palate-Craniofac J. 1995;32(3):217-27.
https://doi.org/10.1597/1545-1569(1995)032<0217:PRAVOT>2.3.CO;2
https://doi.org/10.1597/1545-1569_1995_032_0217_pravot_2.3.co_2 [DOI:10.1597/1545-1569(1995)0322.3.CO;2] [PMID]
18. Bingul BM, Aydin M, Ozbek A, Bulgan C, Gelen E. Upper extremity kinematics of flat serve in tennis. S Afr J Res Sport, Phys Educ Recreation. 2016;38(2):17-25.
19. Cui Y, Gomez MA, Goncalves B, Sampaio J. Performance profiles of professional female tennis players in grand slams. PLoS One. 2018;13(7):e0200591. [DOI:10.1371/journal.pone.0200591] [PMID] [PMCID]
20. Hornery DJ, Farrow D, Mujika I, Young W. An integrated physiological and performance profile of professional tennis. Br J Sports Med. 2007;41(8):531-6; discussion 6. [DOI:10.1136/bjsm.2006.031351] [PMID] [PMCID]
21. Filaire E, Alix D, Ferrand C, Verger M. Psychophysiological stress in tennis players during the first single match of a tournament. Psychoneuroendocrinology. 2009;34(1):150-7. [DOI:10.1016/j.psyneuen.2008.08.022] [PMID]
22. Ali A-HM. The relationship between anthropometric measurements and physical characteristics with the level of performance for tennis players. Sport Sci. 2015;8(2):40-6.
23. Amin M. Compared study between short- and long-distance swimmers, some biological characteristics: Helwan University; 2007.
24. Ulbricht A, Fernandez-Fernandez J, Ferrauti A. Conception for Fitness Testing and individualized training programs in the German Tennis Federation. Sport Orthop. 2013;29(3):180-92. [DOI:10.1016/j.orthtr.2013.07.005]
25. Mahjoub W. Learning and Sports Training schedule. Dar Wael Pub. and Printing: Oman; 2001.
26. Fleisig G, Nicholls R, Elliott B, Escamilla R. Kinematics used by world class tennis players to produce high-velocity serves. Sports Biomech. 2003;2(1):51-64. [DOI:10.1080/14763140308522807] [PMID]
27. Whiteside D, Elliott B, Lay B, Reid M. The effect of age on discrete kinematics of the elite female tennis serve. J Appl Biomech. 2013;29(5):573-82. [DOI:10.1123/jab.29.5.573] [PMID]
28. Hizan H, Whipp P, Reid M. Comparison of serve and serve return statistics of high performance male and female tennis players from different age-groups. Int J Perform Anal Sport. 2017;11(2):365-75. [DOI:10.1080/24748668.2011.11868556]
29. Cross R, Pollard G. Grand Slam men's singles tennis 1991-2009 serve speeds and other related data. Coaching Sport Sci Rev. 2009;16(49):8-10.
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