Classifying the Archery Performance with Conditional Effects on Angular and Linear Shooting Techniques


  • W. P. Loh School of Mechanical Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia.
  • Y. Y. Chong School of Mechanical Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia.


Angular Shooting, Archery Performance, Classification, Linear Shooting,


The archery sports skills are commonly assessed from the physical, psychological, biomechanical and perceptual aspects. Apparently, archers also encounter outdoor obstacles that potentially affect their performances. However, little is described on the different conditions encountered during the shooting in relation to archery techniques and its performances. The study aims to investigate archer’s shooting performances under outdoor conditional stresses, considering two shooting skills: Angular Shooting Technique (AST) and Linear Shooting Technique (LST). Outdoor experimental setups involving a university-level male archer performing 36 shots (6 ends of 6 arrows) each for the 70 m distance target using AST and LST techniques, under nine different conditions: morning, noon, night, hot, rain, calm, windy, cloudy and extreme 6-arrow-shot in 2 minutes were included. Recorded scores on Archery Score Pro software were used to determine the archery performances. The shooting techniques classification were based on the recorded arrow scores using Random Tree algorithm in the Waikato Environment for Knowledge Analysis (WEKA) tool. Classification analyses showed 83.3% distinguishable by shooting conditions; accurately classified by 97.9% on the extreme conditions, 98.1% for first three end shots and last three ends shots. Findings showed that AST outperforms the LST under different outdoor conditions.


D. L. Mann and N. Litke, “Shoulder injuries in archery,” Canadian Journal of Sports Sciences, vol. 14, pp. 85-92, 1989.

K. Stambolieva, M. Otzetov, D. Petrova, R. Ikonomov and P. Gatev, “Postural stability during static upright stance in archers,” Posture, Balance and the Brain International Workshop Proceedings, 2015, pp. 29-35.

A. Dabas, L. Singh and D. P. Sharma, “A personality assessment of top eight interuniversity male archers for various divisions of bow in India,” IOSR Journal of Sports and Physical Education, vol. 1, no. 3, pp. 31-32, 2014.

A. Vrbik, R. Bene and I. Vrbik, “Heart rate values and levels of attention and relaxation in expert archers during shooting,” Hrvat. Športskomed. Vjesn., vol. 30, pp. 21-29, 2015.

J. Roy and E. Suwarganda, “Archery: Emotion intensity regulation to stay in the zone during Olympic competition,” International Journal of Psychological Studies, vol. 7, no. 4, pp. 70-77, 2015.

A. Basumatary and T. N. Pramanik, “Comparative study of mood states between national and international male archers during senior national archery championship,” Online International Interdisciplinary Research Journal, vol. IV, pp. 123-128, 2014.

C-H. Quan, Z. Mohy-Ud-Din and S. Lee, “Analysis of shooting consistency in archers: A dynamic time-warping algorithm-based approach,” Journal of Sensors, vol. 2017, pp. 1-6, 2017.

Z. Taha, R. M. Musa, A. P. P. Abdul Majeed, M. M. Alim and M. R. Abdullah, “The identification of high potential archers based on fitness and motor ability variables: A Support Vector Machine approach,” Human Movement Science, vol. 57, pp. 184-193, 2018.

Z. Ahmad, Z. Taha, H. A. Hassan, M. A. Hisham, M.H. Johari and K. Kadirgama, “Biomechanics measurement in archery,” Journal of Mechanical Engineering and Sciences, vol. 6, pp. 762-771, 2014.

D. Simsek and H. Ertan, “The different release techniques in high level archery: A comparative case study,” 32 International Conference of Biomechanics in Sports, pp. 265-267, 2014.

P. E. Martin and G. D. Heise, “Archery bow grip force distribution: Relationship with performance and fatigue,” International Journal of Sports Biomechanics, vol. 8, pp. 305-319, 1992.

H. Pontzer, D. A. Raichlen, T. Basdeo, J. A. Harris, A. Z. P. Mabulla and B. M. Wood, “Mechanics of archery among Hadza huntergatherers,” Journal of Archaeological Science: Reports, vol. 16, pp. 57- 64, 2017.

K. Mukaiyama, K. Suzuki, T. Miyazaki and H. Sawada, “Aerodynamic properties of an arrow: Influence of point shape on the boundary layer transition,” Engineering Procedia, vol. 13, pp. 265–270, 2011.

J. Barton, J. Včelá, J. Torres-Sanchez, B. O’Flynn, C. O’Mathuna and R. V. Donahoe, “Arrow-mounted ballistic system for measuring performance of arrows equipped with hunting broadheads,” Procedia Engineering, vol. 34, pp. 455-460, 2012.

K. Okawa, Y. Komori, T. Miyazaki, S. Taguchi and H. Sugiura, “Free flight and wind tunnel measurements of the drag exerted on an archery arrow,” Procedia Engineering, vol. 60, pp. 67-72, 2013.

H. Ertan, B. Kentel, S. T. Tümer and F. Korkusuz, “Activation patterns in forearm muscles during archery shooting,” Human Movement Science, vol. 22, no. 1, pp. 37-45, 2003.

A. R. Soylu, H. Ertan and F. Korkusuz, “Archery performance level and repeatability of event-related EMG,” Human Movement Science, vol. 25, no. 6, pp. 767-774, 2006.

R. Balasubramaniam and A. M. Wing, “The dynamics of standing balance,” Trends Cognitive Science, vol. 6, no. 12, pp. 531-536, 2002.

S. Debnath and S. Debnath, “Image based biomechanical case study of an international archer,” International Conference on Sports Engineering (ICSE 2017), 2017.

W. Spratford and R. Campbell, “Postural stability, clicker reaction time and bow draw force predict performance in elite recurve archery,” Sports Science, vol 17, no. 5, pp. 539-545, 2017.

J. Aggarwala and M. Dhingra, “Effects of autonomic control on performance of archers: A comparative study on novice and experienced archers,” International Journal of Biomedical Research, vol 8, no. 4, pp. 182-186, 2017.

Y-T. Kim, J-H. Seo, H-J. Song, D-S. Yoo, H. J. Lee, J. Lee, G. Lee, E. Kwon, J. G. Kim and Y. Chang, “Neural correlates related to action observation in expert archers,” Behavioral Brain Research, vol 223, no. 2, pp. 342-347, 2011.

C-H. Quan, Z. Mohy-Ud-Din and S. Lee, “Analysis of shooting consistency in archers: A dynamic time warping algorithm-based approach,” Journal of Sensors, vol 2017, pp. 1-6, 2017.

R. P. Bunker and F. Thabtah, “A machine learning framework for sport result prediction,” Applied Computing and Informatics, 2017, in press.

M. Fratello and R. Tagliaferri, “Decision trees and random forests,” Reference Module in Life Sciences, 2018.

S. R. Kalmegh, “Comparative analysis of WEKA data mining algorithm Random Forest, Random Tree and LAD Tree for classification of indigenous news data,” International Journal of Emerging Technology and Advanced Engineering, vol 5, no. 1, pp. 507-517, 2015.

K. Haywood and C. Lewis, “Archery steps to success,” 4th ed: Human Kinetics, Inc. , 2014.




How to Cite

Loh, W. P., & Chong, Y. Y. (2018). Classifying the Archery Performance with Conditional Effects on Angular and Linear Shooting Techniques. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(3-2), 95–99. Retrieved from