Video-based phase analysis of technical errors in fundamental tennis skills among physical education students
Keywords:
Tennis, technical errors, video-based analysis, movement phase, physical educationAbstract
Background: Technical errors frequently occur during the acquisition of fundamental tennis skills, yet limited studies have systematically examined these errors across different movement phases using video-based analysis among physical education students. Objectives: This study aimed to analyze technical errors across four fundamental tennis techniques and three movement phases using a video-based analysis approach. Methods: A cross-sectional observational study was conducted with 36 physical education students selected through purposive sampling. Participants performed forehand, backhand, volley, and serve techniques, which were analyzed using video recordings and Kinovea software. Technical errors were evaluated independently by two trained observers across the preparation, execution, and follow-through phases. Data were analyzed using descriptive statistics and inferential analysis. Results: The serve demonstrated the highest proportion of technical errors (31.1%), followed by the forehand (28.3%), backhand (26.4%), and volley (14.2%). Errors occurred most frequently during the execution phase (45.0%). Statistical analysis indicated significant differences in technical error scores among the four techniques (p < .001). Conclusion: Video-based phase analysis enabled detailed identification of technique- and phase-specific technical errors in beginner tennis performers. These findings provide evidence to support phase-specific feedback strategies and instructional planning for improving fundamental tennis skills in physical.
Downloads
Author Biographies
Ruslan Ruslan, Department of Physical Education, Faculty of Sports and Health, Universitas Negeri Gorontalo, Gorontalo, Indonesia
Email: [email protected]
Joni Taufik Hidayat, Department of Physical Education, Faculty of Sports and Health, Universitas Negeri Gorontalo, Gorontalo, Indonesia
Alficandra Alficandra, Department of Physical Education, Faculty of Teacher Training and Education, Universitas Islam Riau, Pekanbaru, Indonesia
References
Aiken, L. R. (1985). Three Coefficients for Analyzing the Reliability and Validity of Ratings. ducational and Psychological Measurement, 45(1), 131–142. https://doi.org/10.1177/0013164485451012 DOI: https://doi.org/10.1177/0013164485451012
Belokurova, G., & Piazza, C. (2025). Tutorial C - Case Study – Predicting Student Success at High-Stakes Nursing Examinations (NCLEX) Using IBM SPSS Modeler and STATISTICA Data Miner 13 (pp. 317–337). Academic Press. https://doi.org/10.1016/B978-0-443-15845-2.00047-5 DOI: https://doi.org/10.1016/B978-0-443-15845-2.00047-5
Bobrownicki, R., MacPherson, A. C., Collins, D., & Sproule, J. (2019). The Acute Effects of Analogy and Explicit Instruction on Movement and Performance. Psychology of Sport and Exercise, 44, 17–25. https://doi.org/10.1016/j.psychsport.2019.04.016 DOI: https://doi.org/10.1016/j.psychsport.2019.04.016
Brito, A. V, Afonso, J., Silva, G., Fernandez-Fernandez, J., & Fernandes, R. J. (2024). Biophysical Characterization of the Tennis Serve: A Systematic Scoping Review with Evidence Gap Map. Journal of Science and Medicine in Sport, 27(2), 125–140. https://doi.org/10.1016/j.jsams.2023.10.018 DOI: https://doi.org/10.1016/j.jsams.2023.10.018
Brocherie, F., & Dinu, D. (2022). Biomechanical Estimation of Tennis Serve Using Inertial Sensors: A Case Study. Frontiers in Sports and Active Living, 4. https://doi.org/10.3389/fspor.2022.962941 DOI: https://doi.org/10.3389/fspor.2022.962941
Cai, W., Huo, Y., Liu, Y., Su, Y., Guo, H., Wang, L., Li, B., & Liang, T. (2025). Biomechanics in Bone Regeneration and Mechanobiology in Osteoblasts: Fundamental Concepts and Recent Progress. EngMedicine, 2(1), 100057. https://doi.org/10.1016/j.engmed.2025.100057 DOI: https://doi.org/10.1016/j.engmed.2025.100057
Collings, T. J., Gorman, A. D., Stuelcken, M. C., Mellifont, D. B., & Sayers, M. G. L. (2020). Do the Landing Mechanics of Experienced Netball Players Differ from Those of Trained Athletes Competing in Sports That do not Require Frequent Landings? Journal of Science and Medicine in Sport, 23(1), 48–52. https://doi.org/10.1016/j.jsams.2019.08.017 DOI: https://doi.org/10.1016/j.jsams.2019.08.017
Forte, P., Neiva, H. P., & Marinho, D. A. (2021). Sports Biomechanics: Monitoring Health and Performance. Journal of Men’s Health, 17(4), 4–6. https://doi.org/10.31083/jomh.2021.105 DOI: https://doi.org/10.31083/jomh.2021.105
Gao, J., & Zhang, G. (2024). Tennis Action Recognition and Evaluation with Inertial Measurement Unit and SVM. Systems and Soft Computing, 6, 200154. https://doi.org/10.1016/j.sasc.2024.200154 DOI: https://doi.org/10.1016/j.sasc.2024.200154
Genevois, C., Reid, M., Creveaux, T., & Rogowski, I. (2020). Kinematic Differences in Upper Limb Joints between Flat and Topspin Forehand Drives in Competitive Male Tennis Players. Sports Biomechanics, 19(2), 212–226. https://doi.org/10.1080/14763141.2018.1461915 DOI: https://doi.org/10.1080/14763141.2018.1461915
Hutting, N., Belton, J., Caneiro, J. P., Oliveira, V. C., Devan, H., Johnston, V., Moore, P., Richardson, J., Staal, J. B., & Walsh, N. (2025). Development and Content Validity of the Musculoskeletal Self-Management Questionnaire (MSK-SMQ). Musculoskeletal Science and Practice, 78, 103342. https://doi.org/10.1016/j.msksp.2025.103342 DOI: https://doi.org/10.1016/j.msksp.2025.103342
Irawan, R., Azam, M., Rahayu, S., Setyawati, H., Soedjatmiko, Adi, S., Priyono, B., & Nugroho, A. (2023). Biomechanical Motion of the Tennis Forehand Stroke: Analyzing the Impact on the Ball Speed Using Biofor Analysis Software. Physical Education Theory and Methodology, 23(6), 918–924. https://doi.org/10.17309/tmfv.2023.6.14 DOI: https://doi.org/10.17309/tmfv.2023.6.14
Jacquier-Bret, J., & Gorce, P. (2024). Kinematics Characteristics of Key Point of Interest during Tennis Serve among Tennis Players: A Systematic Review and Meta-Analysis. Frontiers in Sports and Active Living, 6. 1432030. https://doi.org/10.3389/fspor.2024.1432030 DOI: https://doi.org/10.3389/fspor.2024.1432030
Kibler, W. Ben, Sciascia, A., Tokish, J. T., Kelly, J. D., Thomas, S., Bradley, J. P., Reinold, M., & Ciccotti, M. (2022). Disabled Throwing Shoulder: 2021 Update: Part 2—Pathomechanics and Treatment. Arthroscopy: The Journal of Arthroscopic & Related Surgery, 38(5), 1727–1748. https://doi.org/10.1016/j.arthro.2022.02.002 DOI: https://doi.org/10.1016/j.arthro.2022.02.002
Knudson, D. (2021). Fundamentals of biomechanics (3rd ed.). Springer. https://doi.org/10.1007/978-3-030-51838-7 DOI: https://doi.org/10.1007/978-3-030-51838-7
Kolman, N. S., Huijgen, B. C. H., Visscher, C., & Elferink-Gemser, M. T. (2021). The Value of Technical Characteristics for Future Performance in Youth Tennis Players: A Prospective Study. PLOS ONE, 16(1), e0245435. https://doi.org/10.1371/journal.pone.0245435 DOI: https://doi.org/10.1371/journal.pone.0245435
Krizkova, S., Tomaskova, H., & Tirkolaee, E. B. (2021). Sport Performance Analysis with a Focus on Racket Sports: A Review. Applied Sciences, 11(19), 9212. https://doi.org/10.3390/app11199212 DOI: https://doi.org/10.3390/app11199212
Lakens, D. (2022). Sample Size Justification. Collabra: Psychology, 8(1), 33267. https://doi.org/10.1525/collabra.33267 DOI: https://doi.org/10.1525/collabra.33267
Landis, J. R., & Koch, G. G. (1977). The Measurement of Observer Agreement for Categorical Data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310 DOI: https://doi.org/10.2307/2529310
Marriott, K. A., & Birmingham, T. B. (2023). Fundamentals of Osteoarthritis. Rehabilitation: Exercise, Diet, Biomechanics, and Physical Therapist-Delivered Interventions. Osteoarthritis and Cartilage, 31(10), 1312–1326. https://doi.org/10.1016/j.joca.2023.06.011 DOI: https://doi.org/10.1016/j.joca.2023.06.011
McHugh, M. L. (2012). Interrater Reliability: The Kappa Statistic. Biochemia Medica, 22(3), 276–282. DOI: https://doi.org/10.11613/BM.2012.031
Naskrent, B., Grzywiński, W., Polowy, K., Tomczak, A., & Jelonek, T. (2022). Eye-Tracking in Assessment of the Mental Workload of Harvester Operators. International Journal of Environmental Research and Public Health, 19(9), 5241. https://doi.org/10.3390/ijerph19095241 DOI: https://doi.org/10.3390/ijerph19095241
Nijmeijer, E. M., Brals, F. D., Kempe, M., Elferink-Gemser, M. T., & Benjaminse, A. (2025). How are Athletes Trained to Move? A Systematic Review Exploring the Effects of Implicit and Explicit Learning on Biomechanics of Sport-Specific Tasks. Journal of Biomechanics, 184, 112671. https://doi.org/10.1016/j.jbiomech.2025.112671 DOI: https://doi.org/10.1016/j.jbiomech.2025.112671
Patidar, A., Thakur, P., Thakur, P., Shahane, S., & Dane, K. (2026). FDAnalytics: An AI-Powered E-Sports Player Performance Analyzer. Entertainment Computing, 58, 101153. https://doi.org/10.1016/j.entcom.2026.101153 DOI: https://doi.org/10.1016/j.entcom.2026.101153
Peiris, H., Dona, N. E., & Swartz, T. B. (2025). Analysis of the Impact of Unforced Errors in Tennis. International Journal of Sports Science & Coaching, 20(3), 1151–1161. https://doi.org/10.1177/17479541251333943 DOI: https://doi.org/10.1177/17479541251333943
Rigozzi, C. J., Vio, G. A., & Poronnik, P. (2023). Application of Wearable Technologies for Player Motion Analysis in Racket Sports: A Systematic Review. International Journal of Sports Science & Coaching, 18(6), 2321–2346. https://doi.org/10.1177/17479541221138015 DOI: https://doi.org/10.1177/17479541221138015
Schlüter, U., Arnold, S., Borghi, F., Cherrie, J., Fransman, W., Heussen, H., Jayjock, M., Jensen, K. A., Koivisto, J., Koppisch, D., Meyer, J., Spinazzè, A., Tanarro, C., Verpaele, S., & von Goetz, N. (2022). Theoretical Background of Occupational-Exposure Models-Report of an Expert Workshop of the ISES Europe Working Group "Exposure Models". International journal of environmental research and public health, 19(3), 1234. https://doi.org/10.3390/ijerph19031234 DOI: https://doi.org/10.3390/ijerph19031234
Teferi, G. & Endalew, D. (2020). Methods of Biomechanical Performance Analyses in Sport: Systematic Review. American Journal of Sports Science and Medicine, 8(2), 47–52. https://doi.org/DOI: 10.12691/ajssm-8-2-2
Wang, C., & Ni, P. (2026). Plantar Pressure Measurement Systems in Sports Biomechanics: a Review of Sensor Technologies and Applications for Performance and Injury Analysis. Sensor Review, 46(2), 186–206. https://doi.org/10.1108/SR-05-2025-0349 DOI: https://doi.org/10.1108/SR-05-2025-0349
Ye, Z., & Liu, H. (2025). The Role of Technology in Promoting Sports Participation among College Students. Education and Information Technologies, 30(16), 23549–23576. https://doi.org/10.1007/s10639-025-13669-4 DOI: https://doi.org/10.1007/s10639-025-13669-4
Published
How to Cite
Issue
Section
Copyright (c) 2026 Ruslan Ruslan, Joni Taufik Hidayat, Alficandra Alficandra
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This is an open-access article distributed under the terms of the Creative Commons Attribution-ShareAlike 4.0 International License which permits unrestricted use, distribution, and reproduction in any medium. Users are allowed to read, download, copy, distribute, search, or link to full-text articles in this journal without asking by giving appropriate credit, provide a link to the license, and indicate if changes were made. All of the remix, transform, or build upon the material must distribute the contributions under the same license as the original.
Accepted 2026-07-21
Published 2026-08-10
Indonesia
Philippines
Malaysia
Nigeria
Uzbekistan
Turkey
Iran
Bosnia and Herzegovina
Hungary
Romania
Burundi
Colombia
Ukraine
South Africa
Thailand
Ethiopia
Spain
India
.png)
.png)
