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The Contribution of Speed and Leg Muscle Strength to Passing Performance in University Football Students Mardepi Saputra; Riand Resmana; Yogi Arnaldo; Ardo Okilanda; Ozha Wahyu Pra Adha
Halaman Olahraga Nusantara : Jurnal Ilmu Keolahragaan Vol. 8 No. 1 (2025): Halaman Olahraga Nusantara (Jurnal Ilmu Keolahragaan)
Publisher : Universitas PGRI Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31851/hon.v8i1.21553

Abstract

Background and Study. Passing is a fundamental skill in football that requires not only technical proficiency but also adequate physical conditioning. This study aimed to examine the contribution of speed and leg muscle strength to passing performance among university students. Methods. A quantitative correlational design with multiple regression analysis was employed in this study. The participants were 100 male students from the Physical Education, Sport, and Recreation program. Data were collected using a 30-m sprint test to measure speed, a standing broad jump test to assess leg muscle strength, and a short passing test to evaluate passing performance. The data were analyzed using correlation and multiple regression techniques. Results. The results showed that speed was significantly correlated with passing performance (r = 0.62, p < 0.05), as was leg muscle strength (r = 0.58, p < 0.05). Both variables had significant partial and simultaneous effects on passing performance, accounting for 42% of the total variance. Discussion and Conlusions. These findings indicate that improving speed and leg muscle strength plays an important role in enhancing passing quality and effectiveness; therefore, these components should be prioritized in university football training programs.
Digital biomarkers for volleyball injury prediction: a systematic literature review Rudyanto Rudyanto; Frizki Amra; Ozha Wahyu Pra Adha; Abdur Rohim Fadlan
Lentera Negeri Vol. 6 No. 1 (2025): Lentera Negeri
Publisher : Indonesian Institute For Counseling, Education and Therapy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/992620

Abstract

The increased physical requirements of top-level volleyball players, such as the numerous high-intensity jumps and the quick eccentric landings, have contributed to the rise of overuse injuries and made athlete-monitoring technologies more important. Digital biomarkers extracted from wearable biosensors combined with artificial intelligence (AI) provide a scalable method to measure internal and external load, describe fatigue, and predict injury even before the appearance of symptoms. This systematic literature review provides an overview of the use of wearable biosensing, machine learning, and injury prediction in volleyball, including the common grounds between sports-technology and sports-medicine research fields. Following PRISMA 2020 guidelines, a search of the Scopus database returned 386 records, which were further reduced to 10 after a series of eligibility assessments and exclusions. The results were grouped into three main categories: performance and load monitoring, injury prediction, and biosensing and digital biomarkers. Research shows that inertial measurement units (IMUs) are the most widely used instruments in volleyball. They allow for automated jump detection and jump-load quantification using deep learning techniques such as temporal convolutional networks. Besides, personalized machine-learning models give better results than group-level models for monitoring overuse injuries. Newly developed textile and biochemical biosensors can also detect physiological biomarkers like lactate, extending monitoring beyond mere kinematics. The methods used are highly varied and mainly consisting of supervised learning on small, sport-specific cohort. There is very little external validation and football-specific injury endpoints are scarce. A brief theoretical detour in the review interprets digital biomarkers as a unified concept that combines both biomechanical and physiological monitoring. In a more practical sense, the review provides coaches and clinicians with a well-structured description of sensor placement, modeling strategies, and levels of validation maturity. Future studies should encourage synergistic sensor use, prospective volleyball-specific injury cohorts, model interpretability and standardization of reporting in order to make predictive analytics the basis of trustworthy injury-prevention decisions.
The Effect of Variation-Based Shadow Badminton Training on Improving the Footwork Ability of Sports Education Students Ade Zalindro; Abdur Rohim Fadlan; Ozha Wahyu Pra adha
Jurnal Patriot Vol 8 No 1 (2026): Jurnal Patriot
Publisher : Department of Coaching, Faculty of Sports Science, Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/patriot.v8i1.1207

Abstract

Problem : The low footwork skills of students are inextricably linked to the training methods employed in the learning process. Footwork training in badminton lectures has generally been conducted conventionally, involving monotonous repetition of basic movements, lacking variety, and providing minimal movement stimuli that mimic real-life playing conditions. Purpose : This study aims to determine the effect of variation-based shadow badminton training on improving the footwork abilities of Sports Education students.. Methods : The study used an experimental method with a pretest–posttest control group design. The study sample consisted of 90 students, divided into two groups: the experimental group (n = 45) and the control group (n = 45). The experimental group was given treatment in the form of variation-based shadow badminton training, while the control group was given conventional training. The research instrument used a nationally and internationally validated badminton footwork ability test. Data analysis was performed using normality tests, homogeneity tests, and independent sample t-tests with a significance level of 0.05. Resuluts : The results of the study showed that there was a significant increase in footwork ability in both groups (p < 0.05), but the increase in the experimental group was significantly higher than the control group (p = 0.000). Conclusion : These findings indicate that variation-based shadow badminton training significantly improves students' footwork skills. Therefore, variation-based shadow badminton training is recommended as an effective training method to improve the quality of badminton learning in higher education.