The present study evaluated a nationwide exercise intervention with Football Fitness in a small-scale society. In all, 741 adult participants (20-72 yrs) were successfully recruited for Football Fitness training in local football clubs, corresponding to 2.1% of the adult population. A preintervention test battery including resting heart rate (RHR), blood pressure, and body mass measurements along with performance tests (Yo-Yo Intermittent Endurance level 1 (Yo-Yo IE1), the Arrowhead Agility Test, and the Flamingo Balance Test) were performed (n = 502). Training attendance (n = 310) was 1.6 ± 0.2 sessions per week (range: 0.6-2.9), corresponding to 28.8 ± 1.0 sessions during the 18 wk intervention period. After 18 wks mean arterial pressure (MAP) was -2.7 ± 0.7 mmHg lower (P < 0.05; n = 151) with even greater (P < 0.05) reductions for those with baseline MAP values >99 mmHg (-5.6 ± 1.5 mmHg; n = 50). RHR was lowered (P < 0.05) by 6 bpm after intervention (77 ± 1 to 71 ± 1 bpm). Yo-Yo IE1 performance increased by 41% (540 ± 27 to 752 ± 45 m), while agility and postural balance were improved (P < 0.05) by ~6 and ~45%, respectively. In conclusion, Football Fitness was shown to be a successful health-promoting nationwide training intervention for adult participants with an extraordinary recruitment, a high attendance rate, moderate adherence, high exercise intensity, and marked benefits in cardiovascular health profile and fitness.
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http://dx.doi.org/10.1155/2016/7231545 | DOI Listing |
J Strength Cond Res
December 2024
Physical Activity, Physical Education, Sport and Health (PAPESH) Research Centre, Sports Science Department, Reykjavik University, Reykjavik, Iceland; and.
Oddsson, HR, Friðgeirsdóttir, KÝ, Hafliðadóttir, L, Einarsson, IÞ, Kristjánsdóttir, H, and Saavedra, JM. Differences in anthropometric parameters, physical fitness, and kicking speed in young football players according to performance level, playing position, and relative age effect: a population-based study. J Strength Cond Res XX(X): 000-000, 2024-The objectives of this study were to determine (a) the differences, both in male and female players, in anthropometric parameters, physical fitness, and kicking speed based on the players' level and position on the field; (b) whether there is a relative age effect based on the players' level, and (c) whether there is a relationship between the relative age effect and the anthropometric parameters, physical fitness, and kicking speed parameters.
View Article and Find Full Text PDFIntroduction: Research on the effects of training programs involving small-sided games (SSG) versus high-intensity interval training (HIIT) has been increasing in recent years. However, there is limited understanding of how an individual's initial physical fitness level might influence the extent of adaptations achieved through these programs. This study aimed to compare the impacts of SSG and HIIT on male soccer players, while also considering the players' athleticism, categorized into lower and higher total athleticism score (TSA).
View Article and Find Full Text PDFRev Med Suisse
December 2024
Service de chirurgie orthopédique et traumatologique, Centre hospitalier universitaire vaudois, 1011 Lausanne.
Sport participation in Switzerland is steadily growing, with 8% sustaining injuries while practicing. Most popular sports include hiking, cycling, swimming, alpine skiing, and fitness. Thirty percent of shoulder injuries in urban areas are sport-related, mainly from football, cycling, and alpine skiing.
View Article and Find Full Text PDFJ Sports Sci
December 2024
Applied Sport, Technology, Exercise and Medicine, College of Engineering, Swansea University, Swansea, Wales, UK.
This study first investigated how the probability of winning collision events is affected by technical characteristics among world-class, international female rugby union players, and second, whether enhanced performance of these technical characteristics was related to physical attributes. Carry and tackle events from 16 international matches played by a top-two world ranking team were coded according to technical characteristics and performance outcomes. Binary classification tree models revealed that carry performance was successfully predicted ( < 0.
View Article and Find Full Text PDFInt J Sports Physiol Perform
December 2024
Department of Sports Science and Clinical Biomechanics, Sport and Health Sciences Cluster (SHSC), University of Southern Denmark, Odense, Denmark.
Purpose: The abundance of data in football presents both opportunities and challenges for decision making. Consequently, this review has 2 primary objectives: first, to provide practitioners with a concise overview of the characteristics of machine-learning (ML) analysis, and, second, to conduct a strengths, weaknesses, opportunities, and threats (SWOT) analysis regarding the implementation of ML techniques in professional football clubs. This review explains the difference between artificial intelligence and ML and the difference between ML and statistical analysis.
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