Back to Search Start Over

Optimization of training for professional rugby union players: investigating the impact of different small-sided games models on GPS-derived performance metrics.

Authors :
Ren X
Henry M
Boisbluche S
Philippe K
Demy M
Ding S
Prioux J
Source :
Frontiers in physiology [Front Physiol] 2024 Feb 12; Vol. 15, pp. 1339137. Date of Electronic Publication: 2024 Feb 12 (Print Publication: 2024).
Publication Year :
2024

Abstract

Introduction: Professional rugby union players can improve their performance by engaging in small-sided games (SSGs), which simulate the movement patterns of the game. This study collected metrics related to running performance and mechanical workload and their relative values from both forward and back positions, aiming to explore the impact of different SSGs factors on athlete workload, as well as the workload difference between official games (OGs) and SSGs. Methods: The monitored GPS data were collected from SSGs with different player numbers and pitch sizes (five sessions), SSG rules (5 weeks, four sessions per week), and OGs conducted throughout the year. Additionally, the study compared changes in players' sprinting performance before and after two SSG sessions. Results: Backs had greater workload than forwards. Less space and number of players SSG (4 vs. 4, 660 m <superscript>2</superscript> ) was conducive to facilitating training for players in acceleration and deceleration. Conversely, larger spaces were associated with improved running performance. However, the introduction of a floater had no significant impact on performance improvement. Additionally, the 7 vs. 4 model (seven players engaged with four opponents) resulted in the greatest workload during medium-hard accelerations (F = 52.76-88.23, p < 0.001, η <subscript>p</subscript> <superscript>2</superscript> = 0.19-0.28). Japan touch model allowed for more high-speed running training (F = 47.93-243.55, p < 0.001, η <subscript>p</subscript> <superscript>2</superscript> = 1.52). The workload performed by SSGs can almost cover that of OGs (F = 23.36-454.21, p < 0.05, η <subscript>p</subscript> <superscript>2</superscript> = 0.03-0.57). In the context of η <subscript>p</subscript> <superscript>2</superscript> , values around 0.01, 0.06 and 0.14 indicate small, medium and large effects respectively. Discussion: However, given the significantly higher workload of SSGs and the slight decrease in sprinting performance, further research is required to examine the training patterns of SSGs. This study provided insight into the impact of player numbers, pitch size, and rules on rugby-specific SSGs. Coaches should optimize SSG setups for enhanced training outcomes, ensuring the long-term development of physical capacity, technical and tactical skills.<br />Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br /> (Copyright © 2024 Ren, Henry, Boisbluche, Philippe, Demy, Ding and Prioux.)

Details

Language :
English
ISSN :
1664-042X
Volume :
15
Database :
MEDLINE
Journal :
Frontiers in physiology
Publication Type :
Academic Journal
Accession number :
38410810
Full Text :
https://doi.org/10.3389/fphys.2024.1339137