Assessing pre-season workload variation in professional rugby union players by comparing three acute:Chronic workload ratio models based on playing positions.

Quantifying the pre-season workload of professional Rugby Union players, in relation to their respective positions not only provides crucial insights into their physical demands and training needs but also underscores the significance of the acute:chronic workload ratio (ACWR) in assessing workload. However, given the diversity in ACWR calculation methods, their applicability requires further exploration. As a result, this study aims to analyze the workload depending on the player's positions and to compare three ACWR calculation methods. Fifty-seven players were categorized into five groups based on their playing positions: tight five (T5), third-row (3R), number nine (N9), center, and third line defense (3L). The coupled and uncoupled rolling averages (RA), as well as the exponentially weighted moving average ACWR method, were employed to compute measures derived from GPS data. Changes throughout the pre-season were assessed using the one-way and two-way analysis of variance. The results revealed that N9 covered significantly greater distances and exhibited higher player load compared to T5 and 3L [p < 0.05, effect size (ES) = 0.16-0.68]. Additionally, 3L players displayed the highest workload across various measures, including counts of accelerations and decelerations (>2.5 m s-2), accelerations (>2.5 m s-2), acceleration distance (>2 m s-2), high-speed running (>15 km h-1), very high-speed running (>21 km h-1, VSHR), sprint running (>25 km h-1, SR) distance. When using coupled RA ACWR method, centers exposed significantly greater values to T5 (p < 0.05, ES = 0.8) and 3R (p < 0.05, ES = 0.83). Moreover, centers exhibited greater (p < 0.05, ES = 0.67-0.91) uncoupled RA ACWR values for VHSR and SR than T5 and 3R. When comparing the three ACWR methods, although significant differences emerged in some specific cases, the ES were all small (0-0.56). In light of these findings, training should be customized to the characteristics of players in different playing positions and the three ACWR calculation methods can be considered as equally effective approaches.

Position-specific workload of professional rugby union players during tactical periodization training.

The positional workload characteristics in rugby union on three acquisition days (i.e. strength, endurance, and speed days) of tactical periodization are still relatively unknown. Therefore, the primary aim of this study was to shed light on the positional external workload variables (10 Hz Global Positioning System and accelerometer microtechnology) and internal workload indicators (the session rating of perceived exertion) of players in a professional rugby union team by utilizing and comparing two tactical periodization models. Twenty-six male players (15 forwards and 11 backs) were recruited from a French second-division rugby club. Data were obtained over 10 weeks of in-season home games: a total of 780 observations were analyzed. Student's t-test observed different external workload profiles between positions among acquisition days. Mean external workload values, except PlayerLoadslow, were significantly higher (p≤0.01; effect size: 0.41-1.93) for backs than forwards for all acquisition days. Moreover, forwards perceived a higher internal workload than backs on the strength day of both models. The findings demonstrate that applying these two tactical periodization models could result in effective rugby union training. Validating external and internal workload characteristics on tactical periodization acquisition days enables extensive analysis of training load monitoring data; these data can be utilized to discover the unique characteristics of each position and design position-specific acquisition days to improve performance.

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

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 m2) 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, ηp 2 = 0.19-0.28). Japan touch model allowed for more high-speed running training (F = 47.93-243.55, p < 0.001, ηp 2 = 1.52). The workload performed by SSGs can almost cover that of OGs (F = 23.36-454.21, p < 0.05, ηp 2 = 0.03-0.57). In the context of ηp 2, 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.

Effects of Tactical Periodization on Workload, Physical Fitness, and Well-Being in Professional Rugby Union Players During a Preseason Period.

ABSTRACT: Hu, X, Boisbluche, S, Philippe, K, Maurelli, O, Li, S, Xu, B, and Prioux, J. Effects of tactical periodization on workload, physical fitness, and well-being in professional rugby union players during a preseason period. J Strength Cond Res 38(1): 105-115, 2024-Tactical periodization (TP) emerged approximately 30 years ago and has recently gained considerable attention in rugby union (RU). It aims to develop specific physical fitness components with 3 acquisition days (strength, endurance, and speed). However, no study has investigated the effects of TP on workload, physical fitness, and well-being across an RU preseason. This study aimed to determine how RU players' workload response to TP focusing on positional differences, observe the influence of a TP preseason training program on aerobic fitness and neuromuscular performance between positions, and analyze the variation of well-being reported by forwards and backs from the 3 acquisition days. Thirty-two male players completed a 6-week TP protocol. External and internal workload variables were recorded through global positioning systems and session rating of perceived exertion (s-RPE) separately. Fitness assessments included Bronco and countermovement jump (CMJ) tests. The sum of well-being indices was measured using the Hooper index. Kruskal-Wallis H tests revealed that the highest values of PlayerLoad slow, PlayerLoad slow percentage, and s-RPE were found on endurance day and the lowest on speed day. Mann-Whitney U tests showed that 15 external workload parameters were higher in backs than forwards for each acquisition day. Small improvements were observed on the Bronco test. No differences were observed in CMJ performance during the preseason period and well-being values between acquisition days. This study provides unique insights into external and internal workload variables during each acquisition day. Furthermore, it highlights TP as an efficient theoretical concept to use in an RU context.

Effects of preseason training on body composition, running performance, biochemical markers and workload variation in professional rugby union players.

Few studies have examined the impact of a preseason training intervention through systematic measures in Pro D2 rugby union (RU). Therefore, this study aimed to describe the effects of 12 weeks of preseason training (three blocks) on body composition, running performance, biochemical markers, and workload (WL) variation in professional RU players. Physiological (physical and biochemical) responses to preseason WL were analyzed by examining changes in anthropometric characteristics, Yo-Yo intermittent recovery level 1 (Yo-Yo IR1) test, blood samples (BS), Hooper index (1-7), the 10-Hz global positioning system (GPS), and session rating of perceived exertion (s-RPE) in nineteen elite male players. Changes throughout the preseason were analyzed using the one-way and mixed-model analysis of variance. Significant (p < 0.01) improvements occurred in anthropometry and Yo-Yo IR1 running performance in forwards and backs. Total distance (p < 0.01) and impact (p < 0.05) during the second block were meaningfully higher than the other two blocks, with backs showing higher values than forwards. As expected, WL decreased significantly (p < 0.01) during the last training block. The WL variations were correlated with changes in biochemical markers over the preseason period. The collected data can be used for i) profiling French Pro D2 rugby championships players, ii) establishing effective training strategies, and iii) setting preseason WL expectations.