Assessing pre-season workload variation in professional rugby union players by comparing three acute:Chronic workload ratio models based on playing positions
Xiangyu Ren,
Simon Boisbluche,
Kilian Philippe,
Mathieu Demy,
Xiaopan Hu,
Shuzhe Ding,
Jacques Prioux
Affiliations
Xiangyu Ren
Sino-French Joint Research Center of Sport Science, Key Laboratory of Adolescent Health Assessment and Exercise Intervention of Ministry of Education, College of Physical Education and Health, East China Normal University, 200241, Shanghai, China; Movement, Sport, Health Laboratory, Rennes 2 University, 35170, Bruz, France; Department of Sports Sciences and Physical Education, École normale supérieure de Rennes, 35170, Bruz, France; Corresponding author. École normale supérieure de Rennes, Campus de Ker Lann, 11 Av. Robert Schuman, 35170, Bruz, France.
Simon Boisbluche
Rugby Club Vannes, French Rugby Federation, 56000, Vannes, France
Kilian Philippe
Laboratory of Movement, Balance, Performance and Health, University of Pau and Pays de l’Adour, Tarbes, EA-4445, France
Mathieu Demy
Rugby Club Vannes, French Rugby Federation, 56000, Vannes, France
Xiaopan Hu
Sino-French Joint Research Center of Sport Science, Key Laboratory of Adolescent Health Assessment and Exercise Intervention of Ministry of Education, College of Physical Education and Health, East China Normal University, 200241, Shanghai, China; Movement, Sport, Health Laboratory, Rennes 2 University, 35170, Bruz, France; Department of Sports Sciences and Physical Education, École normale supérieure de Rennes, 35170, Bruz, France
Shuzhe Ding
Sino-French Joint Research Center of Sport Science, Key Laboratory of Adolescent Health Assessment and Exercise Intervention of Ministry of Education, College of Physical Education and Health, East China Normal University, 200241, Shanghai, China
Jacques Prioux
Sino-French Joint Research Center of Sport Science, Key Laboratory of Adolescent Health Assessment and Exercise Intervention of Ministry of Education, College of Physical Education and Health, East China Normal University, 200241, Shanghai, China; Movement, Sport, Health Laboratory, Rennes 2 University, 35170, Bruz, France; Department of Sports Sciences and Physical Education, École normale supérieure de Rennes, 35170, Bruz, France
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 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.
