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.

A Systematic Review of the Relationship between Workload and Injury Risk of Professional Male Soccer Players.

The number of studies on the relationship between training and competition load and injury has increased exponentially in recent years, and it is also widely studied by researchers in the field of professional soccer. In order to provide practical guidance for workload management and injury prevention in professional athletes, this study provides a review of the literature on the effect of load on injury risk, injury prediction, and interpretation mechanisms. The results of the research show that: (1) It appears that short-term fixture congestion may increase the match injury incidence, while long-term fixture congestion may have no effect on both the overall injury incidence and the match injury incidence. (2) It is impossible to determine conclusively whether any global positioning system (GPS)-derived metrics (total distance, high-speed running distance, and acceleration) are associated with an increased risk of injury. (3) The acute:chronic workload ratio (ACWR) of the session rating of perceived exertion (s-RPE) may be significantly associated with the risk of non-contact injuries, but an ACWR threshold with a minimum risk of injury could not be obtained. (4) Based on the workload and fatigue recovery factors, artificial intelligence technology may possess good predictive power regarding injury risk.

Analysis of the injuries and workload evolution using the RPE and s-RPE method in basketball

The quantification of training loads provides valuable information to reduce overtraining and detecting the risk of injury. The present study looks into the evolution of the training load using the RPE and s-RPE method and describes the injuries observed. It is an observational study based on 9 subjects of the Pardinyes basketball team (Leb Plata category) who, in each practice and match, recorded their RPE. This value, together with the volume (in minutes), provides the s-RPE. All injuries and their typology were also recorded during the first round of the competition. A total of 124 sessions were registered and 14 injuries were described in the period that went from 09/19/2019 to 02/15/2020. The load evolution of each player has been compared to the team average and to the one perceived by the coach. The lower extremity was, by far, the most injured one (13/14 injury events). The highest percentage of injuries was registered during the last part of the training sessions and matches, coinciding with the highest physical and psychological fatigue, and 64% of them were due to microtrauma. These inexpensive and easy-to-use methods (RPE and s-RPE) provide valuable data for planning, in order to adjust loads and prevent overtraining and injuries. It is necessary to manage workload to provide the player with the ideal stimulus, minimizing the risk of injury and, at the same time, maximizing their performance.

Internal training and match load quantification of one-match week schedules in female first league Portugal soccer team / Carga interna y cuantificación de la carga de entrenamiento de una semana de partido en una equipa femenina de fútbol de Portugal de la primera liga / Quantificação da carga interna de treino e de jogo em semanas com um jogo numa equipa feminina de futebol da primeira liga portuguesa

La cuantificación de la carga de entrenamiento (TL) permite a los entrenadores gestionar la carga durante el entrenamiento con el objetivo de estar en la mejor forma física para la próxima competición. El propósito de este estudio fue comparar la Percepción Subjetiva de Esfuerzo (s-RPE) y el Índice Hooper (HI) entre deportes y partidos de un solo equipo de fútbol de la principal liga femenina portuguesa. En este estudio participaron dieciséis jugadores con una media ± DE edad, altura y peso de 24,0 ±2,9 años, 164 ± 4,1 cm y 58,5 ± 8,2 kg, respectivamente. Los participantes completaron ≥80% de las sesiones de entrenamiento durante la temporada 2019/20. Los datos evaluados fueron s-RPE y HI, que midieron la calidad de la grasa, la fatiga, el estrés y el dolor muscular (DOMS). Los datos se analizaron en relación con elnúmero de días durante un microciclo competitivo (semana de juego), es decir, menos día de juego (MD-) con tres sesiones de entrenamiento por semana (MD-5; MD-4; MD-2). El estudio analizó datos para un total de 12 juegos y 45 sesiones de entrenamiento con ANOVA de medidas repetidas, p≤0,05. Los resultados mostraron diferencias entre MD-5 (85,2 ± 0,3min) vs MD-4 (87,2 ± 0,4min) vs MD-2 (80,6 ± 0.6min) vs MD (62,8 ± 4,9min), todos p <0,05; s-RPE mostró valores más altos en MD-5 (503,8 ± 19,0ua) vs MD-4 (473,2 ± 14,8ua) vs MD-2 (362,1 ± 12,1ua) vs MD (468, 2 ± 40,5ua); El HI mostró valores más altos en MD-5 (13,4 ± 0,5ua) frente a MD-4 (13,4 ± 0,4ua) frente a MD-2 (12,7 ± 0,5ua) frente a MD (11, 9 ± 0,4ua); DOMS reveló diferencias entre MD-4 vs MD-2 (3,1 ± 0,2 vs 2,7 ± 0,2ua), p<0,05. Se ha demostrado que existe una mayor carga de entrenamiento en el MD-5 y MD-4 en comparación con el MD-2. Los resultados de HI mostraron que la grasa, la fatiga, el estrés y DOMS estaban bien controlados por el equipo técnico y los jugadores. (AU)

Training load (TL) quantification allow coaches to a better load management during training sessions to be in the best physical fitness to the next match. The aim of this study was to compare session rated of perceived exertion (s-RPE) and Hooper Index (HI) between training and match days from the same women’s Portuguese League team. Sixteen players with a mean±SD age, height and weight of 24.0±2.9 years, 164±4.1 cm and 58.5±8.2 kg, respectively, participated in this study. The participants completed ≥80% of the training sessions during 2019/20 in-season. Data was collected through the s-RPE and the HI that measured sleep quality, fatigue, stress, and muscle soreness (DOMS). Data was analysed in relation to the number of days away from the competitive one-match week (i.e., match day minus, MD-) with three training sessions a week (MD-5; MD-4; MD-2).The study analysed data from a total of 12 matches and 45 training sessions with repeated measures ANOVA, p≤0.05. Results showed differences between MD-5 (85.2±0.3min) vs MD-4 (87.2±0.4min) vs MD-2 (80.6±0.6min) vs MD (62.8±4.9min), all p<0.05; s-RPE showed higher values on MD-5 (503.8±19.0au) vs MD-4 (473.2±14.8au) vs MD-2 (362.1±12.1au) vs MD (468.2±40.5au); HI showed higher values on MD-5 (13.4±0.5au) vs MD-4 (13.4±0.4au) vs MD-2 (12.7±0.5au) vs MD (11.9±0.4au); DOMS revealed difference between MD-4 vs MD-2 (3.1±0.2 vs 2.7±0.2au), p<0.05. It was shown that there is a higher TL on MD-5 and MD-4 compared with MD-2. Results from HI showed that sleep, fatigue, stress and DOMS was well fair controlled by coaches and staff. (AU)

A quantificação da carga de treino (CT) permite aos treinadores uma melhor gestão da carga dos jogadores durante as sessões de treino para que estejam na melhor condição física para o próximo jogo. O objetivo deste estudo foi comparar os valores da perceção subjetiva de esforço (s-RPE) e o Índice Hooper (HI) entre dias de treino e de jogo numa equipa feminina de Futebol da principal Liga feminina portuguesa. Participaram neste estudo dezasseis jogadoras com média ± DP de idade, altura e peso de 24,0 ± 2,9 anos, 164 ± 4,1 cm e 58,5 ± 8,2 kg, respetivamente. As participantes completaram ≥80% das sessões de treino durante a temporada de 2019/20. Os dados avaliados foram o s-RPE e o HI que mediu a qualidade do sono, fadiga, stresse e dor muscular (DOMS). Os dados foram recolhidos através do s-RPE e do IH que avaliaram a qualidade do sono, fadiga, stress e dor muscular (DOMS). Os dados foram analisados em relação ao número de dias para o jogo competitivo (ou seja, dia de jogo menos, MD-) com três sessões de treino por semana (MD-5; MD-4; MD-2). O estudo analisou 12 jogos e 45 sessões de treino através de medidas repetidas ANOVA, p≤0,05. Os resultados mostraram diferenças entre MD-5 (85,2±0,3min) vs MD-4 (87,2±0,4min) vs MD-2 (80,6±0,6min) vs MD (62,8±4,9min), todos p<0,05; s-RPE mostrou valores mais altos em MD-5 (503,8±19,0au) vs MD-4 (473,2±14,8au) vs MD-2 (362,1±12,1au) vs MD (468,2±40,5au); HI mostrou valores mais altos em MD-5 (13,4±0,5au) vs MD-4 (13,4±0,4au) vs MD-2 (12,7±0,5au) vs MD (11,9±0,4au); DOMS revelou diferença entre MD-4 vs MD-2 (3,1±0,2 vs 2,7±0,2au), p<0,05. Foi demonstrado que existe uma maior CT no MD-5 e MD-4 em comparação com o MD-2. Os resultados do HI mostraram que o sono, fadiga, stress e DOMS foi bem controlado pelos treinadores e staff. (AU)

Will Next Match Location Influence External and Internal Training Load of a Top-Class Elite Professional European Soccer Team?

BACKGROUND: The purpose of this study is to compare training load (TL) preceding a home versus away match in a top-class elite European team during the 2015-2016 season. METHODS: Twenty elite outfield soccer players with a mean ± SD age, height and body mass of 25.9 ± 4.6 years, 183.1 ± 6.6 cm and 78.6 ± 6.6 kg, respectively, participated in this study. Total distance covered, high-speed running distance (HSRD), average speed (AvS), rating of perceived exertion (RPE) multiplied by training duration (s-RPE) and Hooper index (HI) were collected. Data from 24 weeks were analyzed through match-day minus/plus approach (MD-5, -4, -3, -2, -1, MD + 1). RESULTS: All external TL variables indicated a decrease from MD-5 until MD-1 and then an increase to MD + 1 (p < 0.01). HI decreased from MD-5 to MD-1, but s-RPE increased until MD-3 and then decreased until MD + 1. When comparing TL data that preceded home matches versus away matches, for MD-5, HSRD and muscle soreness exhibited higher values when away match neared (p < 0.05). For MD-4 and MD-3, total distance, HSRD and AvS exhibited higher values closer to an away match than a home match (p < 0.05). For MD-1, total distances covered were higher closer to a home match than an away match (p < 0.01). For MD + 1, all HI items and AvS were higher when an away match was played (p < 0.05). CONCLUSIONS: This study confirms and provides evidence regarding the influence on internal and external TL data preceding home and away matches from a team that played in European competitions.

Training Periodization Over an Elite Rugby Sevens Season: From Theory to Practice.

PURPOSE: To describe the training periodization in rugby sevens players competing in the World Rugby Sevens Series during a non-Olympic season. METHODS: Workload data were collected over a 33-wk period in 12 male players participating in a full competitive season. Workload was quantified using session rating of perceived exertion and global positioning system-derived data during training and competition. Self-reported well-being was assessed using a questionnaire. Each variable was analyzed weekly and through 5 mesocycles (preseason, in-season 1-4), each of which ended with competition blocks. RESULTS: The perceived load decreased throughout the season for the full squad (-68% [26%] between preseason and final competitive block, large effect) and when unavailable players were removed from the analysis (-38% [42%], moderate). Weekly perceived load was highly variable, with a typical periodization in 4 phases during each mesocycle (regeneration, training overload, taper, and competition). During the preseason, the workload was higher during the overload training phase than during the competitive period (range: +23% to +59%, large to very large, for the distance covered above individual maximal aerobic speed and the number of accelerations). This observation no longer persisted during the season. The well-being score decreased almost certainly from in-season 3 (moderate). CONCLUSIONS: These results highlighted the apparent difficulty in maintaining high-load training periods throughout the season in players engaged on the World Rugby Sevens Series despite ∼4-7 training weeks separating each competitive block. This observation was likely explained by the difficulties inherent to the World Rugby Sevens Series (risk of contact injury, calendar, and multiple long-haul travel episodes) and potentially by limited squad-rotation policies.

Training load quantification in elite swimmers using a modified version of the training impulse method.

Prior reports have described the limitations of quantifying internal training loads using hear rate (HR)-based objective methods such as the training impulse (TRIMP) method, especially when high-intensity interval exercises are performed. A weakness of the TRIMP method is that it does not discriminate between exercise and rest periods, expressing both states into a single mean intensity value that could lead to an underestimate of training loads. This study was designed to compare Banister's original TRIMP method (1991) and a modified calculation procedure (TRIMPc) based on the cumulative sum of partial TRIMP, and to determine how each model relates to the session rating of perceived exertion (s-RPE), a HR-independent training load indicator. Over four weeks, 17 elite swimmers completed 328 pool training sessions. Mean HR for the full duration of a session and partial values for each 50 m of swimming distance and rest period were recorded to calculate the classic TRIMP and the proposed variant (TRIMPc). The s-RPE questionnaire was self-administered 30 minutes after each training session. Both TRIMPc and TRIMP measures strongly correlated with s-RPE scores (r = 0.724 and 0.702, respectively; P < 0.001). However, TRIMPc was ∼ 9% higher on average than TRIMP (117 ± 53 vs. 107 ± 47; P < 0.001), with proportionally greater inter-method difference with increasing workload intensity. Therefore, TRIMPc appears to be a more accurate and appropriate procedure for quantifying training load, particularly when monitoring interval training sessions, since it allows weighting both exercise and recovery intervals separately for the corresponding HR-derived intensity.