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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

The relationship between recent (acute) training load relative to long-term (chronic) training load may be associated with sports injury risk. We explored the potential for modelling acute and chronic loads separately to address current statistical methodology limitations. We also determined whether there was any evidence of an interaction in the association between acute and chronic training loads and injury risk in football. A men’s Qatar Stars League football cohort (1 465 players, 1 977 injuries), where training load was defined as the number of minutes of activity, and a Norwegian elite U-19 football cohort (81 players, 60 injuries), where training load was defined as the session rating of perceived exertion (sRPE). Mixed logistic regression was run with training load on the current day (acute load) and cumulative past training load estimated by distributed lag non-linear models (chronic load) as independent variables. Injury was the outcome. An interaction between acute and chronic training load was modelled. In both football populations, we observed that the risk of injury on the current day for different values of acute training load was highest for players with low chronic load, followed by high and then medium chronic load. The slopes varied substantially between different levels of chronic training load, indicating an interaction. Modelling acute and chronic loads separately in regression models is a suitable statistical approach for analysing the association between relative training load and injury risk in injury prevention research. Sports scientists should also consider the potential for interactions between acute and chronic load.

The acute:chronic workload ratio (ACWR) is a metric that can be used to monitor training loads during sport. Over the last decade researchers have investigated how this metric relates to injury, yet little consideration has been given to how this metric interacts with performance. Two prospective longitudinal studies were implemented investigating internal and external ACWRs and match outcome in junior tennis players. Forty-two and 24 players were recruited to participate in the internal and external load studies, respectively. Internal load was measured using session rate of perceive exertion, while external load was defined as total swing counts. The main dependent variable was tennis match performance which was extracted from the universal tennis rating website. The ACWR for internal and external load were the primary independent variables. Acute load was defined as the total load for one week, while a 4-week rolling average represented chronic load. There were no significant associations between internal (p-value = .23) or external (p-value = .81) ACWR and tennis match performance as assessed by multivariate regressions. The ACWRs in these datasets were close to 1.00, thus a balanced training load was undertaken by these athletes upon entering match play but was not related to match success.

The two aims of this study were: (i) to analyse the correlations between weekly acute workload (wAW), chronic workload, acute/chronic workload rate (wACWR), training monotony and strain and the weekly (w) reports of delayed onset muscle soreness, wFatigue, wStress, wSleep quality, and the Hooper indicator (wHI); (ii) to analyse the relationships between early, mid and end preparation season (PS) and the full PS. Ten elite young wrestlers participated in this study. The subjects who were included in this research were wrestlers participating in competitions organized by the National Turkish Wrestling Federation. The subjects were monitored for 32 weeks and were divided into three time periods: early PS, W1 to W11; mid PS, W12 to W22; and end PS, W23 to W32. Very large correlations were found for wAW and wACWR with wFatigue and wHI during end PS. Also, the same workload parameters were significantly correlated with wStress (r = 0.66; P = 0.03), wSleep (r = 0.78; P = 0.004), and wHI (r = 0.72; P = 0.01) during mid PS. The results of this study offer new perspectives for specialists regarding the perceived level of load and the variations of wellbeing during a PS at the level of elite young wrestlers.

Abstract Background The purpose of the present study was to explore the feasibility of collecting GPS data and the usability of GPS data to evaluate associations between the training load and onset of running-related knee injuries (RRKIs). Methods Participants of the INSPIRE-trial, a randomized-controlled trial on running injury prevention, were asked to participate in this study. At baseline, demographic variables were collected. Follow-up questionnaires assessed information on RRKIs. Participants with a new reported RRKI and uninjured participants were sent a GPS export request. Weekly GPS-based training distances were used to calculate Acute:Chronic Workload Ratios (ACWRs). Results A total of 240 participants (62.7%) tracked their running training sessions with the use of a GPS-enabled device or platform and were willing to share their GPS data. From the participants (N = 144) who received a GPS export request, 50.0% successfully shared their data. The majority (69.4%) of the shared GPS data were usable for analyses (N = 50). GPS data were used to present weekly ACWRs of participants with and without an RRKI eight weeks prior to RRKI onset or running event. Conclusions It seems feasible to collect GPS data from GPS-enabled devices and platforms used by recreational runners. The results indicate that GPS data is usable to calculate weekly ACWRs to evaluate associations between training load and onset of RRKIs in recreational runners. Therefore, GPS-based ACWR measures can be used for future studies to evaluate associations between training load and onset of RRIs.

Abstract Background The interpretation of the load variations across a period seems important to control the weekly progression or variation of the load, or to identify within- micro and mesocycle variations. Thus, the aim of this study was to describe the in-season variations of training monotony, training strain, and acute: chronic workload ratio (ACWR) through session rating of perceived exertion (s-RPE), total distance and high-speed running (HSR) according to playing positions in an elite soccer team. Methods Seventeen professional players from an European First League team participated in this study. They were divided four central defenders (CD), three wide defenders (WD), four central midfielders (CM), three wide midfielders (WM) and three strikers (ST). The players were monitored daily over a 41-week period of competition where 52 matches occurred during the 2015–2016 in-season. Through the collection of s-RPE, total distance and HSR, training monotony, training strain and ACWR were calculated for each measure, respectively. Data were analysed across ten mesocycles (M: 1–10). Results The main results showed significant differences (p

Con el objetivo de analizar posibles relaciones entre las modalidades de ratio de carga aguda:crónica (tanto por promedios de carga consecutivos, ACWR, como en su ponderación exponencial dinámica, EWMA), en relación con la lesionabilidad en el fútbol femenino, se realizó un estudio cuasiexperimental sin intervención de las ratios obtenidas a partir de las 212 sesiones de entrenamiento y partidos realizados durante una temporada en un equipo de fútbol femenino amateur (N = 17). Las variables utilizadas para el cálculo de las ratios de carga aguda y carga crónica fueron la percepción subjetiva del esfuerzo (RPE) con relación a la carga interna, el tiempo de exposición de cada jugadora durante las sesiones como carga externa (CAR) y la especificidad (ESP) en relación a la programación del entrenamiento. El análisis estadístico mostró diferencias significativas respecto a la variable lesión en las ratios RPE EWMA (4:16, 7:28, 7:21), ESP EWMA (4:16, 7:28, 7:21), CAR EWMA (4:16, 7:28, 7:21) y CAR ACWR (4:16, 7:28) (p

Injuries in professional soccer are a significant concern for teams, and they are caused amongst others by high training load. This cohort study describes the relationship between workload parameters and the occurrence of non-contact injuries, during weeks with high and low workload in professional soccer players throughout the season. Twenty-one professional soccer players aged 28.3 ± 3.9 yrs. who competed in the Iranian Persian Gulf Pro League participated in this 48-week study. The external load was monitored using global positioning system (GPS, GPSPORTS Systems Pty Ltd) and the type of injury was documented daily by the team's medical staff. Odds ratio (OR) and relative risk (RR) were calculated for non-contact injuries for high- and low-load weeks according to acute (AW), chronic (CW), acute to chronic workload ratio (ACWR), and AW variation (Δ-Acute) values. By using Poisson distribution, the interval between previous and new injuries were estimated. Overall, 12 non-contact injuries occurred during high load and 9 during low load weeks. Based on the variables ACWR and Δ-AW, there was a significantly increased risk of sustaining non-contact injuries (p < 0.05) during high-load weeks for ACWR (OR: 4.67), and Δ-AW (OR: 4.07). Finally, the expected time between injuries was significantly shorter in high load weeks for ACWR [1.25 vs. 3.33, rate ratio time (RRT)] and Δ-AW (1.33 vs. 3.45, RRT) respectively, compared to low load weeks. The risk of sustaining injuries was significantly larger during high workload weeks for ACWR, and Δ-AW compared with low workload weeks. The observed high OR in high load weeks indicate that there is a significant relationship between workload and occurrence of non-contact injuries. The predicted time to new injuries is shorter in high load weeks compared to low load weeks. Therefore, the frequency of injuries is higher during high load weeks for ACWR and Δ-AW. ACWR and Δ-AW appear to be good indicators for estimating the injury risk, and the time interval between injuries.

The study aim was 2-fold (i) to describe and compare the in-season variations of acute: chronic workload ratio (ACWR) coupled, ACWR uncoupled, and exponentially weighted moving average (EWMA) through session-rated perceived exertion (s-RPE), total distance (TD), high-speed running distance (HSRD), and sprint distance across different periods of a professional soccer season (early, mid, and end-season) between starters and non-starters; (ii) to analyze the relationship the aforementioned measures across different periods of the season for starters and non-starters. Twenty elite soccer players (mean ± SD age, 29.4 ± 4.4 y; height, 1.8 ± 0.1 m; and body mass, 74.8 ± 2.3 kg). They were divided into starter and non-starter groups and were evaluated for 20 weeks. ACWR had general changes throughout the season. At the beginning and end of the mid-season, the highest ACWR was observed in three parameters: s-RPE, TD, and HSRD. ACWR and EWMA through sprint distance were higher at the beginning of the early-season than at any other time of the season.The ACWR coupled of s-RPE shows a significant higher value for non-starters than starters (p = 0.015; g = −1.01 [−1.98, −0.09]) and the ACWR coupled of TD shows a significant higher value for starters than non-starters in early-season (p

This study was conducted to determine if the acute: chronic workload ratio (ACWR) is related to the incidence of non-contact injuries. The purpose is to compare the external load of injured and non-injured soccer players with the same characteristics, such as position and age. The present analysis considers both the four and the two weeks preceding an injury. Physical characteristics were recorded and analyzed through global positioning systems (GPS) evaluation over one season of 24 competitive microcycles, 144 training sessions, and 32 matches in a total of 35 professional soccer players from the Greek Super League 1 and Super League 2. The loads calculated were total distance (TD), 15–20 km/h, 20–25 km/h, 25–30 km/h, accelerations (ACC) > 2.5 m/s2, and decelerations (DEC) > 2.5 m/s2). Nine injured athletes exceeded the critical threshold of an ACWR > 1.3 several times compared with non-injured athletes that did not reach this level. The present study showed that ACWR is related to a subsequent occurrence of injury but that the threshold of an ACWR can vary. This seems to be mainly influenced by assessing the load of the last two weeks compared with that of the four weeks before the injury.

Background: This study’s aim was twofold: (i) to compare starters and non-starters on a professional soccer team in terms of variations in training intensity indexes across a season, calculated through total distance, sprint distance, accelerations (Acc), and decelerations (Dec) and (ii) to analyse the relationship between the intensity indexes for each playing status. Methods: Nineteen players (age, 29.4 ± 4.4 years; height, 1.8 ± 0.1 m; body mass, 74.8 ± 2.3 kg) were divided into starters and non-starters and followed for 43 weeks using global positioning systems. Results: Training intensity measures (acute:chronic workload ratio [ACWR], coupled and uncoupled) were higher during the latter stage of the season. Total distance peaked during the mid-season, whereas the highest value for exponentially weighted moving average (EWMA) was recorded later in the season. Interestingly, the EMWA of total distance showed little variation during the season for players of both playing statuses. The EWMA of total distance showed a significant higher value for starters than non-starters (p = 0.036; g = 1.27 [0.31, 2.32]). The interruption in games between week 34 and week 35 due to COVID-19 moved some measures into the injury risk zone — namely, the ACWR coupled of sprint distance and Dec; the ACWR uncoupled of total distance, sprint distance, Acc, Dec; and the EWMA of sprint distance, Acc and Dec. Conclusions: The highest training intensity measures were reported late in the season and were similar between starters and non-starters. Across the season, only one difference between starters and non-starters occurred, revealing that training intensity was properly managed throughout the season regardless of the status of the players.

Background: The aims of this study were to describe the variations of training monotony (TM), training strain (TS), and acute:chronic workload ratio (ACWR) through Hooper Index categories (fatigue, stress, DOMS, and sleep quality) and to compare those variations between player status and player positions. Methods: Seventeen male professional soccer players participated in this study. Considering player status, participants were divided in nine starters and eight non-starters. Additionally, participants were divided by playing positions: three wide defenders, four central defenders, three wide midfielders, four central midfielders, and three strikers. They were followed during 40-week in-season period. TM, TS, and ACWR were calculated for each HI category, respectively. Data were grouped in 10 mesocycles for further analysis. Results: Results showed variations across the mesocycles. In general, starters showed higher values for TM, TS, and ACWR calculations than non-starters, although there were some exceptions. Regarding player positions, significant differences were found in stress between wide defenders vs central midfielders for TM (p = 0.033, ES = 5.16), central defenders vs wide defenders for ACWR (p = 0.044, ES = 4.95), and in sleep between wide defenders and strikers for TM (p = 0.015, ES = 5.80). Conclusions: This study revealed that an analysis of players’ well-being parameters according to player status and positions can provide clear information to the coaches and their staff to complement the tasks of training monitoring.

Competitive periods are critical periods where elite rhythmic gymnasts experience higher training loads and insufficient recovery. The aim of this short report is to describe individual training load, recovery and injuries in elite group rhythmic gymnasts during competitive periods. Six gymnasts from the Brazilian senior rhythmic gymnastics group were monitored daily over a 126-day period comprising regular training and four competitions. Training load was measured using the session rating of perceived exertion (session-RPE). Daily load, chronic load, and acute:chronic workload ratio (ACWR) were assessed. The Total Quality Recovery (TQR) scale was used to monitor recovery and a 3-day rolling average (3RA) TQR was also measured. Injuries were diagnosed and reported by the medical staff and their reports were used in the analysis. Descriptive statistics were used. The gymnasts presented distinct daily load, ACWR, and recovery patterns, as well as injuries across the competitive periods. All athletes had rapid increase (“spike”) in load. Three athletes were underrecovered more than 60% of the time. Four athletes sustained five injuries during the time of the study (all lower limb overuse injuries, two severe, two mild and one slight). Individual factors such as age and chronic load could moderate how each gymnast responds to training and tolerates spikes in load. Moreover, injuries sustained during competitive periods appear to affect the short and long-term careers of gymnasts, as well as impair training and competition organization of the team.

ObjectiveTo examine the relationships between the occurrence and severity of injuries using three workload ratios (ACWR, EWMA, REDI) in elite female soccer players and international male and female pentathletes.Materials and MethodsFemale soccer players in the U16 to U18 national French teams (n = 24) and international athletes (n = 12, 4 women and 8 men) in the French modern pentathlon team were monitored throughout an entire season. The Acute Chronic Workload Ratio (ACWR), the Exponentially Weighted Moving Averages (EWMA), and the Robust Exponential Decreasing Index (REDI) were calculated for internal load by the ROE method in soccer and external load in pentathlon. The occurrence and severity of injuries (determined according to time-loss) were quantified in the sweet spot zone [0.8; 1.3] and compared to the other zones of load variation: [0; 0.8], [1.3; 1.5], [1.5; +8], using the three ratios.ResultsOver the study period, a total of sixty-six injuries (2.75 per athlete) were reported in the soccer players and twelve in pentathletes (1 per athlete). The cumulative severity of all injuries was 788 days lost in soccer and 36 in pentathlon: respectively, 11.9 days lost per injury in soccer player and 3.0 per pentathlete. The mean values across the three methods in soccer showed a higher number of injuries detected in the [0; 0.8] workload ratio zone: 22.3 ± 6.4. They were 17.3 ± 3.5 in the sweet spot ([0.8–1.3] zone) and 17.6 ± 5.5 in the [1.5; +8] zone. In comparison to the [1.5; +8] zone, soccer players reported a higher number of days lost to injuries in the presumed sweet spot and in the [0–0.8] zone: 204.7 ± 28.7 and 275.0 ± 120.7 days, respectively. In pentathletes, ten of the twelve injuries (83.3%) occurred in the presumed sweet spot. REDI was the only method capable of tracking workloads over all-time series.ConclusionIn the present cohort of elite soccer players and pentathletes, acute chronic workload calculations showed an association with injury occurrence and severity but did not provide evidence supporting existence of a sweet spot diminishing injury risk.

Background: The main purpose of the current study was to compare the within-season variations of workload, training duration, acute/chronic workload ratio (ACWR), training monotony ™, and training strain (TS) through session rating perceived exertion (s-RPE) between starters and non-starters. Methods: Seventeen under-17 European male soccer players (age, 16.2 ± 0.3 y, height, 1.8 ± 0.1 m; body mass, 66.5 ± 4.0 kg) divided in two groups: nine starters and eight non-starters, were evaluated over 50 weeks throughout the season. Results: In general, there were load variations for all players during the full-season. RPE tended to decrease during in-season and RPE, training duration and s-RPE did not present significant differences between starters and non-starters. TM and TS presented lower values for starters in mesocycle (M) 4 and M11 compared to non-starters. TS presented lower values for starters in M4 and M11 compared to non-starters, while in M10 a higher value was found for starters when compared to non-starters. ACWR showed differences between starters and non-starters in two of the mesocycles. Conclusions: This study showed that some mesocycles provided higher load for non-starters. This information can alert coaches that non-starter players are likely to try too hard in training to demonstrate their abilities, leading to non-functional overreaching, overtraining syndrome, and then poor performance.

Background: The relation between training load, especially internal load, and the recovery-stress state is of central importance for avoiding negative adaptations in high-performance sports like swimming. The aim of this study was to analyze the individual time-delayed linear effect relationship between training load and recovery-stress state with single case time series methods and to monitor the acute recovery-stress state of high-performance swimmers in an economical and multidimensional manner over a macro cycle. The Acute Recovery and Stress Scale (ARSS) was used for daily monitoring of the recovery-stress state. The methods session-RPE (sRPE) and acute:chronic workload-ratio (ACWR) were used to compare different methods for quantifying the internal training load with regard to their interrelationship with the recovery-stress state.Methods: Internal load and recovery-stress state of five highly trained female swimmers [with a training frequency of 13.6 ± 0.8 sessions per week and specializing in sprint (50 and 100 m), middle-distance (200 and 400 m), or long distance (800 and 1,500 m) events] were daily documented over 17 weeks. Two different types of sRPE were applied: RPE∗duration (sRPEh) and RPE∗volume (sRPEkm). Subsequently, we calculated the ratios ACWRh and ACWRkm (sRPE last week: 4-week exponentially weighted moving average). The recovery-stress state was measured by using the ARSS, consisting of eight scales, four of which are related to recovery [Physical Performance Capability (PPC), Mental Performance Capability (MPC), Emotional Balance (EB), Overall Recovery (OR)], and four to stress [Muscular Stress (MS), Lack of Activation (LA), Negative Emotional State (NES), Overall Stress (OS)]. To examine the relation between training load and recovery-stress state a cross correlation (CCC) was conducted with sRPEh, sRPEkm, ACWRh, and ACWRkm as lead and the eight ARSS-scales as lag variables.Results: A large variation of training load can be observed in the individual week-to-week fluctuations whereby the single fluctuations can significantly differ from the overall mean of the group. The range also shows that the CCC individually reaches values above 0.3, especially with sRPEkm as lead variable. Overall, there is a large range with significant differences between the recovery and stress dimensions of the ARSS and between the training load methods, with sRPEkm having the largest span (Range = 1.16). High inter-individual differences between the athletes lie in strength and direction of the correlation | 0.66|≤ CCC ≥|-0.50|. The time delayed effects (lags 0–7) are highly individual, however, clear patterns can be observed.Conclusion: The ARSS, especially the physical and overall-related scales (PPC, OR, MS, OS), is a suitable tool for monitoring the acute recovery-stress state in swimmers. MPC, EB, LA, and NES are less affected by training induced changes. Comparably high CCC and Ranges result from the four internal load methods, whereby sRPE, especially sRPEkm, shows a stronger relation to recovery-stress state than ACWR. Based on these results and the individual differences in terms of time delay in training response, we recommend for swimming to use sRPE to monitor the internal training load and to use the ARSS, with a focus at the physical and overall-scales, to monitor the recovery-stress state.