Training Load Measures Research Articles

Impact of Weekly Training-Load Structure and Content on the Risk of Injury in Professional Rugby Union Match-Play.

Chéradame, J, Loursac, R, Piscione, J, Carling, C, Decq, P, and Jacqmin-Gadda, H. Impact of weekly training-load structure and content on the risk of injury in professional Rugby Union match-play. J Strength Cond Res 38(9): 1613-1619, 2024-The aim of this study was to investigate the impact of different components of daily training load during the week preceding the match on the risk of sustaining a match injury in professional rugby union. A cohort of 72 players from a single professional French club participated. Global positioning system-derived data including total distance (TD) and high-speed distance in addition to ratings of perceived effort (RPE) for both on- and off-pitch (gym-based strength conditioning work) training were collected for each training session over 3 seasons (2017-2020). The association between the daily measures of external and internal training load over the week preceding the day of the match (MD) and the subsequent risk of injury in match-play was estimated using a mixed-effects logistic model adjusted for contextual and individual factors. A total of 184 injuries were sustained in 128 matches (incidence: 81.2 injuries per 1,000 player hours). Higher RPE values for the strength conditioning session on MD-5 ( p < 0.001) and for the on-pitch session on MD-1 ( p = 0.04) were associated with an increased risk of injury in matches. On MD-2, a higher TD covered and that run at high speed (>MAS) were, respectively, associated with a higher ( p = 0.03) and lower risk ( p = 0.02) of injury in matches played. This study in professional rugby union shows that different components of external and internal load had varying influences on injury risk and particularly in relation to the day on which these were performed in the week leading up to the next match. At MD-2, training load favoring intensity rather than volume could reduce the risk of match-play injury.

A Review of the Validity and Reliability of Accelerometer-Based Metrics From Upper Back-Mounted GNSS Player Tracking Systems for Athlete Training Load Monitoring.

Dawson, L, Beato, M, Devereux, G, and McErlain-Naylor, SA. A review of the validity and reliability of accelerometer-based metrics from upper back-mounted GNSS player tracking systems for athlete training load monitoring. J Strength Cond Res 38(8): e459-e474, 2024-Athlete load monitoring using upper back-mounted global navigation satellite system (GNSS) player tracking is common within many team sports. However, accelerometer-based load monitoring may provide information that cannot be achieved with GNSS alone. This review focuses on the accelerometer-based metrics quantifying the accumulation of accelerations as an estimation of athlete training load, appraising the validity and reliability of accelerometer use in upper back-mounted GNSS player tracking systems, the accelerometer-based metrics, and their potential for application within athlete monitoring. Reliability of GNSS-housed accelerometers and accelerometer-based metrics are dependent on the equipment model, signal processing methods, and the activity being monitored. Furthermore, GNSS unit placement on the upper back may be suboptimal for accelerometer-based estimation of mechanical load. Because there are currently no feasible gold standard comparisons for field-based whole-body biomechanical load, the validity of accelerometer-based load metrics has largely been considered in relation to other measures of training load and exercise intensity. In terms of convergent validity, accelerometer-based metrics (e.g., PlayerLoad, Dynamic Stress Load, Body Load) have correlated, albeit with varying magnitudes and certainty, with measures of internal physiological load, exercise intensity, total distance, collisions and impacts, fatigue, and injury risk and incidence. Currently, comparisons of these metrics should not be made between athletes because of mass or technique differences or between manufacturers because of processing variations. Notable areas for further study include the associations between accelerometer-based metrics and other parts of biomechanical load-adaptation pathways of interest, such as internal biomechanical loads or methods of manipulating these metrics through effective training design.

Monitoring Within-Individual Dose-Response Relationships in Professional Soccer Players: The Importance of Fitness Level.

To (1)examine within-individual player dose-response associations between selected training-load measures and changes in aerobic fitness level via submaximal exercise heart rate (HRex%) and (2)measure the relationships between these dose-response associations with basal HRex% (to study the influence of fitness level on dose-response relationship). During an in-season phase, selected training-load measures including total minutes, total distance, mechanical work (the sum number of accelerations and decelerations > 3m2), high metabolic load distance, and Edwards' training impulse were collected via Global Positioning System and heart-rate sensors for analyzing accumulated load. A submaximal warm-up test was used repeatedly before and after 9 phases to elicit HRex% and track fitness changes at an individual level. Negative to positive extensive ranges of within-individual associations were found among players for different metrics (r = -.84 to .89). The relationship between pooled HRex% (basal fitness) and dose-response correlations showed inverse very large (r = -.71) and large (r = -.65) values for accumulated weekly minutes and distance. However, moderate values were found for all other measures (r = -.35 to -.42). Individual players show extensive different ranges of dose-response associations with training measures. The dose-response association is influenced by players' fitness level, and players with lower fitness levels show stronger inverse relationships with accumulated minutes and total distance.

Acute Response to Training after Returning from the Off-Season in Elite Rugby League Athletes.

The purposes of this study were to quantify the physiological response to the initial two-week preseason period in elite male rugby league (RL) athletes, and to determine if a repeated bout effect (RBE) occurs. Eighteen RL players were monitored for the initial two-week preseason period. Blood samples were collected on days (D)1, D2, D4, D5, D8, D9, D11 and D12 to measure creatine kinase (CK). Neuromuscular power was assessed on D1, D5, D8 and D12. During field-based sessions, the external training load was quantified using global positioning system technology, whilst the internal load was quantified using the training impulse and the session rating of perceived exertion. Resistance-based gym session volume was quantified by total repetitions x weight lifted. Perceived measures of fatigue and muscle soreness were assessed on all training days. Two-way (day x week) repeated measures analysis of variance and Bonferroni's corrected post-hoc tests identified significant changes. There were no significant changes in CK activity (649.2 ± 255.0 vs. 673.8 ± 299.1 µL; p = 0.63) or internal training load measures from week 1 to week 2. External training load measures including total distance (4138.1 ± 198.4 vs. 4525.0 ± 169.2 m; p < 0.001) and repeated high-intensity efforts (12.6 ± 1.8 vs. 17.5 ± 1.8 au; p < 0.001) significantly increased in week 2 compared to week 1. Internal training loads and CK activity did not change in response to an increase in external training loads during the initial preseason. The current results provide support for a 'real world' perspective of the RBE phenomenon that may be more applicable for team sport practitioners.

Load and recovery monitoring in Swiss top-level youth soccer players: Exploring the associations of a new web application-based score with recognised load measures

Load and recovery monitoring in Swiss top-level youth soccer players: Exploring the associations of a new web application-based score with recognised load measures

Workloads of Emergency Call Types in Active-Duty Firefighters

Firefighting is an occupation with high injury risks, particularly when conducting fireground operations. The fire service generally quantifies the job demands of firefighting through tracking emergency call volume across 24 h shifts; however, volume alone does not account for the specific work completed in response to different call types. Utilization of external (i.e., objective work) and internal (i.e., intrinsic responses to work) training load measures have the potential to quantify the multifaceted workload demands of responses to medical and fire emergencies and inform injury prevention strategies. Therefore, the purpose of this study was to utilize training load measures to quantify the workloads across emergency call types. For medical emergencies and fire emergencies, the external load and the physiological, perceived, and cumulative internal loads were quantified. The results indicate that the magnitude of objective work required for fire emergency responses that include fire suppression and/or auto-extrication is approximately three times greater than that of medical and other fire emergency (i.e., no suppression or extrication) responses. Further, in response to the objective work for fire suppression and/or auto-extrication calls, the intrinsic workloads are six times more physiologically and perceptually demanding than—as well as double, cumulatively—those of medical and other fire emergency responses.

Within-Subject Principal Component Analysis of External Training Load and Intensity Measures in Youth Soccer Training.

Marynowicz, J, Lango, M, Horna, D, Kikut, K, Konefał, M, Chmura, P, and Andrzejewski, M. Within-participant principal component analysis of external training load and intensity measures in youth soccer training. J Strength Cond Res 37(12): 2411-2416, 2023-The aim of this study was to identify which combination of external training load (EL) and external intensity (EI) metrics during youth soccer training sessions captured similar or unique information. Data were collected from 18 youth soccer players during an 18-week in-season competition period using a 10-Hz global positioning system, rating of perceived exertion (RPE), and session-RPE (sRPE). External training load measures included total distance (TD, in meters), PlayerLoad (PL, in arbitrary units), high-speed running distance (HSR, in meters), and number of accelerations (ACC, n). All EL metrics were also divided by session duration (minutes) to obtain EI values. A total of 804 training observations were undertaken (43 ± 17 sessions per player). The analysis was performed by use of the principal component analysis technique. The first principal component (PC) captured 49-70% and 68-89% of the total variance in EI and EL, respectively. The findings show that from the 5 EI metrics, most of the information can be explained by either TD per minute or PL per minute, with a loading from 0.87 to 0.98 and from 0.76 to 0.95, respectively. The majority of EL information can be explained by PL (loading: 0.93-0.98), TD (loading: 0.95-0.99), ACC (loading: 0.71-0.91), or sRPE (loading: 0.70-0.93). The second PC for EL metrics is most strongly correlated with HSR, with loadings from 0.53 to 0.84. The results suggest that the majority of the information contained in the EL variables can be captured in 1 PC without losing much information. The findings suggest that stakeholders who intend to provide a fast and holistic view of EL information in a daily training environment should report TD, PL, ACC, or sRPE plus HSR to coaching staff as a metrics that provides additional unique information.

Training Load and Current Soreness Predict Future Delayed Onset Muscle Soreness in Collegiate Female Soccer Athletes.

Delayed onset muscles soreness (DOMS) is an indication of muscle stress and trauma that develops from excessive musculoskeletal loads. Musculoskeletal loads can be measured with wearable devices, but there is limited research on specific training load metrics that most correlate with DOMS after activity. To determine the predictive capabilities of training load variables on the development of lower extremity DOMS in female collegiate soccer athletes throughout an entire season. Prospective Cohort. Twenty-seven collegiate female soccer athletes reported their lower extremity DOMS each day prior to all soccer activity. Participants wore Polar heart rate and global positioning monitors to capture training load measures. Pearson correlation coefficients were used to assess the relationships between the training load variables and change in DOMS when collapsed across dates. Separate linear mixed models were performed with the following day's DOMS as the outcome variable, training load and the current day's DOMS as predictor variables, and participants serving as random intercepts. All training load variables significantly predicted change in DOMS, with number of decelerations (ρ=0.72, p <0.001), minutes spent at greater than 80% of maximum heart rate (HRmax) (ρ=0.71 , p <0.001), and distance (ρ=0.70 , p <0.001) best correlating with change in DOMS. Linear mixed models revealed a significant interaction of all training load and current day's DOMS on the following day's DOMS (p<0.001), but number of decelerations, HRmax, and total number of accelerations demonstrated the highest coefficient of determination (R2 marginal=33.2% - 29.2% , R2 conditional= 46.9% - 44.8%). Training load variables paired with the current day's DOMS significantly predict lower extremity DOMS in the future, with number of decelerations, accelerations, and HRmax best predicting future DOMS. Although this demonstrates that training load variables predict lower extremity DOMS, future research should incorporate objective measures of strength or jump kinetics to identify if similar relationships exist. Level 3.

Respiratory muscle training induces additional stress and training load in well-trained triathletes-randomized controlled trial.

Background: Respiratory muscle training (RMT) has been investigated in the context of improved athletic performance and pulmonary function. However, psychophysiological costs of RMT remain understudied. Voluntary isocapnic hyperpnoea (VIH) and inspiratory pressure threshold loading (IPTL) are widely applied RMT methods. The main purposes of this study were to assess whether RMT induces additional load on well-trained triathletes and determine differences in RMT-induced load between sexes and applied methods. Materials and Methods: 16 well-trained triathletes (n = 16, 56% males) underwent 6weeks of VIH or IPTL program with progressive overload. Blood markers, subjective measures, cardiac indices, near-infrared spectroscopy indices, inspiratory muscle fatigue, and RMT-induced training load were monitored pre-, in and post-sessions. We used multiple ANOVA to investigate effects of sex, training method, and time on measured parameters. Results: There were significant interactions for acid-base balance (p = 0.04 for sex, p < 0.001 for method), partial carbon dioxide pressure (p = 0.03 for sex, p < 0.001 for method), bicarbonate (p = 0.01 for method), lactate (p < 0.001 for method), RMT-induced training load (p = 0.001 for method for single session, p = 0.03 for method per week), average heart rate (p = 0.03 for sex), maximum heart rate (p = 0.02 for sex), intercostales muscle oxygenation (p = 0.007 for testing week), and intercostales muscle oxygenation recovery (p = 0.003 for testing week and p = 0.007 for method). Conclusion: We found that RMT induced additional load in well-trained triathletes. Elicited changes in monitored variables depend on sex and training method. VIH significantly increased subjective training load measures. IPTL was associated with disbalance in blood gasometry, increase in lactate, and reports of headaches and dizziness. Both methods should be applied with consideration in high-performance settings.

Training Load Quantification in Women's Elite Football: A Season-Long Prospective Cohort Study.

The aim of this study was to investigate (1)if there are differences in training load and intensity between the different training days within a microcycle and (2)if training load and intensity within the different training days are stable over the course of a season. Data were collected over a full season from a team in the women's premier division in Norway. External load (total distance, high-speed-running distance, sprint distance, and the combined number of accelerations and decelerations [ACCDEC]) was assessed using a 10-Hz GPS system with a built-in accelerometer. Internal load was assessed through session rating of perceived exertion, which was multiplied with session duration (session rating of perceived exertion-load). Training days were classified in relation to their proximity to the upcoming match day (MD): MD - 4, MD - 3, MD - 2, and MD - 1. Contents on these days were standardized according to a weekly periodization model followed by the coaching staff. Differences between training days were analyzed using a linear mixed-effects model. All training days were significantly different from each other across multiple variables. ACCDEC values were highest on MD - 4 (147.5 [13.0] ACCDEC count), and all distance variables were highest on MD - 3. All measures of training load were significantly reduced from MD - 3 to MD - 2 (effect size [ES] = 1.0-4.1) and from MD - 2 to MD - 1 (ES = 1.6-4.3). A significant negative effect across the season was observed for session rating of perceived exertion-load and ACCDEC (ES = 0.8-2.1). These results provide evidence that elite female football teams can be successful in differentiating training load between training days when implementing a weekly periodization approach.

A semi-automatic tool to quantify training load in endurance athletes

Abstract Funding Acknowledgements Type of funding sources: None. Background Despite the widespread use of wearables in endurance sports allowing the measurements needed for quantification of the training load (TL), studies in sports cardiology consistently use less reliable questionnaires to assess TL.[1] This scant use of activity trackers to determine TL can be explained by the large workload for data analysis. Purpose We aimed to develop a semi-automated post-processing tool that allows quantifying TL, based on heart rate (HR) monitoring by commercial wearables, for future use in clinical and epidemiological studies. We compared the calculated maximal HR automatically derived from HR monitoring during endurance training with the maximal HR obtained during incremental exercise testing in the lab. We describe TL calculated by our tool in young and older endurances athletes and compare it with the TL obtained via questionnaires. Methods Training data was collected in two multicenter studies. Master@Heart is a cohort study of endurance trained middle-aged men between 45 and 70 years.[2] Pro@Heart is a prospective study in young endurance athletes between 16 and 23 years.[3] For the purpose of this substudy, 44 athletes (38 ± 17 years) that had recorded all their training sessions using a chest-worn HR monitor for one year were included. Using an in-house developed pipeline in R (R core Team, Vienna, Austria), maximal HR and TL were calculated from training data. The maximal HR measured in the field (Tangent MaxHR) was then compared with the lab-measured maximal HR (Lab MaxHR). Both Lucia training impulse (LuTRIMP) and Edwards TRIMP (eTRIMP) were compared as measures of TL based on HR-based intensity zones. LuTRIMP, based on individually based exercise intensity zones, and eTRIMP based on the Tangent MaxHR. Participants filled in a standard exercise questionnaire to determine the amount of training sessions and training hours per week. Results Lab MaxHR was lower than Tangent MaxHR (183 ± 12.2bpm vs. 188.3 ± 13.0bpm; Figure 1 A), but correlated strongly (r=0.81, P&amp;lt;0.01; Figure 1 B) with low mean bias (-5.3bpm, LOA±15.4; Figure 1 C). LuTRIMP and eTRIMP correlated very strong (r=0.93, P&amp;lt;0.01). Pro@Heart athletes performed a higher TL (1730 ± 644 vs. 1190 ± 314 AU/week, P&amp;lt;0.01; Figure 2 A), duration (12.2 ± 4.6 hours per week vs. 7.9 ± 2.4, P&amp;lt;0.01; Figure 2 B) and trained more frequent (5.9 ± 1.7 vs. 4.0 ± 1.0 sessions per week, P&amp;lt;0.01; Figure 2 C) than Master@Heart athletes. Neither the reported training sessions nor the training hours in the questionnaires correlated with the measured training sessions (r=0.20) and training hours respectively (r=0.12). Conclusion Our tool allows to semi-automatically quantify different TL parameters in endurance athletes from a wide age range. The use of questionnaires to determine TL is inaccurate. TL calculated using eTRIMP is comparable to TL calculated using LuTRIMP. Since eTRIMP does not require an exercise test, it is more easily implementable in large studies.

Understanding Training Load as Exposure and Dose.

Various terms used in sport and exercise science, and medicine, are derived from other fields such as epidemiology, pharmacology and causal inference. Conceptual and nomological frameworks have described training load as a multidimensional construct manifested by two causally related subdimensions: external and internal training load. In this article, we explain how the concepts of training load and its subdimensions can be aligned to classifications used in occupational medicine and epidemiology, where exposure can also be differentiated into external and internal dose. The meanings of terms used in epidemiology such as exposure, external dose, internal dose and dose-response are therefore explored from a causal perspective and their underlying concepts are contextualised to the physical training process. We also explain how these concepts can assist in the validation process of training load measures. Specifically, to optimise training (i.e. within a causal context), a measure of exposure should be reflective of the mediating mechanisms of the primary outcome. Additionally, understanding the difference between intermediate and surrogate outcomes allows for the correct investigation of the effects of exposure measures and their interpretation in research and applied settings. Finally, whilst the dose-response relationship can provide evidence of the validity of a measure, conceptual and computational differentiation between causal (explanatory) and non-causal (descriptive and predictive) dose-response relationships is needed. Regardless of how sophisticated or "advanced" a training load measure (and metric) appears, in a causal context, if it cannot be connected to a plausible mediator of a relevant response (outcome), it is likely of little use in practice to support and optimise the training process.

Relationships between training load and wellbeing measures across a full season: a study of Turkish national youth wrestlers.

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.

Sleep duration is associated with overnight changes in perceived fatigue in elite women soccer players

ABSTRACT The current study aimed to describe sleep habits and analyze the associations between sleep indices, changes in perceived fatigue (Δ Fatigue) and external training load measures in women soccer players during a 7-day training camp. Sixteen elite women soccer players (age: 25.4 ± 3.6 years; mean ± SD) from the Portuguese Women’s National Team participated in the study. Sleep indices (sleep duration and efficiency) were measured using a wrist-worn accelerometer. External training loads measures were measured using GPS devices. Players also reported perceived fatigue using a Likert scale (1 - very, very low to 7 – very, very high) before and immediately after sleep. Players’ within-subject coefficient of variation for sleep duration was 5.6%, and 4.6% for sleep efficiency. Individually, 8 players (50%) slept less than 7 h per night throughout the training camp, and the same number of athletes had a sleep efficiency lower than 85%. Similar values (p<0.05) were measured for sleep duration and efficiency between training and match days. A moderate negative within-subjects correlation was found between Δ Fatigue and sleep duration (adjusted for pre-sleep fatigue) [r = −0.32; 95% Confidence Interval (−0.51 – −0.08); p = 0.04]. These findings reinforce the importance of sleep in the recovery process of elite women soccer players, showing that more sleep may help to attenuate fatigue.

Does maturity estimation, 2D:4D and training load measures explain physical fitness changes of youth football players?

ObjectivesThe purpose of the present study was two-fold: (1) To analyse physical fitness changes of youth football players after a full-season; and (2) to examine whether physical fitness changes are explainable by estimated maturity status, 2digit:4digit ratio (2D:4D) from each hand and training load (TL) measures.MethodsTwenty-seven youth elite Under-15 football players were daily monitored for training load measures during 38 weeks. At the beginning and at the end of the season, all players were assessed for physical fitness. Also, the maturity status estimation and the length of the second and fourth digits of both hands were collected at the beginning of the season.ResultsSignificant differences were found for all physical fitness measures after the season. The second and fourth digits of left and right hands had negative moderate correlations with change of direction (COD) changes (r=-.39 to − 0.45 | p = .05 to 0.02). Also, the maturity offset measure had negative moderate correlations with COD changes (r=-.40 | p = .04). From the reported significant correlations, the maturity offset, Left 4D, Right 2D and Right 4D significantly predicted the Mod.505 COD test changes (β = 0.41, p = .04; β = -0.41, p = .04; β = -0.45, p = .02; and β = -0.44, p = .03, respectively).ConclusionThe maturity offset and the 2D:4D measures have the potential to predict COD performance changes over-time in youth football players. Given the lack of associations between the maturity estimation, 2D:4D and training load measures, with the overall physical fitness measures, coaches should rely only at COD changes.

The Dose-Response Relationship Between Training-Load Measures and Changes in Force-Time Components During a Countermovement Jump in Male Academy Soccer Players.

To manage physical performance in soccer, practitioners monitor the training load (TL) and the resulting fatigue. A method frequently used to assess performance is the countermovement jump (CMJ). However, the efficacy of CMJ to detect fatigue from soccer matches and training remains uncertain, as does the relationship between TL and change in CMJ performance. The aims of the present study were 2-fold. One was to observe the changes of CMJ force-time components and jump height (JH). The second was to examine dose-response relationships between TL measures and CMJ over a 6-week preseason. Twelve male academy soccer players (17 [1]y, 71.2 [5.6]kg, and 178 [5.8]cm) were recruited. Daily changes in CMJ were assessed against baseline scores established before preseason training, along with internal and external TL measures. A series of Bayesian random intercept models were fitted to determine probability of change above/below zero and greater than the coefficient of variation established at baseline. Jumps were categorized into match day minus (MD-) categories where the higher number indicated more time from a competitive match. JH was lowest on MD - 3 (28cm) and highest on MD - 4 (34.6cm), with the probability of change from baseline coefficient of variation highly uncertain (41% and 61%, respectively). Changes to force-time components were more likely on MD - 3 (21%-99%), which provided less uncertainty than JH. Bayes R2 ranged from .22 to .57 between TL measures and all CMJ parameters. Force-time components were more likely to change than JH. Practitioners should also be cautious when manipulating TL measures to influence CMJ performance.

Training load measures and biomarker responses using a multilevel approach during a training week: a study comparing young and master cyclists

article: Training load measures and biomarker responses using a multilevel approach during a training week: a study comparing young and master cyclists - Medicina dello Sport 2022 September;75(3):342-59 - Minerva Medica - Journals

Analysis of the Association between Internal and External Training Load Indicators in Elite Soccer; Multiple Regression Study.

The aim of this study was to identify the external training load (ETL) variables that are most influential on the session rating of perceived exertion (sRPE) during elite soccer training. The participants (n = 29) were adult male soccer players from a single team that competed in Croatia’s highest national soccer competition in the 2021/2022 season. Data were collected using the 10 Hz Global Positioning System from 66 training sessions, and a total of 1061 training observations were undertaken. The univariate and multivariate relationships among the predictors (ETL variables) and the criterion (sRPE) were assessed using forward stepwise multiple regressions and Pearson’s correlations, respectively. ETL variables explained 63% of the variance in the sRPE (Multiple R = 0.79; p < 0.01), and the model was successfully cross-validated. The significant partial regressors were total distance (β = 0.66), metres per minute (β = −0.47), high-intensity accelerations (β = 0.22) and decelerations (β = 0.18), and sprint distance (β = 0.14). All ETL variables were significantly correlated with the sRPE (all p < 0.01), with the highest correlations found for total distance covered (r = 0.70) and high-intensity accelerations and decelerations (r = 0.62 and 0.65, respectively). Such results show that (i) the total distance and acceleration rates during the training sessions are the most important predictors of the sRPE, and (ii) a combination of different ETL variables predicts the sRPE better than any individual parameter alone. This study shows that both the volume and intensity of training are related to players’ internal responses. The findings ultimately provide further evidence to support the use of sRPE as a global measure of training load in soccer players.

Does transforming subjective measures of load better represent training and match-play intensity in youth soccer players?

The purpose of this study was to investigate the structure of relationships between measures of training load and assess whether these can be modified through non-linear transformations. Ratings of perceived exertion (RPE) and seven external load measures (total distance covered, PlayerLoad, low-intensity running distance, high-speed running distance, sprinting distance, accelerations, and decelerations) were collected from 20 academy soccer players (age = 17.4 ± 1.3 years, stature = 178.0 ± 8.1 cm, body-mass = 71.8 ± 7.2 kg), with 3220 recordings taken across a 47-week season. To control for the effects of session duration, sessions were categorised as short (≤60 min) or long (&gt;60 min). All RPE and sessional RPE-training load (sRPE-TL; RPE multiplied by session duration) were analysed in their raw form and through raising to a series of exponentials. The underlying structure of the data was investigated using principal component analysis. Two components were retained for each analysis and varimax rotation was performed. The first rotated component (RC) was best represented as a measure of volume (RCvolume) with high loadings for RPE and sRPE-TL, whilst the second RC was best represented as a measure of intensity (RCintensity). Non-linear transformations had little effect on loading of modified measures for long sessions for sRPE-TL (RCvolume: 0.87–0.8; RCintensity: 0.27–0.13), and for RPE (RCvolume: 0.76–0.79; RCintensity: 0.17–0.10). For short sessions, the loading became more equal between intensity and volume for sRPE-TL (RCvolume: 0.88–0.41; RCintensity: 0.32–0.36) and more aligned to intensity (RCintensity: 0.52–0.61) compared with volume (RCvolume: 0.44–0.23) for RPE. The present study demonstrates that RPE and sRPE-TL predominantly reflect measures of training volume, however, they can be modified to better reflect intensity for training sessions &lt;60 min in duration.

Training Load Management in Professional Tennis Players During COVID-19 Lockdown: A Case Series Study

Background During the coronavirus disease 2019 (COVID-19) pandemic, training routines of most athletes around the world were abruptly interrupted, potentially increasing the risk of injury. The purpose of this study was to compare 3 measures of training load (TL): tennis-specific TL, physical TL, and total TL management before, during, and after lockdown of 3 professional male tennis players. Case Presentation Three professional male tennis players were monitored throughout the 2020 season. Outcome and Follow-Up The median total weekly TL (CR-10 Borg rating of perceived exertion—session length in minutes) was 5783 arbitrary units (AU). The total weekly TLs before, during, and after lockdown were 7195, 3753, and 5950, respectively. During lockdown, tennis TL was reduced to 0, while physical TL (including preventive loads) increased by 73%. All players suffered an injury/illness during tennis training resumption following lockdown, where 2 of them were musculoskeletal related and the others were due to COVID-19. There was no association between total acute:chronic workload ratio (ACWR) and injury. However, one case had a spike (&gt;1.5) in tennisspecific ACWR 2 weeks before injury, despite maintaining total ACWR between 0.8 and 1.5. Discussion Tennis and physical differential TL monitoring should be carried out separately in order to ensure tennis-specific player readiness. If only total load is monitored during lockdown or rehabilitation from injury, subsequent increases in tennis load upon return to play could potentially increase the risk of injury. The 3 participants showed a similar pattern of total TL throughout the season with pre-lockdown loads being the highest. JOSPT Cases 2022;2(3):141–148. Epub: 21 June 2022. doi:10.2519/josptcases.2022.10863