Establishing the criterion validity and reliability of common methods for quantifying training load

Acute performance fatigability following continuous versus intermittent cycling protocols is not proportional to total work done

Classical training theory postulates that performance fatigability following a training session should be proportional to the total work done (TWD); however, this notion has been questioned. This study investigated indices of performance and perceived fatigability after primary sessions of high-intensity interval training (HIIT) and constant work rate (CWR) cycling, each followed by a cycling time-to-task failure (TTF) bout. On separate days, 16 participants completed an incremental cycling test, and, in a randomized order, (i) a TTF trial at 80% of peak power output (PPO), (ii) an HIIT session, and (iii) a CWR session, both of which were immediately followed by a TTF trial at 80% PPO. Central and peripheral aspects of performance fatigability were measured using interpolated twitch technique, and perceptual measures were assessed prior to and following the HIIT and CWR trials, and again following the TTF trial. Despite TWD being less following HIIT (P = 0.029), subsequent TTF trial was an average of 125 s shorter following HIIT versus CWR (P < 0.001), and this was accompanied by greater impairments in voluntary and electrically evoked forces (P < 0.001), as well as exacerbated perceptual measures (P < 0.001); however, there were no differences in any fatigue measure following the TTF trial (P ≥ 0.149). There were strong correlations between the decline in TTF and indices of peripheral (r = 0.70) and perceived fatigability (r ≥ 0.80) measured at the end of HIIT and CWR. These results underscore the dissociation between TWD and performance fatigability and highlight the importance of peripheral components of fatigability in limiting endurance performance during high-intensity cycling exercise.

Relationship between methods of monitoring training load and physiological indicators changes during 4 weeks cross-country skiing altitude training

This study aimed to: (i) analyze the load characteristics of 4 weeks cross-country skiing altitude training; (ii) analyze the relationships between methods of monitoring training load and physiological indicators changes of elite male Chinese cross-country skiers during this period. Practitioners collected load data during 4 weeks of altitude training camp. Participants performed maximal oxygen uptake, lactate threshold, body composition, and skierg power test before and after the training camp to investigate the changes in physiological performance. Edwards TRIMP, Lucia TRIMP, and session rating of perceived exertion were collected as internal load. Training distance, time recorded by the Catapult module were collected as external load. The result revealed a " pyramid " pattern in the load characteristics during the altitude training camp. The correlation between luTRIMP and percent change in physiological indicators was highest. Percentage changes in lactate threshold velocity (r = .78 [95% CI -.01 to .98]), percentage changes in lactate threshold HR (r = .71 [95% CI .14- .99]), percentage changes in maximum HR (r = .83 [95% CI .19-1.00]), percentage changes in skierg power-to-weight ratio (r = .75 [95% CI -.28 to .98]) had very large relationships with luTRIMP. In cross-country skiing altitude training, training loads should be reasonably controlled to ensure that athletes do not become overly fatigued. Methods of training load monitoring that combine with athletes' physiological characteristics and program characteristics have the highest dose-response relationships, it is an important aspect of cross-country ski training load monitoring. The luTRIMP could be a good monitoring tool in cross-country skiing altitude training.

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

Background

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.

Purpose

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.

Study Design

Prospective Cohort.

Methods

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.

Results

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%).

Conclusions

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 of Evidence

Level 3.

Validity and Reliability of Facial Rating of Perceived Exertion Scales for Training Load Monitoring

ABSTRACT

van der Zwaard, S, Hooft Graafland, F, van Middelkoop, C, and Lintmeijer, LL. Validity and reliability of facial rating of perceived exertion scales for training load monitoring. J Strength Cond Res XX(X): 000-000, 2022-Rating of perceived exertion (RPE) is often used by coaches and athletes to indicate exercise intensity, which facilitates training load monitoring and prescription. Although RPE is typically measured using the Borg's category-ratio 10-point scale (CR10), digital sports platforms have recently started to incorporate facial RPE scales, which potentially have a better user experience. The aim of this study was to evaluate the validity and reliability of a 5-point facial RPE scale (FCR5) and a 10-point facial RPE scale (FCR10), using the CR10 as a golden standard and to assess their use for training load monitoring. Forty-nine subjects were grouped into 17 untrained (UT), 19 recreationally trained (RT), and 13 trained (T) individuals Subjects completed 9 randomly ordered home-based workout sessions (3 intensities × 3 RPE scales) on the Fitchannel.com platform. Heart rate was monitored throughout the workouts. Subjects performed 3 additional workouts to assess reliability. Validity and reliability of both facial RPE scales were low in UT subjects (intraclass correlation [ICC] ≤ 0.44, p ≤ 0.06 and ICC ≤ 0.43, p ≥ 0.09). In RT and T subjects, validity was moderate for FCR5 (ICC ≥ 0.72, p < 0.001) and good for FCR10 (ICC ≥ 0.80, p < 0.001). Reliability for these groups was rather poor for FCR5 (ICC = 0.51, p = 0.006) and moderate for FCR10 (ICC = 0.74, p < 0.001), but it was excellent for CR10 (ICC = 0.92, p < 0.001). In RT and T subjects, session RPE scores were also strongly related to Edward's training impulse scores ( r ≥ 0.70, p < 0.001). User experience was best supported by the FCR10 scale. In conclusion, researchers, coaches, strength and conditioning professionals, and digital sports platforms are encouraged to incorporate the valid and reliable FCR10 and not FCR5 to assess perceived exertion and internal training load of recreationally trained and trained individuals.

Comparing Two Methods of Acute: Chronic Workload Calculations in Girls’ Youth Volleyball

Monitoring training load using acute:chronic workload ratio (ACWR) enables coaches to maximize fitness potential while mitigating injury risks by maintaining an optimal ACWR range. There are two methods of determining ACWR: rolling average (RA) and exponentially weighted moving average (EWMA). This study aimed to (1) compare weekly changes in kinetic energy (KE) output in female youth athletes (n = 24) during the high school (HSVB) and club volleyball (CVB) seasons and (2) evaluate the agreement in RA and EWMA ACWR calculations during the HSVB and CVB seasons. Weekly load was measured using a wearable device, and RA and EWMA ACWRs were calculated using KE. The HSVB data showed spikes in ACWR at the onset of the season and during one week mid-season (p = 0.001–0.015), but most weeks were in the optimal ACWR range. The CVB data had greater weekly variations throughout the season (p < 0.05), and many weeks were outside of the optimal ACWR range. There were moderate correlations between the two ACWR methods (HSVB: r = 0.756, p < 0.001; CVB: r = 0.646, p < 0.001). Both methods can be used as a monitoring tool for consistent training like that in HSVB, but more research is needed to investigate appropriate methods for an inconsistent season like that of CVB.

Comparison among U-17, U-20, and Professional Female Soccer in the GPS Profiles during Brazilian Championships

The purpose of this study was to compare and characterize the physical demand of official matches among under-17 (U-17), under-20 (U-20), and professional (Pro) female soccer players. All matches were from the U-17, U-20, and Pro National Brazilian Championships. Fourteen Pro matches, nine U-20 matches, and four U-17 matches were analyzed. The external load was measured by the global positioning system (GPS) and the internal workload was assessed by the ratings of perceived exertion (RPE) multiplied by the duration of the match. The activity profiles measured were total distance covered (km), total sprint distance (m) (speed > 18 km·h^-1), number of accelerations and decelerations (between 1 and 2 m·s^-2 and >3 m·s^-2), and top speed (km·h^-1). For the analysis, we standardized all the metrics (except the top speed) by the time (in minutes) played. The Pro group presented higher sprint distances, number of accelerations and decelerations, and top speeds, compared to U-20 and U-17. There was no difference in the total distance among groups, and there was no difference in any GPS metrics between U-20 and U-17. The RPE was higher in Pro and U-17, compared to U-20; however, the workload-RPE was higher in Pro, compared to both U-17 and U-20 groups. These findings provide important information for the evolution of physical performance according to age categories in elite female soccer players.

Validation of Internal and External Load Metrics in NCAA D1 Women's Beach Volleyball

ABSTRACT

Tometz, MJ, Jevas, SA, Esposito, PM, and Annaccone, AR. Validation of internal and external load metrics in NCAA D1 women's beach volleyball. J Strength Cond Res 36(8): 2223-2229, 2022-The purpose of this study was to determine the validity of internal and external load metrics in NCAA D1 women's beach volleyball. Subjects included 13 NCAA D1 women's beach volleyball players (age: 20.3 ± 1.4 years). A total of 578 data points were analyzed from 51 team training sessions, including practice, games, and sport-specific conditioning during the pre-season semester (15 weeks). Data points included Edward's training impulse (TRIMP) (228.0 ± 80.7 arbitrary units [AU]), session rating of perceived exertion (sRPE) Load (532.5 ± 232.8 [AU]), distance covered (DC) in meters (2,635.4 ± 884.3 [m]), and daily environmental condition variables {(temperature (76.5 ± 13.7 [°F]), relative humidity (72.5 ± 13.2 [%]), and wet-bulb globe temperature (52.9 ± 19.9 [°F])}. The subjects wore Polar Team Pro heart rate monitors with global positioning system during each session. Subjects completed an sRPE questionnaire after every session. Pearson product moment correlations yielded statistically significant relationships (p < 0.01) between TRIMP and sRPE Load (r = 0.81), TRIMP and DC (r = 0.78), and sRPE Load and DC (r = 0.82). A forward selection multiple regression yielded that sRPE Load could predict TRIMP with the equation: TRIMPTometz = 78.735 + (sRPE Load * 0.28) (p < 0.001). These findings support sRPE Load as a valid alternative to TRIMP when monitoring internal loads in NCAA D1 women's beach volleyball. Session rating of perceived exertion Load may be more practical and accessible for teams. Distance covered should be considered when periodizing and monitoring training loads because of its relationship with internal loads.

Urinary extracellular vesicle as a potential biomarker of exercise-induced fatigue in young adult males

Purpose

Previous studies have suggested that circulating extracellular vesicles (EVs) arise after high intensity exercise and urine could reflect the plasma proteome. Herein, we investigated the characteristic of urinary EVs from healthy young adult males who had completed a maximal effort exercise test.

Methods

Thirteen healthy men completed a 20 m shuttle run test (20 m SRT). Fresh urine samples were collected at first morning, right after, and 1 h rest after 20 m SRT. Also, blood lactate, heart rate, rating of perceived exertion, and blood pressure were measured before, right after, and 1 h rest after 20 m SRT. Urinary EVs were analyzed using Exoview instrument and microRNAs (miRNAs) sequencing on urinary EVs were performed.

Results

Urinary EVs increased significantly after exercise and returned to baseline value after 1 h of rest. miRNA sequencing on urinary EV revealed alterations in four miRNAs (1 up and 3 down) and nine miRNAs (2 up and 7 down) in pre- vs. post- and post- vs. post-1 h samples, respectively. Lastly, bioinformatic analysis of urinary EV miRNA suggests that predicted target genes could affect PI3K-Akt, mitogen-activated protein kinase, and insulin pathways by exercise.

Conclusions

Exercise to voluntary exhaustion increased the number of EVs in urine. Also, miRNAs in urinary EVs were altered after exercise. These findings could indicate the possibility of using the urinary EVs as a novel biomarker of acute exercise-induced fatigue.

Validity of the Training-Load Concept

Training load (TL) is a widely used concept in training prescription and monitoring and is also recognized as as an important tool for avoiding athlete injury, illness, and overtraining. With the widespread adoption of wearable devices, TL metrics are used increasingly by researchers and practitioners worldwide. Conceptually, TL was proposed as a means to quantify a dose of training and used to predict its resulting training effect. However, TL has never been validated as a measure of training dose, and there is a risk that fundamental problems related to its calculation are preventing advances in training prescription and monitoring. Specifically, we highlight recent studies from our research groups where we compare the acute performance decrement measured following a session with its TL metrics. These studies suggest that most TL metrics are not consistent with their notional training dose and that the exercise duration confounds their calculation. These studies also show that total work done is not an appropriate way to compare training interventions that differ in duration and intensity. We encourage scientists and practitioners to critically evaluate the validity of current TL metrics and suggest that new TL metrics need to be developed.

A Study on the Relationship between RPE and sEMG in Dynamic Contraction Based on the GPR Method

The rating of perceived exertion (RPE) and surface electromyography (sEMG) describe exercise intensity subjectively and objectively, while there has been a lack of research on the relationship between them during dynamic contractions to predict exercise intensity, comprehensively. The purpose of this study was to establish a model of the relationship between sEMG and RPE during dynamic exercises. Therefore, 20 healthy male subjects were organized to perform an incremental load test on a cycle ergometer, and the subjects’ RPEs (Borg Scale 6–20) were collected every minute. Additionally, the sEMGs of the subjects’ eight lower limb muscles were collected. The sEMG features based on time domain, frequency domain and time–frequency domain methods were extracted, and the relationship model was established using Gaussian process regression (GPR). The results show that the sEMG and RPE of the selected lower limb muscles are significantly correlated (p < 0.05) but that they have different monotonic correlation degrees. The model that was established with all three domain features displayed optimal performance and when the RPE was 13, the prediction error was the smallest. The study is significant for lower limb muscle training strategy and quantification of training intensity from both subjective and objective aspects, and lays a foundation for sEMG further applications in rehabilitation medicine and sports training.

The dose-response relationship between training-load measures and aerobic fitness in elite academy soccer players

The aim of the current study is to examine the dose-response relationships between training load (TL) measures and the consequent changes in aerobic fitness. Data were collected over the 6-week pre-season period in elite youth soccer players. Participants completed a lactate threshold test to identify changes in treadmill speed at 2 mmol · l^-1 (S2) and 4 mmol · l^-1 (S4). Internal TL was quantified with the following training impulse (TRIMP) methods: Banister TRIMP, Edwards TRIMP, Lucia TRIMP, individual TRIMP (iTRIMP) and rate of perceived exertion was also collected. External TL measures were total distance, PlayerLoad, high speed running (14.4-19.8 km · h^-1), very high-speed running (19.8-25.2 km · h^-1) and maximal sprint distance (>25.2 km · h^-1). Individual high-speed distance was derived from each participants treadmill speed at S4. Different Bayesian regression models were run with different likelihood functions. The best-fitting models with both the lowest out-of-sample prediction error and the highest variance explained (R²) were used. iTRIMP had the strongest relationships with changes in S2 (r = 0.93, R² = 0.90) and S4 (r = 0.88, R² = 0.82). Explained variance ranged from 10%-69% and 11%-38% for all other internal TL measures and external measures, respectively. In summary, the iTRIMP method demonstrates a dose-response relationship with changes in aerobic fitness in elite youth soccer players.

Self-Paced Cycling at the Highest Sustainable Intensity With Blood Flow Restriction Reduces External but Not Internal Training Loads

Purpose: This study compared training loads and internal:external load ratios from an aerobic interval session at the highest perceptually sustainable intensity with and without blood flow restriction (BFR). Methods: On separate days, 14 endurance cyclists/triathletes completed four 4-minute self-paced aerobic cycling intervals at their highest sustainable intensity, with and without BFR (60% of arterial occlusion pressure). Internal training load was quantified using 3 training impulses (TRIMP; Banister, Lucia, and Edwards) and sessional ratings of perceived exertion. External load was assessed using total work done (TWD). Training load ratios between all internal loads were calculated relative to TWD. Results: Lucia TRIMP was lower for the BFR compared with non-BFR session (49 [9] vs 53 [8] arbitrary units [au], P = .020, dz = −0.71). No between-conditions differences were observed for Banister TRIMP (P = .068), Edwards TRIMP (P = .072), and training load in sessional ratings of perceived exertion (P = .134). The TWD was lower for the BFR compared with non-BFR session (223 [52] vs 271 [58] kJ, P < .001, dz = −1.27). Ratios were greater for the BFR session compared with non-BFR for Lucia TRIMP:TWD (0.229 [0.056] vs 0.206 [0.056] au, P < .001, dz = 1.21), Edwards TRIMP:TWD (0.396 [0.105] vs 0.370 [0.088] au, P = .031, dz = 0.66), and training load in sessional ratings of perceived exertion:TWD (1.000 [0.266] vs 0.890 [0.275] au, P = .044, dz = 0.60), but not Banister TRIMP:TWD (P = .306). Conclusions: Practitioners should consider both internal and external loads when monitoring BFR exercise to ensure the demands are appropriately captured. These BFR-induced changes were reflected by the Lucia TRIMP:TWD and Edwards TRIMP:TWD ratio, which could be used to monitor aerobic BFR training loads. The Lucia TRIMP:TWD ratio likely represents BFR-induced changes more appropriately compared with ratios involving either Edwards or Banister TRIMP.

Athlete Resilience Trajectories Across Competitive Training: The Influence of Physical and Psychological Stress

Competitive sport involves physical and psychological stressors, such as training load and stress perceptions, that athletes must adapt to in order to maintain health and performance. Psychological resilience, one’s capacity to equilibrate or adapt affective and behavioral responses to adverse physical or emotional experiences, is an important topic in athlete training and performance. The study purpose was to investigate associations of training load and perceived sport stress with athlete psychological resilience trajectories. Sixty-one collegiate club athletes (30 females and 31 males) completed self-reported surveys over 6 weeks of training. Athletes significantly differed in resilience at the beginning of competitive training. Baseline resilience differences were associated with resilience trajectories. Perceived stress and training load were negatively associated with resilience. Physical and psychological stressors had a small but statistically significant impact on resilience across weeks of competitive training, indicating that both types of stressors should be monitored to maintain athlete resilience.

The Impact of Environmental Conditions on Player Loads During Preseason Training Sessions in Women's Soccer Athletes

ABSTRACT

Austin, AB, Collins, SM, Huggins, RA, Smith, BA, and Bowman, TG. The impact of environmental conditions on player loads during preseason training sessions in women's soccer athletes. J Strength Cond Res 35(10): 2775-2782, 2021-Our objective was to determine the impact of environmental conditions on player loads during preseason training sessions in women's soccer athletes. Eleven women's NCAA Division III soccer players (age = 20 ± 1 year, height = 167.28 ± 8.65 cm, body mass = 60.18 ± 5.42 kg, V̇o2max = 43.70 ± 3.95 ml·kg-1·min-1) volunteered to wear Global Positioning System (GPS) devices (Sports Performance Tracking, Melbourne, Australia) that provided measures of training session external intensity throughout all preseason practices (n = 15). We recorded wet-bulb globe temperature (WBGT), session Rating of Perceived Exertion-Training Load (sRPE-TL), and ΔBM during each preseason training session and set α ≤ 0.05. The combination of WBGT, sRPE-TL, and ΔBM explained 34% of the variance in GPS-based intensity score (proprietary measure) (F3,153 = 26.25, p < 0.001). Wet-bulb globe temperature (t156 = -2.58, p = 0.01), sRPE (t156 = 8.24, p < 0.001), and ΔBM (t156 = 2.39, p = 0.02) were significantly associated with intensity. The ΔBM from prepractice (60.00 ± 5.21 kg) to postpractice (59.61 ± 5.10 kg) was statistically significant (p < 0.001); however, ΔBM from the beginning of preseason (59.87 ± 5.31 kg) to the end of preseason (59.91 ± 5.58 kg) was not significant (p = 0.89). Despite relatively low to moderate environmental conditions, increases in WBGT were associated with reductions in GPS intensity and elevated internal load via sRPE-TL. Our findings support the association between exercise intensity and WBGT, internal load, and hydration status; thus, coaches and exercise scientists should take these factors into account when monitoring or interpreting intensity metrics. Furthermore, these findings support the continued use of environmental monitoring and hydration best-practice policies to limit exercise intensity in the heat so as to mitigate excessive heat stress.

Continuous Versus Intermittent Running: Acute Performance Decrement and Training Load

PURPOSE

To examine the effect of continuous (CON) and intermittent (INT) running training sessions of different durations and intensities on subsequent performance and calculated training load (TL).

METHODS

Runners (N = 11) performed a 1500-m time trial as a baseline and after completing 4 different running training sessions. The training sessions were performed in a randomized order and were either maximal for 10 minutes (10CON and 10INT) or submaximal for 25 minutes (25CON and 25INT). An acute performance decrement (APD) was calculated as the percentage change in 1500-m time-trial speed measured after training compared with baseline. The pattern of APD response was compared with that for several TL metrics (bTRIMP, eTRIMP, iTRIMP, running training stress score, and session rating of perceived exertion) for the respective training sessions.

RESULTS

Average speed (P < .001, ηp2=.924) was different for each of the initial training sessions, which all resulted in a significant APD. This APD was similar when compared across the sessions except for a greater APD found after 10INT versus 25CON (P = .02). In contrast, most TL metrics were different and showed the opposite response to APD, being higher for CON versus INT and lower for 10- versus 25-minute sessions (P < .001, ηp2>.563).

CONCLUSION

An APD was observed consistently after running training sessions, but it was not consistent with most of the calculated TL metrics. The lack of agreement found between APD and TL suggests that current methods for quantifying TL are flawed when used to compare CON and INT running training sessions of different durations and intensities.

The Influence of Mental Fatigue on Sessional Ratings of Perceived Exertion in Elite Open and Closed Skill Sports Athletes

ABSTRACT

Coyne, JOC, Coutts, AJ, Newton, RU, and Haff, GG. The influence of mental fatigue on sessional ratings of perceived exertion in elite open and closed skill sports athletes. J Strength Cond Res 35(4): 963-969, 2021-The main purpose of this investigation was to examine influence of mental fatigue on sessional ratings of perceived exertion (sRPE) over a training week in elite athletes in open skill (OS, i.e., more unpredictable and externally paced sports) and closed skill (CS, i.e., more predictable and internally paced) sports. Visual analogue scales for mental fatigue, sRPE (CR-10 scale), and training duration were collected from an OS group (n = 27) of basketball and volleyball athletes and a CS group (n = 28) of weightlifting and track and field athletes during a typical training week 5 months before the 2016 Olympic Games. These variables were then examined using repeated measure correlations and linear mixed models with the level of significance set for the study at p < 0.05. There was a small significant correlation between mental fatigue and sRPE in the OS group (r = 0.23, p < 0.01), but not in the CS group (r = -0.07, p = 0.38). Mental fatigue had trivial influence on sRPE during individual sessions, but had a moderate effect on total sRPE over a week (p < 0.001, f2 = 0.265) when accounting for type of sport, training duration, and injury/illness burden. It seems mental fatigue may not significantly influence sRPE in individual training sessions, but may potentially have a cumulative effect that may affect the sRPE over a training week. This suggests monitoring mental fatigue independently of other training load (TL) measures may be worthwhile for strength and conditioning specialists and sports coaches to manage their athletes and researchers conducting studies into TL and performance.

Influence of Baseball Training Load on Clinical Reach Tests and Grip Strength in Collegiate Baseball Players

CONTEXT

A baseball-specific training load may influence strength or glenohumeral range of motion, which are related to baseball injuries. Glenohumeral reach tests and grip strength are clinical assessments of shoulder range of motion and upper extremity strength, respectively.

OBJECTIVE

To examine changes in glenohumeral reach test performance and grip strength between dominant and nondominant limbs and high, moderate, and low baseball-specific training-load groups.

DESIGN

Repeated-measures study.

SETTING

University laboratory and satellite clinic.

PATIENTS OR OTHER PARTICIPANTS

Collegiate baseball athletes (n = 18, age = 20.1 ± 1.3 years, height = 185.0 ± 6.5 cm, mass = 90.9 ± 10.2 kg).

MAIN OUTCOME MEASURE(S)

Participants performed overhead reach tests (OHRTs), behind-the-back reach tests (BBRTs), and grip strength assessments using the dominant and nondominant limbs every 4 weeks for 16 weeks. Percentage change scores were calculated between testing times. After each training session, participants provided their duration of baseball activity, throw count, and body-specific and arm-specific ratings of perceived exertion. We classified them in the high, moderate, or low training-load group based on each training-load variable: body-specific acute:chronic workload ratio (ACWR), arm-specific ACWR, body-specific cumulative load, and arm-specific cumulative load. Mixed models were used to compare training-load groups and limbs.

RESULTS

The arm-specific ACWR group demonstrated as main effect for OHRT (F = 7.70, P = .001), BBRT (F = 4.01, P = .029), and grip strength (F = 8.89, P < .001). For the OHRT, the moderate training-load group demonstrated a 10.8% greater increase than the high group (P = .004) and a 13.2% greater increase than the low group (P < .001). For the BBRT, the low training-load group had a 10.1% greater increase than the moderate group (P = .011). For grip strength, the low training-load group demonstrated a 12.1% greater increase than the high group (P = .006) and a 17.7% greater increase than the moderate group (P < .001).

CONCLUSIONS

Arm-specific ACWR was related to changes in clinical assessments of range of motion and strength. Clinicians may use arm-specific ACWR to indicate when a baseball athlete's physical health is changing.

Monitoring Training Load in Soccer: The ROMEI Model

Montini, M and Rocchi, JE. Monitoring training load in soccer: The Relation of Ongoing Monitored Exercise in Individual model. J Strength Cond Res 12XX(2X): 000-000, 2016. For a training organization, monitoring training load (TL) is of paramount importance. Despite this, a conclusive response on such topic is yet to be reported. The aims of this study were to investigate the relationship between TL indicators and to propose a new method for monitoring TL response and physical fitness. Twenty professional soccer players were retrospectively evaluated. The first phase of data analysis included 34 in-season training sessions. Subsequently, three microcycles (T1-T2-T3) of pre-season training were processed. A regression model was used to examine the relationships between internal TL (session rating of perceived exertion [s-RPE]) and external TL (energy expenditure, EE). The standard error of the regression equation was used to propose a new model called "ROMEI" (Relation of Ongoing Monitored Exercise in Individual). The level of statistical significance was set at p < 0.05. During the competitive season and the pre-season training camp, the average TL values were 65.8 ± 22 and 58.2 ± 22 minutes; 336 ± 204 and 228 ± 101 AU of s-RPE; and 29 ± 13 and 25 ± 9 kJ kJ of EE, respectively. In the competitive season, the collective and average individual correlation coefficients between s-RPE and EE were r = 0.888 and r = 0.892 ± 0.05, respectively. Considering slope values (m) of the regression line, data highlighted a significant increase of +34.4 ± 15.9% in T2 vs. T3 (p < 0.001) and +38.2 ± 15.2% in T1 vs. T3 (p < 0.001). Data shown in this investigation support the use of an individualized analysis to better understand the TL administered to soccer players rather than a collective analysis. This may be accomplished with the proposed ROMEI model.

Do Athlete Monitoring Tools Improve a Coach's Understanding of Performance Change?

PURPOSE

To assess a coach's subjective assessment of their athletes' performances and whether the use of athlete-monitoring tools could improve on the coach's prediction to identify performance changes.

METHODS

Eight highly trained swimmers (7 male and 1 female, age 21.6 [2.0] y) recorded perceived fatigue, total quality recovery, and heart-rate variability over a 9-month period. Prior to each race of the swimmers' main 2 events, the coach (n = 1) was presented with their previous race results and asked to predict their race time. All race results (n = 93) with aligning coach's predictions were recorded and classified as a dichotomous outcome (0 = no change; 1 = performance decrement or improvement [change +/- > or < smallest meaningful change]). A generalized estimating equation was used to assess the coach's accuracy and the contribution of monitoring variables to the model fit. The probability from generalized estimating equation models was assessed with receiver operating characteristic curves to identify the model's accuracy from the area under the curve analysis.

RESULTS

The coach's predictions had the highest diagnostic accuracy to identify both decrements (area under the curve: 0.93; 95% confidence interval, 0.88-0.99) and improvements (area under the curve: 0.89; 95% confidence interval, 0.83-0.96) in performance.

CONCLUSIONS

These findings highlight the high accuracy of a coach's subjective assessment of performance. Furthermore, the findings provide a future benchmark for athlete-monitoring systems to be able to improve on a coach's existing understanding of swimming performance.

Heart rate and stroke rate misrepresent supramaximal sprint kayak training as quantified by power

This study examined the utility of novel measures of power output (PO) compared to traditional measures of heart rate (HR) and stroke rate (SR) for quantifying high-intensity sprint kayak training. Twelve well-trained, male and female sprint kayakers (21.3 ± 6.8 y) completed an on-water graded exercise test (GXT) and a 200-, 500- and 1000-m time-trial for the delineation of individualised training zones (T) for HR (5-zone model, T1-T5), SR and PO (8-zone model, T1-T8). Subsequently, athletes completed two repeat trials of a high-intensity interval (HIIT) and a sprint interval (SIT) training session, where intensity was prescribed using individualised PO-zones. Time-in-zone (minutes) using PO, SR and HR was then compared for both HIIT and SIT. Compared to PO, time-in-zone using HR was higher for T1 in HIIT and SIT (P < 0.001, d ≥ 0.90) and lower for T5 in HIIT (P < 0.001, d = 1.76). Average and peak HR were not different between HIIT (160 ± 9 and 173 ± 11 bpm, respectively) and SIT (157 ± 13 and 174 ± 10 bpm, respectively) (P ≥ 0.274). In HIIT, time-in-zone using SR was higher for T4 (P < 0.001, d = 0.85) and was lower for T5 (P = 0.005, d = 0.43) and T6 (P < 0.001, d = 0.94) compared to PO. In SIT, time-in-zone using SR was lower for T7 (P = 0.001, d = 0.66) and was higher for T8 (P = 0.004, d = 0.70), compared to PO. Heart rate measures were unable to differentiate training demands across different high-intensity sessions, and could therefore misrepresent the training load in such instances. Furthermore, SR may not provide a sensitive measure for detecting changes in intensity due to fatigue, whereas PO may be more suitable.

Preliminary Validation of Mirrored Scales for Monitoring Professional Soccer Training Sessions

We aimed to create a single subjective method to assess both internal training loads and subsequent fatigue. This new training-fatigue (dose-response) scale (TFS) was composed of two similar scales with the same properties, metrics and construction criteria. These two scales were designed to rate the perceived exertion (RPETFS) and perceived fatigue (RPFTFS) in professional soccer players. Twenty-two athletes participated to establish reliability, and 15 participated to establish validity. For reliability, the intraclass correlation coefficient (ICC) and standard error of measurement (SEM) were used. For criterion validity, the Spearman’s correlation coefficient and linear regression analyses were applied. Associations between RPETFS and RPFTFS were verified by a chi square test, and a further factorial exploratory analysis was conducted. RPETFS and RPFTFS were found to be reliable (ICC 0.74 and 0.77, SEM 0.30 and 0.30, respectively) and valid. RPETFS was best explained by the internal load of the Banister training impulse (p < 0.001), while RPFTFS was best explained by the internal load of the Stagno training impulse (p < 0.001). An association was found between the scales (RPETFS and RPFTFS) in which training duration had a more substantial impact on these subjective perceptions than did training intensity (p < 0.01). RPETFS and RPFTFS scales are reliable and valid for monitoring training sessions in Brazilian professional soccer players. The simultaneous oscillations of the RPETFS and RPFTFS scores can be used by staff members to better plan weekly training programs based on dose-response ratings. Finally, training duration must be carefully controlled because it has a greater impact than intensity on subjective perceptions.

Individual Response to External Training Load in Elite Football Players

PURPOSE

To investigate within-player effect, between-player effect, and individual response of external training load from player tracking devices on session rating of perceived exertion training load (sRPE-TL) in elite football players.

METHODS

The authors collected sRPE-TL from 18 outfield players in 21 training sessions. Total distance, high-speed running distance (>14.4 m/s), very high-speed running distance (>19.8 m/s), PlayerLoad™, PlayerLoad2D™, and high-intensity events (HIE > 1.5, HIE > 2.5, and HIE > 3.5 m/s) were extracted from the tracking devices. The authors modeled within-player and between-player effects of single external load variables on sRPE-TL, and multiple levels of variability, using a linear mixed model. The effect of 2 SDs of external load on sRPE-TL was evaluated with magnitude-based inferences.

RESULTS

Total distance, PlayerLoad™, PlayerLoad2D™, and HIE > 1.5 had most likely substantial within-player effects on sRPE-TL (100%-106%, very large effect sizes). Moreover, the authors observed likely substantial between-player effects (12%-19%, small to moderate effect sizes) from the majority of the external load variables and likely to very likely substantial individual responses of PlayerLoad™, high-speed running distance, very high-speed running distance, and HIE > 1.5 (19%-30% coefficient of variation, moderate to large effect sizes). Finally, sRPE-TL showed large to very large between-session variability with all external load variables.

CONCLUSIONS

External load variables with low intensity-thresholds had the strongest relationship with sRPE-TL. Furthermore, the between-player effect of external load and the individual response to external load advocate for monitoring sRPE-TL in addition to external load. Finally, the large between-session variability in sRPE-TL demonstrates that substantial amounts of sRPE-TL in training sessions are not explained by single external load variables.

The Influence of Exercise Intensity on the Association Between Kilojoules Spent and Various Training Loads in Professional Cycling

Purpose: A valid measure for training load (TL) is an important tool for cyclists, trainers, and sport scientists involved in professional cycling. The aim of this study was to explore the influence of exercise intensity on the association between kilojoules (kJ) spent and different measures of TL to arrive at valid measures of TL. Methods: Four years of field data were collected from 21 cyclists of a professional cycling team, including 11,716 training and race sessions. kJ spent was obtained from power output measurements, and others TLs were calculated based on the session rating of perceived exertion (sRPE), heart rate (Lucia training impulse [luTRIMP]), and power output (training stress score [TSS]). Exercise intensity was expressed by the intensity factor (IF). To study the effect of exercise intensity on the association between kJ spent and various other TLs (sRPE, luTRIMP, and TSS), data from low- and high-intensity sessions were subjected to regression analyses using generalized estimating equations. Results: This study shows that the IF is significantly different for training and race sessions (0.59 [0.03] vs 0.73 [0.03]). Significant regression coefficients show that kJ spent is a good predictor of sRPE, and luTRIMP, as well as TSS. However, IF does not influence the associations between kJ spent and sRPE and luTRIMP, while the association with TSS is different when sessions are done with low or high IF. Conclusion: It seems that the TSS reacts differently to exercise intensity than sRPE and luTRIMP. A possible explanation could be the quadratic relation between IF and TSS.

Test-retest reliability of TRIMP in collegiate ice hockey players

The utility of the heart rate derived variable TRaining IMPulse (TRIMP) for assessing internal training load in ice hockey players is not clear. Having a reliable measure of internal training load during on-ice training sessions would help coaches program exercise training. This study determined the reliability of TRIMP during on-ice training sessions in ice hockey players. Twelve Division I collegiate male ice hockey players (aged 18–23 years) had their heart rate (HR) data recorded during two on-ice practice sessions separated by two weeks. TRIMP and other descriptive HR variables were compared between sessions. TRIMP demonstrated moderate reliability during on-ice sessions. Systematic error, quantified as standardized change in means was negligible (–0.19); random error quantified as the percent typical error (%TE) was moderate (12.2%); and, test-retest correlation was very strong (0.75). TRIMP is suitable for quantifying training load during intermittent work in hockey athletes. The results from our study can be used to determine the threshold for meaningful change in TRIMP, which may aid in informing decisions by coaches and strength training staff regarding on-ice training session difficulty and composition.

Relationship Between Various Training-Load Measures in Elite Cyclists During Training, Road Races, and Time Trials

Purpose: The relationship between various training-load (TL) measures in professional cycling is not well explored. This study investigated the relationship between mechanical energy spent (in kilojoules), session rating of perceived exertion (sRPE), Lucia training impulse (LuTRIMP), and training stress score (TSS) in training, races, and time trials (TT). Methods: For 4 consecutive years, field data were collected from 21 professional cyclists and categorized as being collected in training, racing, or TTs. Kilojoules (kJ) spent, sRPE, LuTRIMP, and TSS were calculated, and the correlations between the various TLs were made. Results: 11,655 sessions were collected, from which 7596 sessions had heart-rate data and 5445 sessions had an RPE score available. The r between the various TLs during training was almost perfect. The r between the various TLs during racing was almost perfect or very large. The r between the various TLs during TTs was almost perfect or very large. For all relationships between TSS and 1 of the other measurements of TL (kJ spent, sRPE, and LuTRIMP), a significant different slope was found. Conclusion: kJ spent, sRPE, LuTRIMP, and TSS all have a large or almost perfect relationship with each other during training, racing, and TTs, but during racing, both sRPE and LuTRIMP have a weaker relationship with kJ spent and TSS. Furthermore, the significant different slope of TSS vs the other measurements of TL during training and racing has the effect that TSS collected in training and road races differs by 120%, whereas the other measurements of TL (kJ spent, sRPE, and LuTRIMP) differ by only 73%, 67%, and 68%, respectively.

Description of training loads using whole-body exercise during high-intensity interval training

OBJECTIVES

To describe external training load and internal training load through sets of a single session of high-intensity interval training (HIIT) body work.

METHODS

Twenty male individuals (24±3 years) performed a HIIT body work protocol consisting of a single bout of exercise with 1:1 stimuli. The exercises used were 30 min in duration with "all-out" intensity. The exercises included jumping jacks, mountain climbers, burpees and squat jumps, totaling 20 min of exercise. During exercise, total movement capacity, blood lactate measurement, ratings of perceived exertion and recovery, training load and intensity were monitored.

RESULTS

The single bout examined showed a total of 382±89 movements. Differences (p<0.01) in the total amount of movement for each exercise were noted, reflecting the difficulty of maintaining exercise over time. Increases in lactate concentrations (before: 0.98±0.16, after: 14.10±1.66; mmol/L) were found postexercise. Significant differences (p<0.01) were found after the fifth set, and the values for movement capacity remained higher than the values of the first set, demonstrating high load in a single session. No differences in ratings of perceived exertion (RPE) during the sets were found. However, the ratings of perceived recuperation from the second set were significantly (p<0.01) lower than those from the first set.

CONCLUSIONS

The exercise protocol used in this study was of high intensity and produced large values for stress during performance, with increases recorded for the internal load indicators.

Changes in Pain and Nutritional Intake Modulate Ultra-Running Performance: A Case Report

Ultra-endurance running provides numerous physiological, psychological, and nutritional challenges to the athlete and supporting practitioners. We describe the changes in physiological status, psychological condition, and nutritional intake over the course of two 100-mile running races, with differing outcomes: non-completion and completion. Athlete perception of pain, freshness, and motivation differed between events, independent of rating of perceived exertion. Our data suggest that the integration of multiple sensations (freshness, motivation, hunger, pain, and thirst) produce performance. Increases in carbohydrate feeding (+5 g·h⁻¹) and protein intake (+0.3 g·kg⁻¹) also likely contributed to successful completion of a 100-mile race, by reducing the fractional utilization of maximal oxygen uptake and satiating hunger, respectively. Nutritional data support the notion that the gut is a trainable, and critical organ with respect to ultra-endurance performance. Finally, we propose future research to investigate the rate at which peak feeding occurs throughout ultra-endurance events, as this may further serve to personalize sports nutrition strategies.

Session-RPE Method for Training Load Monitoring: Validity, Ecological Usefulness, and Influencing Factors

Purpose: The aim of this review is to (1) retrieve all data validating the Session-rating of perceived exertion (RPE)-method using various criteria, (2) highlight the rationale of this method and its ecological usefulness, and (3) describe factors that can alter RPE and users of this method should take into consideration.

Method: Search engines such as SPORTDiscus, PubMed, and Google Scholar databases in the English language between 2001 and 2016 were consulted for the validity and usefulness of the session-RPE method. Studies were considered for further analysis when they used the session-RPE method proposed by Foster et al. in 2001. Participants were athletes of any gender, age, or level of competition. Studies using languages other than English were excluded in the analysis of the validity and reliability of the session-RPE method. Other studies were examined to explain the rationale of the session-RPE method and the origin of RPE.

Results: A total of 950 studies cited the Foster et al. study that proposed the session RPE-method. 36 studies have examined the validity and reliability of this proposed method using the modified CR-10.

Conclusion: These studies confirmed the validity and good reliability and internal consistency of session-RPE method in several sports and physical activities with men and women of different age categories (children, adolescents, and adults) among various expertise levels. This method could be used as “standing alone” method for training load (TL) monitoring purposes though some recommend to combine it with other physiological parameters as heart rate.

Monitoring training load and fatigue in soccer players with physiological markers

The quantification and monitoring of training load (TL) has been the topic of many scientific works in the last fifteen years. TL monitoring helps coaches to individually prescribe, follow-up, analyse, adjust and programme training sessions. In particular, the aim of the present review was to provide a critical literature report regarding different physiological markers of TL monitoring, particularly in soccer, as the load is specific to individual sports. Therefore, the interests and limitations of heart rate (HR), HR variability (HRV) and biochemical variables (blood, urinary and hormonal variations) were analysed, with a special focus on daily measures (before, during and after training) and monitoring throughout a whole season. It appears that the most relevant markers were the resting HR before training, HR reserve during training, HRV during rest days, blood lactate, and blood and salivary immunological status in follow-ups throughout the season. Urinary markers indicative of the players' hydration status also deserve attention. However, these objective markers should be considered with a subjective marker of TL such as the rating of perceived exertion to give a more precise quantification of TL and its perception. Future research could be directed towards urinary marker analysis and the analysis of specific markers of TL, which could be related to injury occurrence and to performance during competition.

Role of Ratings of Perceived Exertion during Self-Paced Exercise: What are We Actually Measuring?

Ratings of perceived exertion (RPE) and effort are considered extremely important in the regulation of intensity during self-paced physical activity. While effort and exertion are slightly different constructs, these terms are often used interchangeably within the literature. The development of perceptions of both effort and exertion is a complicated process involving numerous neural processes occurring in various regions within the brain. It is widely accepted that perceptions of effort are highly dependent on efferent copies of central drive which are sent from motor to sensory regions of the brain. Additionally, it has been suggested that perceptions of effort and exertion are integrated based on the balance between corollary discharge and actual afferent feedback; however, the involvement of peripheral afferent sensory feedback in the development of such perceptions has been debated. As such, this review examines the possible difference between effort and exertion, and the implications of such differences in understanding the role of such perceptions in the regulation of pace during exercise.

Characteristics impacting on session rating of perceived exertion training load in Australian footballers

The relationship between external training load and session rating of perceived exertion (s-RPE) training load and the impact that playing experience, playing position and 2-km time-trial performance had on s-RPE training load were explored. From 39 Australian Football players, 6.9 ± 4.6 training sessions were analysed, resulting in 270 samples. Microtechnology devices provided external training load (distance, average speed, high-speed running distance, player load (PL) and player loadslow (PLslow)). The external training load measures had moderate to very large associations (r, 95% CI) with s-RPE training load, average speed (0.45, 0.35-0.54), high-speed running distance (0.51, 0.42-0.59), PLslow (0.80, 0.75-0.84), PL (0.86, 0.83-0.89) and distance (0.88, 0.85-0.90). Differences were described using effect sizes (d ±95% CL). When controlling for external training load, the 4- to 5-year players had higher s-RPE training load than the 0- to 1- (0.44 ± 0.33) and 2- to 3-year players (0.51 ± 0.30), ruckmen had moderately higher s-RPE training load than midfielders (0.82 ± 0.58), and there was a 0.2% increase in s-RPE training load per 1 s increase in time-trial (95% CI: 0.07-0.34). Experience, position and time-trial performance impacted the relationship between external training load and s-RPE training load. This suggests that a given external training load may result in different internal responses between athletes, potentially leaving individuals at risk of overtraining or failing to elicit positive adaptation. It is therefore vital that coaches and trainers give consideration to these mediators of s-RPE training load.

A comparison of methods for quantifying training load: relationships between modelled and actual training responses

PURPOSE

To assess the validity of methods for quantifying training load, fitness and fatigue in endurance athletes using a mathematical model.

METHODS

Seven trained runners (VO2max: 51.7 ± 4.5 mL kg(-1) min(-1), age: 38.6 ± 9.4 years, mean ± SD) completed 15 weeks of endurance running training. Training sessions were assessed using a heart rate (HR), running pace and rating of perceived exertion (RPE). Training dose was calculated using the session-RPE method, Banisters TRIMP and the running training stress score (rTSS). Weekly running performance (1,500-m time trial), fitness (submaximal HR, resting HR) and fatigue [profile of mood states, heart rate variability (HRV)] were measured. A mathematical model was applied to the training data from each runner to provide individual estimates of performance, fitness and fatigue. Correlations assessed the relationships between the modelled and actual weekly performance, fitness and fatigue measures within each runner.

RESULTS

Training resulted in 5.4 ± 2.6 % improvement in 1,500-m performance. Modelled performance was correlated with actual performance in each subject, with relationships being r = 0.70 ± 0.11, 0.60 ± 0.10 and 0.65 ± 0.13 for the rTSS, session-RPE and TRIMP input methods, respectively. There were moderate correlations between modelled and actual fitness (submaximal HR) for the session-RPE (-0.43 ± 0.37) and TRIMP (-0.48 ± 0.39) methods and moderate-to-large correlations between modelled and actual fatigue measured through HRV indices for both session-RPE (-0.48 ± 0.39) and TRIMP (-0.59 ± 0.31) methods.

CONCLUSIONS

These findings showed that each of the training load methods investigated are appropriate for quantifying endurance training dose and that submaximal HR and HRV may be useful for monitoring fitness and fatigue, respectively.