scholarly journals The Association Between Internal and External Measures of Training Load in Batsmen and Medium-Fast Bowlers During Net-Based Cricket Training

2017 ◽  
Vol 12 (2) ◽  
pp. 247-253 ◽  
Author(s):  
Will Vickery ◽  
Ben Dascombe ◽  
Rob Duffield
Keyword(s):  
Heart Rate ◽  
Multiple Regression ◽  
High Intensity ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Stepwise Multiple Regression ◽  
Total Distance ◽  
Regression Techniques ◽  
External Training

Purpose:To examine the relationship between session rating of perceived exertion (sRPE) and measures of internal and external training load (TL) in cricket batsmen and medium-fast bowlers during net-based training sessions.Methods:The internal (heart rate), external (movement demands, PlayerLoad), and technical (cricket-specific skills) loads of 30 male cricket players (age 21.2 ± 3.8 y, height 1.82 ± 0.07 m, body mass 79.0 ± 8.7 kg) were determined from net-based cricket-training sessions (n = 118). The relationships between sRPE and measures of TL were quantified using Pearson product–moment correlations respective to playing position. Stepwise multiple-regression techniques provided key internal- and external-load determinants of sRPE in cricket players.Results:Significant correlations were evident (r = -.34 to .87, P < .05) between internal and external measures of TL and sRPE, with the strongest correlations (r ≥ .62) for GPS-derived measures for both playing positions. In batsmen, stepwise multiple-regression analysis revealed that 67.8% of the adjusted variance in sRPE could be explained by PlayerLoad and high-intensity distance (y = 27.43 + 0.81 PlayerLoad + 0.29 high-intensity distance). For medium-fast bowlers, 76.3% of the adjusted variance could be explained by total distance and mean heart rate (y = 101.82 + total distance 0.05 + HRmean – 0.48).Conclusion:These results suggest that sRPE is a valid method of reporting TL among cricket batsmen and medium-fast bowlers. Position-specific responses are evident and should be considered when monitoring the TL of cricket players.

Quantifying Training Loads in Contemporary Dance

2017 ◽  
Vol 12 (6) ◽  
pp. 796-802 ◽  
Author(s):  
Annie C. Jeffries ◽  
Lee Wallace ◽  
Aaron J. Coutts
Keyword(s):  
Heart Rate ◽  
Sleep Quality ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Stepwise Multiple Regression ◽  
Contemporary Dance ◽  
Related Factors ◽  
Dance Training ◽  
Metabolic Equivalents

Purpose:To describe the training demands of contemporary dance and determine the validity of using the session rating of perceived exertion (sRPE) to monitor exercise intensity and training load in this activity. In addition, the authors examined the contribution of training (ie, accelerometry and heart rate) and non-training-related factors (ie, sleep and wellness) to perceived exertion during dance training.Methods:Training load and ActiGraphy for 16 elite amateur contemporary dancers were collected during a 49-d period, using heart-rate monitors, accelerometry, and sRPE. Within-individual correlation analysis was used to determine relationships between sRPE and several other measures of training intensity and load. Stepwise multiple regressions were used to determine a predictive equation to estimate sRPE during dance training.Results:Average weekly training load was 4283 ± 2442 arbitrary units (AU), monotony 2.13 ± 0.92 AU, strain 10677 ± 9438 AU, and average weekly vector magnitude load 1809,707 ± 1015,402 AU. There were large to very large within-individual correlations between training-load sRPE and various other internal and external measures of intensity and load. The stepwise multiple-regression analysis also revealed that 49.7% of the adjusted variance in training-load sRPE was explained by peak heart rate, metabolic equivalents, soreness, motivation, and sleep quality (y = –4.637 + 13.817%HRpeak + 0.316 METS + 0.100 soreness + 0.116 motivation – 0.204 sleep quality).Conclusion:The current findings demonstrate the validity of the sRPE method for quantifying training load in dance, that dancers undertake very high training loads, and a combination of training and nontraining factors contribute to perceived exertion in dance training.

Quantifying Training Load: A Comparison of Subjective and Objective Methods

2008 ◽  
Vol 3 (1) ◽  
pp. 16-30 ◽  
Author(s):  
Jill Borresen ◽  
Michael I. Lambert
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Regression Equations ◽  
Training Time ◽  
Ad Libitum ◽  
Training Impulse ◽  
The Relationship

Purpose:To establish the relationship between a subjective (session rating of perceived exertion [RPE]) and 2 objective (training impulse [TRIMP]) and summated-heart-rate-zone (SHRZ) methods of quantifying training load and explain characteristics of the variance not accounted for in these relationships.Methods:Thirty-three participants trained ad libitum for 2 wk, and their heart rate (HR) and RPE were recorded to calculate training load. Subjects were divided into groups based on whether the regression equations over- (OVER), under- (UNDER), or accurately predicted (ACCURATE) the relationship between objective and subjective methods.Results:A correlation of r = .76 (95% CI: .56 to .88) occurred between TRIMP and session-RPE training load. OVER spent a greater percentage of training time in zone 4 of SHRZ (ie, 80% to 90% HRmax) than UNDER (46% ± 8% vs 25% ± 10% [mean ± SD], P = .008). UNDER spent a greater percentage of training time in zone 1 of SHRZ (ie, 50% to 60% HRmax) than OVER (15% ± 8% vs 3% ± 3%, P = .005) and ACCURATE (5% ± 3%, P = .020) and more time in zone 2 of SHRZ (ie, 60% to 70%HRmax) than OVER (17% ± 6% vs 7% ± 6%, P = .039). A correlation of r = .84 (.70 to .92) occurred between SHRZ and session-RPE training load. OVER spent proportionally more time in Zone 4 than UNDER (45% ± 8% vs 25% ± 10%, P = .018). UNDER had a lower training HR than ACCURATE (132 ± 10 vs 148 ± 12 beats/min, P = .048) and spent more time in zone 1 than OVER (15% ± 8% vs 4% ± 3%, P = .013) and ACCURATE (5% ± 3%, P = .015).Conclusions:The session-RPE method provides reasonably accurate assessments of training load compared with HR-based methods, but they deviate in accuracy when proportionally more time is spent training at low or high intensity.

Quantifying Training Demands of a 2-Week In-Season Squash Microcycle

2020 ◽  
pp. 1-8
Author(s):  
Carl James ◽  
Aishwar Dhawan ◽  
Timothy Jones ◽  
Olivier Girard
Keyword(s):  
Heart Rate ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Global Positioning ◽  
Group Feeding ◽  
External Training ◽  
Group Sessions ◽  
Training Demands ◽  
Differential Rating

Purpose: To quantify the demands of specific on- and off-court sessions, using internal and external training load metrics, in elite squash. Methods: A total of 15 professional squash players (11 males and 4 females) wore a 100-Hz triaxial accelerometer/global positioning system unit and heart rate monitor during on-court “Group,” “Feeding,” “Ghosting,” “Matchplay,” and off-court “Conditioning” sessions across a 2-week in-season microcycle. Comparisons of absolute training load (total values) and relative intensity (per minute) were made between sessions for internal (session rating of perceived exertion, differential rating of perceived exertion, TRIMP) and external (Playerload, very high–intensity movements [>3.5 m·s−2]) metrics. Results: The Group sessions were the longest (79 [12] min), followed by Feeding (55 [15] min), Matchplay (46 [17] min), Conditioning (37 [9] min), and Ghosting (35 [6] min). Time >90% maximum heart rate was the lowest during Feeding (vs all others P < .05) but other sessions were not different (all P > .05). Relative Playerload during Conditioning (14.3 [3.3] arbitrary unit [a.u.] per min, all P < .05) was higher than Ghosting (7.5 [1.2] a.u./min) and Matchplay (6.9 [1.5] a.u./min), with no difference between these 2 sessions (P ≥ .999). Conditioning produced the highest Playerloads (519 [153] a.u., all P < .001), with the highest on-court Playerloads from Group (450 [94] a.u., all P < .001). The highest session rating of perceived exertion (all P < .001), Edward’s TRIMP (all P < .001), and TEAM-TRIMP (all P < .019) occurred during the Group sessions. Conclusions: Squash Matchplay does not systematically produce the highest training intensities and loads. Group sessions provide the highest training loads for many internal and external parameters and, therefore, play a central role within the training process. These findings facilitate planning or adjustment of intensity, volume, and frequency of sessions to achieve desirable physical outcomes.

scholarly journals Internal and External Training Load in Under-19 versus Professional Soccer Players during the In-Season Period

2021 ◽  
Vol 18 (2) ◽  
pp. 558
Author(s):  
Sullivan Coppalle ◽  
Guillaume Ravé ◽  
Jason Moran ◽  
Iyed Salhi ◽  
Abderraouf Ben Abderrahman ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Training Session ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Soccer Players ◽  
Time Intervals ◽  
Professional Soccer ◽  
Global Positioning ◽  
External Training ◽  
Soccer Team

This study aimed to compare the training load of a professional under-19 soccer team (U-19) to that of an elite adult team (EAT), from the same club, during the in-season period. Thirty-nine healthy soccer players were involved (EAT [n = 20]; U-19 [n = 19]) in the study which spanned four weeks. Training load (TL) was monitored as external TL, using a global positioning system (GPS), and internal TL, using a rating of perceived exertion (RPE). TL data were recorded after each training session. During soccer matches, players’ RPEs were recorded. The internal TL was quantified daily by means of the session rating of perceived exertion (session-RPE) using Borg’s 0–10 scale. For GPS data, the selected running speed intensities (over 0.5 s time intervals) were 12–15.9 km/h; 16–19.9 km/h; 20–24.9 km/h; >25 km/h (sprint). Distances covered between 16 and 19.9 km/h, > 20 km/h and >25 km/h were significantly higher in U-19 compared to EAT over the course of the study (p =0.023, d = 0.243, small; p = 0.016, d = 0.298, small; and p = 0.001, d = 0.564, small, respectively). EAT players performed significantly fewer sprints per week compared to U-19 players (p = 0.002, d = 0.526, small). RPE was significantly higher in U-19 compared to EAT (p =0.001, d = 0.188, trivial). The external and internal measures of TL were significantly higher in the U-19 group compared to the EAT soccer players. In conclusion, the results obtained show that the training load is greater in U19 compared to EAT.

scholarly journals Quantifying Accelerations and Decelerations in Elite Women Soccer Players during Regular In-Season Training as an Index of Training Load

Sports ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 109
Author(s):  
Tom Douchet ◽  
Allex Humbertclaude ◽  
Carole Cometti ◽  
Christos Paizis ◽  
Nicolas Babault
Keyword(s):  
Heart Rate ◽  
Perceived Exertion ◽  
Training Load ◽  
Soccer Players ◽  
Unit Recording ◽  
Fitness Level ◽  
Total Distance ◽  
Load Monitoring ◽  
Soccer Training ◽  
Stress Fatigue

Accelerations (ACC) and decelerations (DEC) are important and frequent actions in soccer. We aimed to investigate whether ACC and DEC were good indicators of the variation of training loads in elite women soccer players. Changes in the training load were monitored during two different selected weeks (considered a “low week” and a “heavy week”) during the in-season. Twelve elite soccer women playing in the French first division wore a 10-Hz Global Positioning System unit recording total distance, distance within speed ranges, sprint number, ACC, DEC, and a heart rate monitor during six soccer training sessions and rated their perceived exertion (RPE). They answered the Hooper questionnaire (sleep, stress, fatigue, DOMS) to get an insight of their subjective fitness level at the start (Hooper S) and at the end of each week (Hooper E). A countermovement jump (CMJ) was also performed once a week. During the heavy week, the training load was significantly greater than the low week when considering number of ACC >2 m·s−2 (28.2 ± 11.9 vs. 56.1 ± 10.1, p < 0.001) and number of DEC < −2 m·s−2 (31.5 ± 13.4 vs. 60.9 ± 14.4, p < 0.001). The mean heart rate percentage (HR%) (p < 0.05), RPE (p < 0.001), and Hooper E (p < 0.001) were significantly greater during the heavy week. ACC and DEC showed significant correlations with most outcomes: HR%, total distance, distance per min, sprint number, Hooper index of Hooper E, DOMS E, Fatigue E, RPE, and session RPE. We concluded that, for elite women soccer players, quantifying ACC and DEC alongside other indicators seemed to be essential for a more complete training load monitoring. Indeed, it could lead to a better understanding of the reasons why athletes get fatigued and give insight into neuromuscular, rather than only energetic, fatigue.

Internal Training Load Affects Day-After-Pretraining Perceived Fatigue in Female Volleyball Players

2021 ◽  
pp. 1-7
Author(s):  
Alexandru Nicolae Ungureanu ◽  
Corrado Lupo ◽  
Gennaro Boccia ◽  
Paolo Riccardo Brustio
Keyword(s):  
Heart Rate ◽  
Muscle Soreness ◽  
Perceived Exertion ◽  
Well Being ◽  
Delayed Onset Muscle Soreness ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Mixed Effect ◽  
Delayed Onset ◽  
Volleyball Players

Purpose: The primary aim of this study was to evaluate whether the internal (session rating of perceived exertion [sRPE] and Edwards heart-rate-based method) and external training load (jumps) affect the presession well-being perception on the day after (ie, +22 h), according to age and tactical position, in elite (ie, Serie A2) female volleyball training. Methods: Ten female elite volleyball players (age = 23 [4] y, height = 1.82 [0.04] m, body mass = 73.2 [4.9] kg) had their heart rate monitored during 13 team (115 individual) training sessions (duration: 101 [8] min). Mixed-effect models were applied to evaluate whether sRPE, Edwards method, and jumps were correlated (P ≤ .05) to Hooper index factors (ie, perceived sleep quality/disorders, stress level, fatigue, and delayed-onset muscle soreness) in relation to age and tactical position (ie, hitters, central blockers, opposites, and setters). Results: The results showed a direct relationship between sRPE (P < .001) and presession well-being perception 22 hours apart, whereas the relationship was the inverse for Edwards method internal training load. Age, as well as the performed jumps, did not affect the well-being perception of the day after. Finally, central blockers experienced a higher delayed-onset muscle soreness than hitters (P = .003). Conclusions: Findings indicated that female volleyball players’ internal training load influences the pretraining well-being status on the day after (+ 22 h). Therefore, coaches can benefit from this information to accurately implement periodization in a short-term perspective and to properly adopt recovery strategies in relation to the players’ well-being status.

Within-Subject Correlation Between Salivary IgA and Measures of Training Load in Elite Football Players

2019 ◽  
Vol 14 (6) ◽  
pp. 847-849 ◽  
Author(s):  
Pedro Figueiredo ◽  
George P. Nassis ◽  
João Brito
Keyword(s):  
High Speed ◽  
Perceived Exertion ◽  
Immunoglobulin A ◽  
Correlation Coefficients ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Football Players ◽  
Positioning Systems ◽  
External Training ◽  
Salivary Secretory Immunoglobulin A

Purpose: To quantify the association between salivary secretory immunoglobulin A (sIgA) and training load in elite football players. Methods: Data were obtained on 4 consecutive days during the preparation camp for the Rio 2016 Olympic Games. Saliva samples of 18 elite male football players were collected prior to breakfast. The session rating of perceived exertion (s-RPE) and external training-load metrics from global positioning systems (GPS) were recorded. Within-subject correlation coefficients between training load and sIgA concentration, and magnitude of relationships, were calculated. Results: sIgA presented moderate to large negative correlations with s-RPE (r = −.39), total distance covered (r = −.55), accelerations (r = −.52), and decelerations (r = −.48). Trivial to small associations were detected between sIgA and distance covered per minute (r = .01), high-speed distance (r = −.23), and number of sprints (r = −.18). sIgA displayed a likely moderate decrease from day 1 to day 2 (d = −0.7) but increased on day 3 (d = 0.6). The training-load variables had moderate to very large rises from day 1 to day 2 (d = 0.7 to 3.2) but lowered from day 2 to day 3 (d = −5.0 to −0.4), except for distance per minute (d = 0.8) and sprints (unclear). On day 3, all training-load variables had small to large increments compared with day 1 (d = 0.4 to 1.5), except for accelerations (d = −0.8) and decelerations (unclear). Conclusions: In elite football, sIgA might be more responsive to training volume than to intensity. External load such as GPS-derived variables presented stronger association with sIgA than with s-RPE. sIgA can be used as an additional objective tool in monitoring football players.

Training-Load Distribution in Endurance Runners: Objective Versus Subjective Assessment

2015 ◽  
Vol 10 (8) ◽  
pp. 1023-1028 ◽  
Author(s):  
Vincenzo Manzi ◽  
Antonio Bovenzi ◽  
Carlo Castagna ◽  
Paola Sinibaldi Salimei ◽  
Maurizio Volterrani ◽  
...  
Keyword(s):  
Heart Rate ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Maximal Heart Rate ◽  
Long Distance ◽  
Running Speed ◽  
Training Time ◽  
Significant Difference ◽  
Training Methodologies

Purpose:To assess the distribution of exercise intensity in long-distance recreational athletes (LDRs) preparing for a marathon and to test the hypothesis that individual perception of effort could provide training responses similar to those provided by standardized training methodologies.Methods:Seven LDRs (age 36.5 ± 3.8 y) were followed during a 5-mo training period culminating with a city marathon. Heart rate at 2.0 and 4.0 mmol/L and maximal heart rate were used to establish 3 intensity training zones. Internal training load (TL) was assessed by training zones and TRIMPi methods. These were compared with the session-rating-of-perceived-exertion (RPE) method.Results:Total time spent in zone 1 was higher than in zones 2 and 3 (76.3% ± 6.4%, 17.3% ± 5.8%, and 6.3% ± 0.9%, respectively; P = .000 for both, ES = 0.98, ES = 0.99). TL quantified by session-RPE provided the same result. The comparison between session-RPE and training-zones-based methods showed no significant difference at the lowest intensity (P = .07, ES = 0.25). A significant correlation was observed between TL RPE and TL TRIMPi at both individual and group levels (r = .79, P < .001). There was a significant correlation between total time spent in zone 1 and the improvement at the running speed of 2 mmol/L (r = .88, P < .001). A negative correlation was found between running speed at 2 mmol/L and the time needed to complete the marathon (r = –.83, P < .001).Conclusions:These findings suggest that in recreational LDRs most of the training time is spent at low intensity and that this is associated with improved performances. Session-RPE is an easy-to-use training method that provides responses similar to those obtained with standardized training methodologies.

Positional Differences in Elite Basketball: Selecting Appropriate Training-Load Measures

2018 ◽  
Vol 13 (7) ◽  
pp. 947-952 ◽  
Author(s):  
Luka Svilar ◽  
Julen Castellano ◽  
Igor Jukic ◽  
David Casamichana
Keyword(s):  
Principal Components ◽  
Perceived Exertion ◽  
Principal Component ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Change Of Direction ◽  
External Variables ◽  
Load Monitoring ◽  
External Training ◽  
Almost All

Purpose: To study the structure of interrelationships among external-training-load measures and how these vary among different positions in elite basketball. Methods: Eight external variables of jumping (JUMP), acceleration (ACC), deceleration (DEC), and change of direction (COD) and 2 internal-load variables (rating of perceived exertion [RPE] and session RPE) were collected from 13 professional players with 300 session records. Three playing positions were considered: guards (n = 4), forwards (n = 4), and centers (n = 5). High and total external variables (hJUMP and tJUMP, hACC and tACC, hDEC and tDEC, and hCOD and tCOD) were used for the principal-component analysis. Extraction criteria were set at an eigenvalue of greater than 1. Varimax rotation mode was used to extract multiple principal components. Results: The analysis showed that all positions had 2 or 3 principal components (explaining almost all of the variance), but the configuration of each factor was different: tACC, tDEC, tCOD, and hJUMP for centers; hACC, tACC, tCOD, and hJUMP for guards; and tACC, hDEC, tDEC, hCOD, and tCOD for forwards are specifically demanded in training sessions, and therefore these variables must be prioritized in load monitoring. Furthermore, for all playing positions, RPE and session RPE have high correlation with the total amount of ACC, DEC, and COD. This would suggest that although players perform the same training tasks, the demands of each position can vary. Conclusion: A particular combination of external-load measures is required to describe the training load of each playing position, especially to better understand internal responses among players.

Training Characteristics of Male and Female Professional Road Cyclists: A 4-Year Retrospective Analysis

2020 ◽  
Vol 15 (4) ◽  
pp. 534-540 ◽  
Author(s):  
Teun van Erp ◽  
Dajo Sanders ◽  
Jos J. de Koning
Keyword(s):  
Heart Rate ◽  
Retrospective Analysis ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Intensity ◽  
Male And Female ◽  
Stress Score ◽  
Training Stress ◽  
Training Impulse

Purpose: To describe the training intensity and load characteristics of professional cyclists using a 4-year retrospective analysis. Particularly, this study aimed to describe the differences in training characteristics between men and women professional cyclists. Method: For 4 consecutive years, training data were collected from 20 male and 10 female professional cyclists. From those training sessions, heart rate, rating of perceived exertion, and power output (PO) were analyzed. Training intensity distribution as time spent in different heart rate and PO zones was quantified. Training load was calculated using different metrics such as Training Stress Score, training impulse, and session rating of perceived exertion. Standardized effect size is reported as Cohen’s d. Results: Small to large higher values were observed for distance, duration, kilojoules spent, and (relative) mean PO in men’s training (d = 0.44–1.98). Furthermore, men spent more time in low-intensity zones (ie, zones 1 and 2) compared with women. Trivial differences in training load (ie, Training Stress Score and training impulse) were observed between men’s and women’s training (d = 0.07–0.12). However, load values expressed per kilometer were moderately (d = 0.67–0.76) higher in women compared with men’s training. Conclusions: Substantial differences in training characteristics exist between male and female professional cyclists. Particularly, it seems that female professional cyclists compensate their lower training volume, with a higher training intensity, in comparison with male professional cyclists.

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