scholarly journals Quantifying Sub-Elite Youth Football Weekly Training Load and Recovery Variation

2021 ◽  
Vol 11 (11) ◽  
pp. 4871
Author(s):  
José E. Teixeira ◽  
Pedro Forte ◽  
Ricardo Ferraz ◽  
Miguel Leal ◽  
Joana Ribeiro ◽  
...  

Monitoring the training load in football is an important strategy to improve athletic performance and an effective training periodization. The aim of this study was two-fold: (1) to quantify the weekly training load and recovery status variations performed by under-15, under-17 and under-19 sub-elite young football players; and (2) to analyze the influence of age, training day, weekly microcycle, training and playing position on the training load and recovery status. Twenty under-15, twenty under-17 and twenty under-19 players were monitored over a 2-week period during the first month of the 2019–2020 competitive season. Global positioning system technology (GPS) was used to collect external training loads: total distance covered, average speed, maximal running speed, relative high-speed running distance, high metabolic load distance, sprinting distance, dynamic stress load, accelerations and decelerations. Internal training load was monitored using ratings of perceived exertion (RPE) and session rating of perceived exertion (sRPE). Recovery status was obtained using the total quality recovery (TQR) scale. The results show an age-related influence for external training load (p ≤ 0.001; d = 0.29–0.86; moderate to strong effect), internal training load (p ≤ 0.001, d = 0.12–0.69; minimum to strong effect) and recovery status (p ≤ 0.001, d = 0.59; strong effect). The external training load presented differences between training days (p < 0.05, d = 0.26–0.95; moderate to strong effect). The playing position had a minimum effect on the weekly training load (p < 0.05; d = 0.06–0.18). The weekly microcycle had a moderate effect in the TD (p < 0.05, d = 0.39), RPE (p < 0.05; d = 0.35) and sRPE (p < 0.05, d = 0.35). Interaction effects were found between the four factors analyzed for deceleration (F = 2.819, p = 0.017) and between inter-day, inter-week and age for total covered distance (F = 8.342, p = 0.008). This study provided specific insights about sub-elite youth football training load and recovery status to monitor training environments and load variations. Future research should include a longer monitoring period to assess training load and recovery variations across different season phases.

2020 ◽  
Vol 26 (2) ◽  
pp. 158-161
Author(s):  
Thiago Andrade Goulart Horta ◽  
Pedro Henrique Prazeres de Lima ◽  
Guilherme Garcia Matta ◽  
Jefferson Verbena de Freitas ◽  
Bernardo Miloski Dias ◽  
...  

ABSTRACT Introduction: The success of training depends on the balance between training load magnitude and recovery. Objective: Verify the effect of training load distribution on recovery status, vigor and fatigue in volleyball players during a season. Methods: Nine male athletes from a professional volleyball team participated in the study. During 19 weeks of the season, quantification of the training load was performed through the session rating of perceived exertion (RPE) method, evaluation of the athletes' recovery status through the Total Quality Recovery (TQR) scale, and evaluation of the profile of mood state through the POMS questionnaire, with research focus for the subscales vigor and fatigue. Results: The average total weekly training load (TWTL) was 3206 ± 685.5 A. Us and the average recovery of the whole season was 15.3 ± 0.57. The mean values of fatigue and vigor were 11 ± 3.05 and 19.4 ± 2.84, respectively. Significant differences were found for the variables RPE, fatigue and Energy Index (Vigor - Fatigue) in the three different periods of the season (Preparatory Period, Competitive Period I and Competitive Period II). Conclusion: It was concluded that the training load and recovery monitoring methods used throughout the season were effective in controlling the variables, with a positive impact of training loads verified on the recovery values presented by the athletes. Level of Evidence III; Diagnostic study.


Author(s):  
Sullivan Coppalle ◽  
Guillaume Ravé ◽  
Jason Moran ◽  
Iyed Salhi ◽  
Abderraouf Ben Abderrahman ◽  
...  

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.


2019 ◽  
Vol 14 (6) ◽  
pp. 847-849 ◽  
Author(s):  
Pedro Figueiredo ◽  
George P. Nassis ◽  
João Brito

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.


2018 ◽  
Vol 13 (7) ◽  
pp. 947-952 ◽  
Author(s):  
Luka Svilar ◽  
Julen Castellano ◽  
Igor Jukic ◽  
David Casamichana

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.


2017 ◽  
Vol 12 (2) ◽  
pp. 247-253 ◽  
Author(s):  
Will Vickery ◽  
Ben Dascombe ◽  
Rob Duffield

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.


2018 ◽  
Author(s):  
Rafael Soares Oliveira ◽  
João Paulo Brito ◽  
Alexandre Martins ◽  
Bruno Mendes ◽  
Francisco Calvete ◽  
...  

Elite soccer teams that participate in European competitions often have a difficult schedule, involving weeks in which they play up to three matches, which leads to acute and transient subjective, biochemical, metabolic and physical disturbances in players over the subsequent hours and days. Inadequate time recovery between matches can expose players to the risk of training and competing whilst not fully recovered. Controlling the level of effort and fatigue of players to reach higher performances during the matches is therefore critical. Therefore, the aim of the current study was to provide the first report of seasonal internal and external training load (TL) that included Hooper Index (HI) scores in elite soccer players during an in-season period. Sixteen elite soccer players were sampled, using global position system, session rating of perceived exertion (s-RPE) and HI scores during the daily training sessions throughout the 2015-2016 in-season period. Data were analysed across ten mesocycles (M: 1 to 10) and collected according to the number of days prior to a match. Total daily distance covered was higher at the start (M1 and M3) compared to the final mesocycle (M10) of the season. M1 (5589m) reached a greater distance than M5 (4473m) (ES = 9.33 [12.70, 5.95]) and M10 (4545m) (ES = 9.84 [13.39, 6.29]). M3 (5691m) reached a greater distance than M5 (ES = 9.07 [12.36, 5.78]), M7 (ES = 6.13 [8.48, 3.79]) and M10 (ES = 9.37 [12.76, 5.98]). High-speed running distance was greater in M1 (227m), than M5 (92m) (ES = 27.95 [37.68, 18.22]) and M10 (138m) (ES = 8.46 [11.55, 5.37]). Interestingly, the s-RPE response was higher in M1 (331au) in comparison to the last mesocycle (M10, 239au). HI showed minor variations across mesocycles and in days prior to the match. Every day prior to a match, all internal and external TL variables expressed significant lower values to other days prior to a match (p<0.01). In general, there were no differences between player positions. Conclusions: Our results reveal that despite the existence of some significant differences between mesocycles, there were minor changes across the in-season period for the internal and external TL variables used. Furthermore, it was observed that MD-1 presented a reduction of external TL (regardless of mesocycle) while internal TL variables did not have the same record during in-season match-day-minus.


2014 ◽  
Vol 9 (6) ◽  
pp. 905-912 ◽  
Author(s):  
Dan Weaving ◽  
Phil Marshall ◽  
Keith Earle ◽  
Alan Nevill ◽  
Grant Abt

Purpose:This study investigated the effect of training mode on the relationships between measures of training load in professional rugby league players.Methods:Five measures of training load (internal: individualized training impulse, session rating of perceived exertion; external—body load, high-speed distance, total impacts) were collected from 17 professional male rugby league players over the course of two 12-wk preseason periods. Training was categorized by mode (small-sided games, conditioning, skills, speed, strongman, and wrestle) and subsequently subjected to a principal-component analysis. Extraction criteria were set at an eigenvalue of greater than 1. Modes that extracted more than 1 principal component were subjected to a varimax rotation.Results:Small-sided games and conditioning extracted 1 principal component, explaining 68% and 52% of the variance, respectively. Skills, wrestle, strongman, and speed extracted 2 principal components each explaining 68%, 71%, 72%, and 67% of the variance, respectively.Conclusions:In certain training modes the inclusion of both internal and external training-load measures explained a greater proportion of the variance than any 1 individual measure. This would suggest that in training modes where 2 principal components were identified, the use of only a single internal or external training-load measure could potentially lead to an underestimation of the training dose. Consequently, a combination of internal- and external-load measures is required during certain training modes.


Author(s):  
Carl Foster ◽  
Daniel Boullosa ◽  
Michael McGuigan ◽  
Andrea Fusco ◽  
Cristina Cortis ◽  
...  

The session rating of perceived exertion (sRPE) method was developed 25 years ago as a modification of the Borg concept of rating of perceived exertion (RPE), designed to estimate the intensity of an entire training session. It appears to be well accepted as a marker of the internal training load. Early studies demonstrated that sRPE correlated well with objective measures of internal training load, such as the percentage of heart rate reserve and blood lactate concentration. It has been shown to be useful in a wide variety of exercise activities ranging from aerobic to resistance to games. It has also been shown to be useful in populations ranging from patients to elite athletes. The sRPE is a reasonable measure of the average RPE acquired across an exercise session. Originally designed to be acquired ∼30 minutes after a training bout to prevent the terminal elements of an exercise session from unduly influencing the rating, sRPE has been shown to be temporally robust across periods ranging from 1 minute to 14 days following an exercise session. Within the training impulse concept, sRPE, or other indices derived from sRPE, has been shown to be able to account for both positive and negative training outcomes and has contributed to our understanding of how training is periodized to optimize training outcomes and to understand maladaptations such as overtraining syndrome. The sRPE as a method of monitoring training has the advantage of extreme simplicity. While it is not ideal for the precise recording of the details of the external training load, it has large advantages relative to evaluating the internal training load.


2021 ◽  
pp. 1-7
Author(s):  
Frederico Ribeiro Neto ◽  
Ramires Alsamir Tibana ◽  
Jefferson Rodrigues Dorneles ◽  
Rodrigo Rodrigues Gomes Costa

Context: Paracanoeing is one of the adapted sports eligible for different motor impairments. The acute:chronic workload ratio (ACWR) is an index between acute and chronic training workload. However, no studies have analyzed this variable in paracanoeing, relating it with training recovery markers. Objective: This study aimed to quantify the internal (session rating of perceived exertion) and external (distance traveled and total training time) training workloads in 4 experienced paracanoe athletes over 9 months and 5 canoeing events. Design: Cross-sectional study. Setting: Rehabilitation Hospital Network, Paralympic Program. Participants: Four experienced paracanoe athletes participated in 36 weeks of training for 5 events. Main Outcomes Measures: The daily and weekly training workload, monotony, ACWR, distance, and total training time were described for all the training phases. The perceived recovery status scale (PRS) and medicine ball throw (MBT) were used to quantify recovery. Results: The average daily and weekly training workload varied from 213.1 to 239.3 and 767.3 to 1036.8 arbitrary units, respectively. Average ACWR results ranged from 0.96 to 1.10 in the 4 athletes, findings that were outside the safety zone in 38% of the training weeks. All the correlations between MBT and PRS were classified as weak (ρ between .20 and .39, P > .05). ACWR showed a very weak correlation with MBT and moderately and highly significant correlations with PRS in 2 athletes, respectively. Conclusions: The training workloads of 4 paracanoe athletes may serve as a comparison with other periodization models. Pretraining recovery assessments (MBT and PRS) exhibited a low, nonsignificant correlation. However, ACWR correlated significantly with PRS in 2 athletes and might be a suitable tool for daily training adjustments.


2018 ◽  
Vol 13 (9) ◽  
pp. 1182-1189 ◽  
Author(s):  
Paula B. Debien ◽  
Marcelly Mancini ◽  
Danilo R. Coimbra ◽  
Daniel G.S. de Freitas ◽  
Renato Miranda ◽  
...  

Purpose: To describe and analyze the distribution of internal training load (ITL), recovery, and physical performance of professional volleyball players throughout 1 season. Methods: Fifteen male professional Brazilian volleyball players participated in this study. The session rating of perceived exertion (s-RPE) and Total Quality Recovery (TQR) score were collected daily for 36 wk. s-RPE was collected after each training session, and TQR, before the first session of the day. The sum of the ITL of each session during the week, training monotony, strain, acute∶chronic workload ratio, match difficulty score, and average of the TQR scores were recorded for the analysis. In addition, the athletes performed countermovement-jump (CMJ) tests with and without the use of the arms 4 times over the season. Results: The season mean weekly ITL was 3733 (1228) AU and the TQR was 15.02 (0.71). The ITL and recovery demonstrated undulating dynamics over the 36 wk, with higher weekly ITL in the preparatory periods (F = 50.32; P < .001) and worse recovery during the main competition (F = 6.47; P = .004). Negative correlations were found between TQR and ITL variables (P < .05). There was improvement and maintenance in CMJ tests without (F = 11.88; P < .001) and with (F = 16.02; P < .001) the use of the arms after the preparatory periods. Conclusions: The ITL variables, recovery, and physical performance changed significantly throughout a professional volleyball season. Despite the decrease in ITL during the main competitive period, the correct distribution of weekly ITL seems to be very important to guarantee the best recovery of athletes.


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