scholarly journals The tracking of internal and external training loads with next-day player-reported fatigue at different times of the season in elite soccer players

2021 ◽  
pp. 174795412198896
Author(s):  
Garrison Draper ◽  
Matthew Wright ◽  
Paul Chesterton ◽  
Greg Atkinson
Keyword(s):  
Global Positioning System ◽  
Perceived Exertion ◽  
Longitudinal Research ◽  
Principal Component ◽  
Training Load ◽  
Ratings Of Perceived Exertion ◽  
Global Positioning ◽  
Within Subjects ◽  
External Training ◽  
Psychological Mood

The aim was to assess factor structure of player-reported fatigue and quantify within-subjects association between changes in training load measures and next day player-reported fatigue at different time points of an elite football season. Using longitudinal research design, twenty-four professional footballers, mean (SD) age of 25.7 (3.4) years, were monitored during their competitive season, including pre-season. Player-reported fatigue data and session ratings of perceived exertion (session-RPE) were collected via a mobile application. Player’s Heart rate (HR) and global positioning system (GPS) data were collected daily for each player in field sessions. Principal component analysis (PCA) indicated three components with Eigenvalues above 1.0; “soreness”, “mood, and “hydration”. Within-player correlations between training load values and next day player-reported fatigue values were trivial to moderate (r ≈ −0.42 to −0.04). In-season we observed large correlations between Total Distance (TD) and PlayerLoad with Soreness (r = −0.55, 95% CI: −0.62 to −0.46; r = −.054, 95% CI: −0.62 to −0.46), but during pre-season, correlations were small (r = −0.15, 95% CI: −0.28 to −0.01; r = −0.13, 95% CI: −0.26 to 0.01). The HR TRIMP, TD and session-RPE measures each showed trivial to moderate correlations (r ≈ −0.41 to −0.08) with next day “mood”. Our in-house player-reported fatigue questionnaire was sensitive to the multi-dimensional nature of fatigue, identifying physiological (soreness), psychological (mood and stress) and nutritional (hydration and nutrition) components. We found the in-season correlations with training load to be greater than previously reported in the literature, specifically with next day player-reported “soreness”. Nevertheless, the correlations between the items of our scale and pre-season training load were small.

An Evaluation of Training Load Measures for Drills in Women’s Collegiate Lacrosse

2020 ◽  
pp. 1-8
Author(s):  
Jennifer A. Bunn ◽  
Bradley J. Myers ◽  
Mary K. Reagor
Keyword(s):  
Global Positioning System ◽  
External Load ◽  
Principal Component ◽  
Training Load ◽  
Division I ◽  
Heart Rate Monitor ◽  
Global Positioning ◽  
Different Types ◽  
External Training ◽  
Evaluation Of Training

Purpose: To statistically evaluate the internal and external load metrics in different types of lacrosse drills. Methods: A total of 25 Division I collegiate female lacrosse players wore a heart rate monitor and a global positioning system during preseason training sessions. Seven measures determined training load, 2 internal measures and 5 external measures, across 5 different types of drills: stickwork, small-sided games, individual skills, conditioning, and team drills. Principal component analysis was used to determine which internal and external load variables were most associated with each drill type. Results: Stickwork extracted 2 principal components, explaining 45% and 17% of the variance. Small-sided games extracted 1 principal component, explaining 51% of the variance. Individual skills extracted 2 components, explaining 39% and 22% of the variance. Conditioning extracted 2 components, explaining 44% and 24% of the variance. Team drills extracted 2 components, explaining 52% and 18% of the variance. Conclusions: In 4 out of 5 training modes, the inclusion of both internal and external training-load measures was necessary to accurately decipher training load. For most drills, the first component is related to measures of external load, and the second component described the balance between internal and external load measures. Small-sided games extracted only external measures including the following: accelerations, total distance, and average speed. These results show that a combination of internal and external load measures is required to determine training load during certain training modes. This information can help coaches make decisions about desired training load for practice sessions.

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.

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.

scholarly journals Combining Internal- and External-Training-Load Measures in Professional Rugby League

2014 ◽  
Vol 9 (6) ◽  
pp. 905-912 ◽  
Author(s):  
Dan Weaving ◽  
Phil Marshall ◽  
Keith Earle ◽  
Alan Nevill ◽  
Grant Abt
Keyword(s):  
Principal Components ◽  
High Speed ◽  
Perceived Exertion ◽  
Principal Component ◽  
Rugby League ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Dose ◽  
External Training ◽  
Training Impulse

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.

scholarly journals Relationship Between Subjective and External Training Load Variables in Youth Soccer Players

2020 ◽  
pp. 1-7
Author(s):  
Patrick C. Maughan ◽  
Niall G. MacFarlane ◽  
Paul A. Swinton
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Perceived Exertion ◽  
Principal Component ◽  
Component Analysis ◽  
Training Load ◽  
Soccer Players ◽  
Youth Soccer ◽  
Depth Analysis ◽  
External Training

Purpose: To quantify and describe relationships between subjective and external measures of training load in professional youth soccer players. Methods: Data from differential ratings of perceived exertion (dRPE) and 7 measures of external training load were collected from 20 professional youth soccer players over a 46-week season. Relationships were described by repeated-measures correlation, principal component analysis, and factor analysis with oblimin rotation. Results: Significant positive (.44 ≤ r ≤ .99; P < .001) within-individual correlations were obtained across dRPE and all external training load measures. Correlation magnitudes were found to decrease when training load variables were expressed per minute. Principal component analysis provided 2 components, which described 83.3% of variance. The first component, which described 72.9% of variance, was heavily loaded by all measures of training load, while the second component, which described 10.4% of the variance, appeared to have a split between objective and subjective measures of volume and intensity. Exploratory factor analysis identified 4 theoretical factors, with correlations between factors ranging from .5 to .8. These factors could be theoretically described as objective volume, subjective volume, objective running, and objective high-intensity measures. Removing dRPE measures from the analysis altered the structure of the model, providing a 3-factor solution. Conclusions: The dRPE measures are significantly correlated with a range of external training load measures and with each other. More in-depth analysis showed that dRPE measures were highly related to each other, suggesting that, in this population, they would provide practitioners with similar information. Further analysis provided characteristic groupings of variables.

The Reliability of a Rugby League Movement-Simulation Protocol Designed to Replicate the Performance of Interchanged Players

2013 ◽  
Vol 8 (5) ◽  
pp. 483-489 ◽  
Author(s):  
Mark Waldron ◽  
Jamie Highton ◽  
Craig Twist
Keyword(s):  
Global Positioning System ◽  
Perceived Exertion ◽  
Lactate Concentration ◽  
Blood Lactate Concentration ◽  
Rugby League ◽  
Moderate Intensity ◽  
Ratings Of Perceived Exertion ◽  
Global Positioning ◽  
Simulation Protocol ◽  
Movement Simulation

Purpose:This study assessed the reliability of a rugby league movement-simulation protocol, relative to interchanged players (RLMSP-i).Methods:Fifteen male participants completed 2 trials of the RLMSP-i, separated by 1 wk. The RLMSP-i comprised low- to moderate-intensity running, interspersed by high-intensity sprinting and tackling activity, based on global positioning system (GPS) data recorded during Super League performances.Results:The lowest coefficient of variation (CV ± 95% CI) was observed for total m/min during both interchange bout 1 (1.1% ± 0.2%) and bout 2 (1.0% ± 0.2%). The percentage of heart rate peak and ratings of perceived exertion demonstrated CVs of 1.2–2.0% and 2.9–3.5%, respectively. The poorest agreement between trials was found for blood lactate concentration (16.2% ± 2.8%). In no case was the CV smaller than the smallest worthwhile change, yet in every case the moderate changes were larger than the CV.Conclusions:The RLMSP-i’s reliability is sufficient to enable the detection of moderate changes in various performance and physiological measurements that accurately simulate some, but not all, aspects of rugby league matches.

Seasonal Training Load and Wellness Monitoring in a Professional Soccer Goalkeeper

2018 ◽  
Vol 13 (5) ◽  
pp. 672-675 ◽  
Author(s):  
James J. Malone ◽  
Arne Jaspers ◽  
Werner Helsen ◽  
Brenda Merks ◽  
Wouter G.P. Frencken ◽  
...  
Keyword(s):  
Global Positioning System ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Total Distance ◽  
Professional Soccer ◽  
Competitive Season ◽  
Global Positioning ◽  
The Relationship

The purpose of this investigation was to (1) quantify the training load practices of a professional soccer goalkeeper and (2) investigate the relationship between the training load observed and the subsequent self-reported wellness response. One male goalkeeper playing for a team in the top league of the Netherlands participated in this case study. Training load data were collected across a full season using a global positioning system device and session-RPE (rating of perceived exertion). Data were assessed in relation to the number of days to a match (MD− and MD+). In addition, self-reported wellness response was assessed using a questionnaire. Duration, total distance, average speed, PlayerLoad™, and load (derived from session-RPE) were highest on MD. The lowest values for duration, total distance, and PlayerLoad™ were observed on MD−1 and MD+1. Total wellness scores were highest on MD and MD−3 and were lowest on MD+1 and MD−4. Small to moderate correlations between training load measures (duration, total distance covered, high deceleration efforts, and load) and the self-reported wellness response scores were found. This exploratory case study provides novel data about the physical load undertaken by a goalkeeper during 1 competitive season. The data suggest that there are small to moderate relationships between training load indicators and self-reported wellness response. This weak relation indicates that the association is not meaningful. This may be due to the lack of position-specific training load parameters that practitioners can currently measure in the applied context.

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 Relationships Between Different Internal and External Training Load Variables and Elite International Women’s Basketball Performance

2020 ◽  
pp. 1-10
Author(s):  
Joseph O.C. Coyne ◽  
Aaron J. Coutts ◽  
Robert U. Newton ◽  
G. Gregory Haff
Keyword(s):  
Perceived Exertion ◽  
Efficiency Index ◽  
Training Load ◽  
Ratings Of Perceived Exertion ◽  
Basketball Players ◽  
Smoothing Methods ◽  
Women's Basketball ◽  
External Training ◽  
Training Stress ◽  
Training Efficiency

Purpose: To investigate the relationships between internal and external training load (TL) metrics with elite international women’s basketball performance. Methods: Sessional ratings of perceived exertion, PlayerLoad™/minute, and training duration were collected from 13 elite international-level female basketball athletes (age 29.0 [3.7] y, stature 186.0 [9.8] cm, body mass 77.9 [11.6] kg) during the 18 weeks prior to the International Basketball Federation Olympic qualifying event for the 2016 Rio Olympic Games. Training stress balance, differential load, and the training efficiency index were calculated with 3 different smoothing methods. These TL metrics and their change in the last 21 days prior to competition were examined for their relationship to competition performance as coach ratings of performance. Results: For a number of TL variables, there were consistent significant small to moderate correlations with performance and significant small to large differences between successful and unsuccessful performances. However, these differences were only evident for external TL when using exponentially weighted moving averages to calculate TL. The variable that seemed most sensitive to performance was the change in training efficiency index in the last 21 days prior to competition (performance r = .47–.56, P < .001 and difference between successful and unsuccessful performance P < .001, f2 = 0.305–0.431). Conclusions: Internal and external TL variables were correlated with performance and distinguished between successful and unsuccessful performances among the same players during international women’s basketball games. Manipulating TL in the last 3 weeks prior to competition may be worthwhile for basketball players’ performance, especially in internal TL.

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.

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