The Impact of 3 Different-Length Between-Matches Microcycles on Training Loads in Professional Rugby League Players

2015 ◽  
Vol 10 (6) ◽  
pp. 767-773 ◽  
Author(s):  
Alexandre Moreira ◽  
Tom Kempton ◽  
Marcelo Saldanha Aoki ◽  
Anita C. Sirotic ◽  
Aaron J. Coutts
Keyword(s):  
Perceived Exertion ◽  
Training Session ◽  
Rugby League ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Endurance Athletes ◽  
Moderate Intensity ◽  
High Intensity Zone ◽  
Competition Period ◽  
The Impact

Purpose: To examine the impact of varying between-matches microcycles on training characteristics (ie, intensity, duration, and load) in professional rugby league players and to report on match load related to these between-matches microcycles. Methods: Training-load data were collected during a 26-wk competition period of an entire season. Training load was measured using the session rating of perceived exertion (session-RPE) method for every training session and match from 44 professional rugby league players from the same National Rugby League team. Using the category-ratio 10 RPE scale, the training intensity was divided into 3 zones (low <4 AU, moderate ≥4-≤7 AU, and high >7 AU). Three different-length between-matches recovery microcycles were used for analysis: 5−6 d, 7−8 d, and 9−10 d. Results: A total of 3848 individual sessions were recorded. During the shorter-length between-matches microcycles (5−6 d), significantly lower training load was observed. No significant differences for subsequent match load or intensity were identified between the various match recovery periods. Overall, 16% of the training sessions were completed at the low-intensity zone, 61% at the moderate-intensity zone, and 23% at the high-intensity zone. Conclusions: The findings demonstrate that rugby league players undertake higher training load as the length of between-matches microcycles is increased. The majority of in-season training of professional rugby league players was at moderate intensity, and a polarized approach to training that has been reported in elite endurance athletes does not occur in professional rugby league.

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 Measuring Training Load in Dance: The Construct Validity of Session-RPE

2019 ◽  
Vol 34 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Brenton Surgenor ◽  
Matthew Wyon
Keyword(s):  
Construct Validity ◽  
Convergent Validity ◽  
Perceived Exertion ◽  
Training Session ◽  
Team Sports ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Methods ◽  
Dance Training ◽  
Strong Positive Relationship

OBJECTIVE: The session rating of perceived exertion (session-RPE) is a practical and non-invasive method that allows a quantification of internal training load (ITL) in individual and team sports. As yet, no study has investigated its construct validity in dance. This study examines the convergent validity between the session-RPE method and an objective heart rate (HR)-based method of quantifying the similar ITL in vocational dance students during professional dance training. METHODS: Ten dance students (4 male, 20±1.16 yrs; 6 female, 20±0.52 yrs) participated in this study. During a normal week of training, session-RPE and HR data were recorded in 96 individual sessions. HR data were analysed using Edwards-TL method. Correlation analysis was used to evaluate the convergent validity between the session-RPE and Edwards-TL methods for assessing ITL in a variety of training modes (contemporary, ballet, and rehearsal). RESULTS: The overall correlation between individual session-RPE and Edwards-TL was r=0.72, p<0.0001, suggesting there was a statistically significantly strong positive relationship between session-RPE and Edwards-TL. This trend was observed across all the training modes: rehearsal sessions (r=0.74, p=0.001), contemporary (r=0.60, p=0.001), and ballet (r=0.46, p=0.018) sessions. CONCLUSIONS: This study shows that session-RPE can be considered as a valid method to assess ITL for vocational dance students, and that notably there is some variation between session-RPE and HR-based TL in different dance activities.

Relationship Between Pretraining Subjective Wellness Measures, Player Load, and Rating-of-Perceived-Exertion Training Load in American College Football

2018 ◽  
Vol 13 (1) ◽  
pp. 95-101 ◽  
Author(s):  
Andrew D. Govus ◽  
Aaron Coutts ◽  
Rob Duffield ◽  
Andrew Murray ◽  
Hugh Fullagar
Keyword(s):  
Muscle Soreness ◽  
Perceived Exertion ◽  
Training Session ◽  
College Football ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Football Players ◽  
Unit Increase ◽  
Relationship Of ◽  
The Relationship

Context:The relationship between pretraining subjective wellness and external and internal training load in American college football is unclear.Purpose:To examine the relationship of pretraining subjective wellness (sleep quality, muscle soreness, energy, wellness Z score) with player load and session rating of perceived exertion (s-RPE-TL) in American college football players.Methods:Subjective wellness (measured using 5-point, Likert-scale questionnaires), external load (derived from GPS and accelerometry), and s-RPE-TL were collected during 3 typical training sessions per week for the second half of an American college football season (8 wk). The relationship of pretraining subjective wellness with player load and s-RPE training load was analyzed using linear mixed models with a random intercept for athlete and a random slope for training session. Standardized mean differences (SMDs) denote the effect magnitude.Results:A 1-unit increase in wellnessZscore and energy was associated with trivial 2.3% (90% confidence interval [CI] 0.5, 4.2; SMD 0.12) and 2.6% (90% CI 0.1, 5.2; SMD 0.13) increases in player load, respectively. A 1-unit increase in muscle soreness (players felt less sore) corresponded to a trivial 4.4% (90% CI −8.4, −0.3; SMD −0.05) decrease in s-RPE training load.Conclusion:Measuring pretraining subjective wellness may provide information about players’ capacity to perform in a training session and could be a key determinant of their response to the imposed training demands American college football. Hence, monitoring subjective wellness may aid in the individualization of training prescription in American college football players.

scholarly journals Multiple Measures are Needed to Quantify Training Loads in Professional Rugby League

2017 ◽  
Vol 38 (10) ◽  
pp. 735-740 ◽  
Author(s):  
Daniel Weaving ◽  
Ben Jones ◽  
Phil Marshall ◽  
Kevin Till ◽  
Grant Abt
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
High Speed ◽  
Perceived Exertion ◽  
Principal Component ◽  
Component Analysis ◽  
Rugby League ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Mode

AbstractThis study aims to investigate the effect of training mode (conditioning and skills) on multivariate training load relationships in professional rugby league via principal component analysis. Four measures of training load (internal: heart rate exertion index, session rating of perceived exertion; external: PlayerLoad™, individualised high-speed distance) were collected from 23 professional male rugby league players over the course of one 12 wk preseason period. Training was categorised by mode (skills or conditioning) and then 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 subject to a varimax rotation. Skills extracted 1 principal component, explaining 57% of the variance. Conditioning extracted 2 principal components (1st: internal; 2nd: external), explaining 85% of the variance. The presence of multiple training load dimensions (principal components) during conditioning training provides further evidence of the influence of training mode on the ability of individual measures of external or internal training load to capture training variance. Consequently, a combination of internal and external training-load measures is required during certain training modes.

scholarly journals The Quantification of Within-Week Session Intensity, Duration, and Intensity Distribution Across a Season in Australian Football Using the Session Rating of Perceived Exertion Method

2018 ◽  
Vol 13 (7) ◽  
pp. 940-946 ◽  
Author(s):  
Farhan Juhari ◽  
Dean Ritchie ◽  
Fergus O’Connor ◽  
Nathan Pitchford ◽  
Matthew Weston ◽  
...  
Keyword(s):  
Intensity Distribution ◽  
Mixed Models ◽  
High Intensity ◽  
Perceived Exertion ◽  
Linear Mixed Models ◽  
Training Session ◽  
Rating Of Perceived Exertion ◽  
Moderate Intensity ◽  
Low Intensity ◽  
Australian Football

Context: Team-sport training requires the daily manipulation of intensity, duration, and frequency, with preseason training focusing on meeting the demands of in-season competition and training on maintaining fitness. Purpose: To provide information about daily training in Australian football (AF), this study aimed to quantify session intensity, duration, and intensity distribution across different stages of an entire season. Methods: Intensity (session ratings of perceived exertion; CR-10 scale) and duration were collected from 45 professional male AF players for every training session and game. Each session’s rating of perceived exertion was categorized into a corresponding intensity zone, low (<4.0 arbitrary units), moderate (≥4.0 and <7.0), and high (≥7.0), to categorize session intensity. Linear mixed models were constructed to estimate session duration, intensity, and distribution between the 3 preseason and 4 in-season periods. Effects were assessed using linear mixed models and magnitude-based inferences. Results: The distribution of the mean session intensity across the season was 29% low intensity, 57% moderate intensity, and 14% high intensity. While 96% of games were high intensity, 44% and 49% of skills training sessions were low intensity and moderate intensity, respectively. Running had the highest proportion of high-intensity training sessions (27%). Preseason displayed higher training-session intensity (effect size [ES] = 0.29–0.91) and duration (ES = 0.33–1.44), while in-season game intensity (ES = 0.31–0.51) and duration (ES = 0.51–0.82) were higher. Conclusions: By using a cost-effective monitoring tool, this study provides information about the intensity, duration, and intensity distribution of all training types across different phases of a season, thus allowing a greater understanding of the training and competition demands of Australian footballers.

scholarly journals Intradialytic cycling does not exacerbate microparticles or circulating markers of systemic inflammation in haemodialysis patients

2021 ◽  
Author(s):  
Patrick J. Highton ◽  
Daniel S. March ◽  
Darren R. Churchward ◽  
Charlotte E. Grantham ◽  
Hannah M. L. Young ◽  
...  
Keyword(s):  
Systemic Inflammation ◽  
Perceived Exertion ◽  
Venous Blood ◽  
Rating Of Perceived Exertion ◽  
Moderate Intensity ◽  
Inflammatory Status ◽  
Intensity Rating ◽  
Circulating Markers ◽  
Post Hoc ◽  
The Impact

Abstract Purpose Patients receiving haemodialysis (HD) display elevated circulating microparticle (MP) concentration, tissue factor (TF) expression and markers of systemic inflammation, though regular intradialytic cycling (IDC) may have a therapeutic effect. This study investigated the impact of regular, moderate-intensity IDC on circulating MPs and inflammatory markers in unit-based HD patients. Methods Patients were cluster-randomised to intervention (n = 20, age: 51.4 ± 18.1 years, body mass: 77.6 ± 18.3 kg, mean ± SD) or no-exercise control (n = 20, 56.8 ± 14.0 years, 80.5 ± 26.5 kg). Intervention participants completed 30 min of moderate intensity (rating of perceived exertion [RPE] of 12–14) IDC, thrice weekly for 6 months. Pre-dialysis venous blood samples were obtained at 0, 3 and 6 months. Circulating MP phenotypes, cytokines, chemokine and MP TF expression were quantified using flow cytometry and cytometric bead array assays. Results Despite high exercise compliance (82%), no IDC-dependent effects were observed for any MP, cytokine or chemokine measure (p ≥ 0.051, ηρ2 ≤ 0.399) other than TNF-α (p = 0.001, ηρ2 = 0.186), though no significance was revealed upon post hoc analysis. Conclusion Six months of regular, moderate-intensity IDC had no effect on MPs, cytokines or chemokines. This suggests that the exercise did not exacerbate thrombotic or inflammatory status, though further functional assays are required to confirm this. Trial registration ISRCTN1129707, prospectively registered on 05/03/2015.

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.

25 Years of Session Rating of Perceived Exertion: Historical Perspective and Development

2020 ◽  
pp. 1-10 ◽  
Author(s):  
Carl Foster ◽  
Daniel Boullosa ◽  
Michael McGuigan ◽  
Andrea Fusco ◽  
Cristina Cortis ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Lactate Concentration ◽  
Training Session ◽  
Blood Lactate Concentration ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Exercise Session ◽  
Training Outcomes ◽  
External Training ◽  
Training Impulse

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.

Training Periodization of Professional Australian Football Players During an Entire Australian Football League Season

2015 ◽  
Vol 10 (5) ◽  
pp. 566-571 ◽  
Author(s):  
Alexandre Moreira ◽  
Johann C. Bilsborough ◽  
Courtney J. Sullivan ◽  
Michael Cianciosi ◽  
Marcelo Saldanha Aoki ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Training Session ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Football Players ◽  
Training Intensity ◽  
Australian Football League ◽  
Football Team ◽  
Cross Training ◽  
Australian Football

Purpose:To examine the training periodization of an elite Australian Football team during different phases of the season.Methods:Training-load data were collected during 22 wk of preseason and 23 wk of in-season training. Training load was measured using the session rating of perceived exertion (session-RPE) for all training sessions and matches from 44 professional Australian Football players from the same team. Training intensity was divided into 3 zones based on session-RPE (low, <4; moderate, >4 AU and <7 AU; and high, >7 AU). Training load and intensity were analyzed according to the type of training session completed.Results:Higher training load and session duration were undertaken for all types of training sessions during the preseason than in-season (P < .05), with the exception of “other” training (ie, re/prehabilitation training, cross-training, and recovery activities). Training load and intensity were higher during the preseason, with the exception of games, where greater load and intensity were observed during the in-season. The overall distribution of training intensity was similar between phases with the majority of training performed at moderate or high intensity.Conclusions:The current findings may allow coaches and scientists to better understand the characteristics of Australian Football periodization, which in turn may aid in developing optimal training programs. The results also indicate that a polarized training-intensity distribution that has been reported in elite endurance athletes does not occur in professional Australian Football.

Importance of Various Training-Load Measures in Injury Incidence of Professional Rugby League Athletes

2017 ◽  
Vol 12 (6) ◽  
pp. 819-824 ◽  
Author(s):  
Heidi R. Thornton ◽  
Jace A. Delaney ◽  
Grant M. Duthie ◽  
Ben J. Dascombe
Keyword(s):  
Risk Factors ◽  
High Speed ◽  
Injury Risk ◽  
Perceived Exertion ◽  
Rugby League ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Machine Learning Techniques ◽  
Injury Incidence ◽  
The Individual

Purpose:To investigate the ability of various internal and external training-load (TL) monitoring measures to predict injury incidence among positional groups in professional rugby league athletes.Methods:TL and injury data were collected across 3 seasons (2013–2015) from 25 players competing in National Rugby League competition. Daily TL data were included in the analysis, including session rating of perceived exertion (sRPE-TL), total distance (TD), high-speed-running distance (>5 m/s), and high-metabolic-power distance (HPD; >20 W/kg). Rolling sums were calculated, nontraining days were removed, and athletes’ corresponding injury status was marked as “available” or “unavailable.” Linear (generalized estimating equations) and nonlinear (random forest; RF) statistical methods were adopted.Results:Injury risk factors varied according to positional group. For adjustables, the TL variables associated most highly with injury were 7-d TD and 7-d HPD, whereas for hit-up forwards they were sRPE-TL ratio and 14-d TD. For outside backs, 21- and 28-d sRPE-TL were identified, and for wide-running forwards, sRPE-TL ratio. The individual RF models showed that the importance of the TL variables in injury incidence varied between athletes.Conclusions:Differences in risk factors were recognized between positional groups and individual athletes, likely due to varied physiological capacities and physical demands. Furthermore, these results suggest that robust machine-learning techniques can appropriately monitor injury risk in professional team-sport athletes.

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