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.

A Prospective Cohort Study of Load and Wellness (Sleep, Fatigue, Soreness, Stress, and Mood) in Elite Junior Australian Football Players

2019 ◽  
Vol 14 (6) ◽  
pp. 829-840 ◽  
Author(s):  
Timothy J.H. Lathlean ◽  
Paul B. Gastin ◽  
Stuart V. Newstead ◽  
Caroline F. Finch
Keyword(s):  
Cohort Study ◽  
Confidence Interval ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Perceived Exertion ◽  
Training Session ◽  
Load Ratio ◽  
Rating Of Perceived Exertion ◽  
Football Players ◽  
Australian Football

Purpose:To investigate associations between load (training and competition) and wellness in elite junior Australian Football players across 1 competitive season.Methods:A prospective cohort study was conducted during the 2014 playing season in 562 players from 9 teams. Players recorded their training and match intensities according to the session-rating-of-perceived-exertion (sRPE) method. Based on sRPE player loads, a number of load variables were quantified, including cumulative load and the change in load across different periods of time (including the acute-to-chronic load ratio). Wellness was quantified using a wellness index including sleep, fatigue, soreness, stress, and mood on a Likert scale from 1 to 5.Results:Players spent an average of 85 (21) min in each match and 65 (31) min per training session. Average match loads were 637 (232) arbitrary units, and average training loads were 352 (233) arbitrary units. Over the 24 wk of the 2014 season, overall wellness had a significant linear negative association with 1-wk load (B = −0.152; 95% confidence interval, −0.261 to −0.043;P = .006) and an inverseU-curve relationship with session load (B = −0.078; 95% confidence interval, 0.143 to 0.014;P = .018). Mood, stress, and soreness were all found to have associations with load.Conclusions:This study demonstrates that load (within a session and across the week) is important in managing the wellness of elite junior Australian Football players. Quantifying loads and wellness at this level will help optimize player management and has the potential to reduce the risk of adverse events such as injury.

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 Relationship between External Load and Perceptual Responses to Training in Professional Football: Effects of Quantification Method

Sports ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 68 ◽  
Author(s):  
Vincenzo Rago ◽  
João Brito ◽  
Pedro Figueiredo ◽  
Peter Krustrup ◽  
António Rebelo
Keyword(s):  
High Speed ◽  
Perceived Exertion ◽  
Training Session ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Quantification Method ◽  
Individual Fitness ◽  
Football Team ◽  
Maximal Aerobic Speed ◽  
Sprinting Speed

We examined the within-player correlation between external training load (ETL) and perceptual responses to training in a professional male football team (n = 13 outfield players) over an eight-week competitive period. ETL was collected using 10-Hz GPS, whereas perceptual responses were accessed through rating of perceived exertion (RPE) questionnaires. Moderate-speed running (MSR), high-speed running (HSR) and sprinting were defined using arbitrary (fixed) and individualised speed zones (based on maximal aerobic speed and maximal sprinting speed). When ETL was expressed as actual distance covered within the training session, perceptual responses were moderately correlated to MSR and HSR quantified using the arbitrary method (p < 0.05; r = 0.53 to 0.59). However, the magnitude of correlations tended to increase when the individualised method was used (p < 0.05; r = 0.58 to 0.67). Distance covered by sprinting was moderately correlated to perceptual responses only when the individualised method was used (p < 0.05; 0.55 [0.05; 0.83] and 0.53 [0.02; 0.82]). Perceptual responses were largely correlated to the sum of distance covered within all three speed running zones, irrespective of the quantification method (p < 0.05; r = 0.58 to 0.68). When ETL was expressed as percentage of total distance covered within the training session, no significant correlations were observed (p > 0.05). Perceptual responses to training load seem to be better associated with ETL, when the latter is adjusted to individual fitness capacities. Moreover, reporting ETL as actual values of distance covered within the training session instead of percentual values inform better about players’ perceptual responses to training load.

Perceived Exertion in Coaches and Young Swimmers With Different Training Experience

2014 ◽  
Vol 9 (2) ◽  
pp. 212-216 ◽  
Author(s):  
Renato Barroso ◽  
Ronaldo K. Cardoso ◽  
Everton Crivoi Carmo ◽  
Valmor Tricoli
Keyword(s):  
Perceived Exertion ◽  
Age Groups ◽  
Training Session ◽  
Practical Method ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Intensity ◽  
Training Experience ◽  
Competitive Swimming ◽  
Performance Development

Session rating of perceived exertion (SRPE) is a practical method to assess internal training load to provide appropriate stimuli. However, coaches and athletes might rate training sessions differently, which can impair performance development. In addition, SRPE might be influenced by athletes’ training experience. The authors studied 160 swimmers of different age groups and different competitive swimming experience and 9 coaches. SRPE was indicated by the swimmers 30 min after the end of a training session and before the training session by the coaches. Training-session intensities were classified into easy (SRPE <3), moderate (SRPE 3–5), and difficult (SRPE >5), based on coaches’ perception. We observed that the correlation between coaches’ and athletes’ SRPE increased with increased age and competitive swimming experience, r = .31 for the 11- to 12-y-old group (P < .001), r = .51 for the 13- to 14-y-old group (P < .001), and r = .74 for the 15- to 16-y-old group (P < .001). In addition, younger swimmers (11–12 y, P < .01; 13–14 y, P < .01) rated training intensity differently from coaches in all 3 categories (easy, moderate, and difficult), while the older group rated differently in only 1 category (difficult, P < .01). These findings suggest that the more experienced swimmers are, the more accurate their SRPE is.

scholarly journals Association Between Preseason Training and Performance in Elite Australian Football

2019 ◽  
Vol 14 (1) ◽  
pp. 68-75 ◽  
Author(s):  
Callum J. McCaskie ◽  
Warren B. Young ◽  
Brendan B. Fahrner ◽  
Marc Sim
Keyword(s):  
Performance Measures ◽  
Perceived Exertion ◽  
Performance Measure ◽  
Rating Of Perceived Exertion ◽  
Training Data ◽  
Internal Load ◽  
Australian Football League ◽  
Football Team ◽  
Australian Football ◽  
And Performance

Purpose: To examine the association between preseason training variables and subsequent in-season performance in an elite Australian football team. Methods: Data from 41 elite male Australian footballers (mean [SD] age = 23.4 [3.1] y, height =188.4 [7.1] cm, and mass = 86.7 [7.9] kg) were collected from 1 Australian Football League (AFL) club. Preseason training data (external load, internal load, fitness testing, and session participation) were collected across the 17-wk preseason phase (6 and 11 wk post-Christmas). Champion Data© Player Rank (CDPR), coaches’ ratings, and round 1 selection were used as in-season performance measures. CDPR and coaches’ ratings were examined over the entire season, first half of the season, and the first 4 games. Both Pearson and partial (controlling for AFL age) correlations were calculated to assess if any associations existed between preseason training variables and in-season performance measures. A median split was also employed to differentiate between higher- and lower-performing players for each performance measure. Results: Preseason training activities appeared to have almost no association with performance measured across the entire season and the first half of the season. However, many preseason training variables were significantly linked with performance measured across the first 4 games. Preseason training variables that were measured post-Christmas were the most strongly associated with in-season performance measures. Specifically, total on-field session rating of perceived exertion post-Christmas, a measurement of internal load, displayed the greatest association with performance. Conclusion: Late preseason training (especially on-field match-specific training) is associated with better performance in the early season.

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.

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 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.

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.

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.

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