The Effects of Endurance-Based Skills-Specific Running Loads on Same-Day Resistance-Training Performance in Professional Australian Rules Football Players

2020 ◽  
Vol 15 (9) ◽  
pp. 1281-1288
Author(s):  
Dean Ritchie ◽  
Justin Keogh ◽  
Steven Stern ◽  
Peter Reaburn ◽  
Fergus O’Connor ◽  
...  
Keyword(s):  
Resistance Training ◽  
High Speed ◽  
Training Session ◽  
Concurrent Training ◽  
Football Players ◽  
Maximal Velocity ◽  
Endurance Running ◽  
Mixed Effect ◽  
Total Distance ◽  
Australian Football

Little is known about the effect of preceding endurance-exercise bouts on subsequent resistance-training (RT) performance in team-sport players. Purpose: To examine the effect of prior skills/endurance training and different recovery time periods on subsequent same-day RT performance in professional Australian football players. Methods: Sport-specific endurance-running loads (duration [in minutes], total distance [in meters], mean speed [in meters per minute], high-speed running >15 km·h−1, and relative high-speed running [>75% and >85% of maximal velocity]) were obtained for 46 professional Australian football players for each training session across an entire competitive season. RT was prescribed in 3 weekly mesocycles with tonnage (in kilograms) lifted recorded as RT performance. Endurance and RT sessions were interspersed by different recovery durations: ∼20 min and 1, 2, and 3 h. Fixed- and mixed-effect linear models assessed the influence of skills/endurance-running loads on RT performance. Models also accounted for season period (preseason vs in-season) and recovery duration between concurrent training bouts. Results: An increase in high-speed running and distance covered >75% and >85% of maximal velocity had the greatest reductions on RT performance. In-season total distance covered displayed greater negative effects on subsequent RT performance compared with preseason, while ∼20-min recovery between skills/endurance and RT was associated with greater reductions in RT performance, compared with 1-, 2-, and 3-h recovery. Conclusions: Sport-specific endurance-running loads negatively affect subsequent same-day RT performance, and this effect is greater in-season and with shorter recovery durations between bouts.

scholarly journals Training Load and Carbohydrate Periodization Practices of Elite Male Australian Football Players: Evidence of Fueling for the Work Required

2020 ◽  
Vol 30 (4) ◽  
pp. 280-286 ◽  
Author(s):  
Harry E. Routledge ◽  
Stuart Graham ◽  
Rocco Di Michele ◽  
Darren Burgess ◽  
Robert M. Erskine ◽  
...  
Keyword(s):  
Global Positioning System ◽  
Training Session ◽  
Football Players ◽  
Total Distance ◽  
Practice Elements ◽  
Physical Loading ◽  
Global Positioning ◽  
Australian Football ◽  
Food Diaries ◽  
And Training

The authors aimed to quantify (a) the periodization of physical loading and daily carbohydrate (CHO) intake across an in-season weekly microcycle of Australian Football and (b) the quantity and source of CHO consumed during game play and training. Physical loading (via global positioning system technology) and daily CHO intake (via a combination of 24-hr recall, food diaries, and remote food photographic method) were assessed in 42 professional male players during two weekly microcycles comprising a home and away fixture. The players also reported the source and quantity of CHO consumed during all games (n = 22 games) and on the training session completed 4 days before each game (n = 22 sessions). The total distance was greater (p < .05) on game day (GD; 13 km) versus all training days. The total distance differed between training days, where GD-2 (8 km) was higher than GD-1, GD-3, and GD-4 (3.5, 0, and 7 km, respectively). The daily CHO intake was also different between training days, with reported intakes of 1.8, 1.4, 2.5, and 4.5 g/kg body mass on GD-4, GD-3, GD-2, and GD-1, respectively. The CHO intake was greater (p < .05) during games (59 ± 19 g) compared with training (1 ± 1 g), where in the former, 75% of the CHO consumed was from fluids as opposed to gels. Although the data suggest that Australian Football players practice elements of CHO periodization, the low absolute CHO intakes likely represent considerable underreporting in this population. Even when accounting for potential underreporting, the data also suggest Australian Football players underconsume CHO in relation to the physical demands of training and competition.

scholarly journals Predicting ratings of perceived exertion in Australian football players: methods for live estimation

2016 ◽  
Vol 15 (2) ◽  
pp. 64-77 ◽  
Author(s):  
D. L. Carey ◽  
K. Ong ◽  
M. E. Morris ◽  
J. Crow ◽  
K. M. Crossley
Keyword(s):  
Machine Learning ◽  
Heart Rate ◽  
Perceived Exertion ◽  
Training Session ◽  
Machine Learning Techniques ◽  
Football Players ◽  
Ratings Of Perceived Exertion ◽  
Positioning Systems ◽  
Total Distance ◽  
Australian Football

Abstract The ability of machine learning techniques to predict athlete ratings of perceived exertion (RPE) was investigated in professional Australian football players. RPE is commonly used to quantifying internal training loads and manage injury risk in team sports. Data from global positioning systems, heart-rate monitors, accelerometers and wellness questionnaires were recorded for each training session (n=3398) from 45 professional Australian football players across a full season. A variety of modelling approaches were considered to investigate the ability of objective data to predict RPE. Models were compared using nested cross validation and root mean square error (RMSE) on RPE predictions. A random forest model using player normalised running and heart rate variables provided the most accurate predictions (RMSE ± SD = 0.96 ± 0.08 au). A simplification of the model using only total distance, distance covered at speeds between 18-24 km·h−1, and the product of total distance and mean speed provided similarly accurate predictions (RMSE ± SD = 1.09 ± 0.05 au), suggesting that running distances and speeds are the strongest predictors of RPE in Australian football players. The ability of non-linear machine learning models to accurately predict athlete RPE has applications in live player monitoring and training load planning.

Influence of Neuromuscular Fatigue on Accelerometer Load in Elite Australian Football Players

2013 ◽  
Vol 8 (4) ◽  
pp. 373-378 ◽  
Author(s):  
Stuart J. Cormack ◽  
Mitchell G. Mooney ◽  
Will Morgan ◽  
Michael R. McGuigan
Keyword(s):  
High Speed ◽  
Neuromuscular Fatigue ◽  
Football Players ◽  
Countermovement Jump ◽  
Baseline Measure ◽  
Running Activity ◽  
Australian Football ◽  
Percent Contribution ◽  
Playing Time ◽  
The Impact

Purpose:To determine the impact of neuromuscular fatigue (NMF) assessed from variables obtained during a countermovement jump on exercise intensity measured with triaxial accelerometers (load per minute [LPM]) and the association between LPM and measures of running activity in elite Australian Football.Methods:Seventeen elite Australian Football players performed the Yo-Yo Intermittent Recovery Test level 2 (Yo-Yo IR2) and provided a baseline measure of NMF (flight time:contraction time [FT:CT]) from a countermovement jump before the season. Weekly samples of FT:CT, coaches’ rating of performance (votes), LPM, and percent contribution of the 3 vectors from the accelerometers in addition to high-speed-running meters per minute at >15 km/h and total distance relative to playing time (m/min) from matches were collected. Samples were divided into fatigued and nonfatigued groups based on reductions in FT:CT. Percent contributions of vectors to LPM were assessed to determine the likelihood of a meaningful difference between fatigued and nonfatigued groups. Pearson correlations were calculated to determine relationships between accelerometer vectors and running variables, votes, and Yo-Yo IR2 score.Results:Fatigue reduced the contribution of the vertical vector by (mean ± 90% CI) –5.8% ± 6.1% (86% likely) and the number of practically important correlations.Conclusions:NMF affects the contribution of individual vectors to total LPM, with a likely tendency toward more running at low speed and less acceleration. Fatigue appears to limit the influence of the aerobic and anaerobic qualities assessed via the Yo-Yo IR2 test on LPM and seems implicated in pacing.

Effects of Velocity Loss Threshold Within Resistance Training During Concurrent Training on Endurance and Strength Performance

2020 ◽  
pp. 1-9
Author(s):  
Miguel Sánchez-Moreno ◽  
David Rodríguez-Rosell ◽  
David Díaz-Cueli ◽  
Fernando Pareja-Blanco ◽  
Juan José González-Badillo
Keyword(s):  
Resistance Training ◽  
Oxygen Uptake ◽  
Maximal Oxygen Uptake ◽  
Vertical Jump ◽  
Treadmill Running ◽  
Concurrent Training ◽  
Endurance Running ◽  
Loading Test ◽  
Significant Group ◽  
Group Time

Purpose: This study analyzed the effects of 3 training interventions: 1 isolated endurance training (ET) and 2 concurrent training (CT), which differed in the velocity loss (VL) magnitude allowed during the resistance training (RT) set: 15% (VL15) versus 45%, on strength and endurance running performance. Methods: A total of 33 resistance- and endurance-trained men were randomly allocated into 3 groups: VL15, VL 45%, and ET. ET was similar across all groups. The CT groups differed in the VL allowed during the RT set. Before and after the 8-week training program the following tests were performed: (1) running sprints, (2) vertical jump, (3) progressive loading test in the squat exercise, and (4) incremental treadmill running test up to maximal oxygen uptake. Results: Significant differences (P < .001) in RT volume (approximately 401 vs 177 total repetitions for VL 45% and VL15, respectively) were observed. Significant “group” × “time” interactions were observed for vertical jump and all strength-related variables: the CT groups attained significantly greater gains than ET. Moreover, a significant “group” × “time” interaction (P = .03) was noted for velocity at maximal oxygen uptake. Although all groups showed increases in velocity at maximal oxygen uptake, the VL15 group achieved greater gains than the ET group. Conclusions: CT interventions experienced greater strength gains than the ET group. Although all groups improved their endurance performance, the VL15 intervention resulted in greater gains than the ET approach. Therefore, moderate VL thresholds in RT performed during CT could be a good strategy for concurrently maximizing strength and endurance development.

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.

Individual Response to External Training Load in Elite Football Players

2020 ◽  
Vol 15 (5) ◽  
pp. 696-704
Author(s):  
Håvard Wiig ◽  
Thor Einar Andersen ◽  
Live S. Luteberget ◽  
Matt Spencer
Keyword(s):  
External Load ◽  
High Speed ◽  
Training Load ◽  
Effect Sizes ◽  
Football Players ◽  
Individual Response ◽  
Total Distance ◽  
External Training ◽  
Tracking Devices ◽  
Very High

Purpose: To investigate within-player effect, between-player effect, and individual response of external training load from player tracking devices on session rating of perceived exertion training load (sRPE-TL) in elite football players. Methods: The authors collected sRPE-TL from 18 outfield players in 21 training sessions. Total distance, high-speed running distance (>14.4 m/s), very high-speed running distance (>19.8 m/s), PlayerLoad™, PlayerLoad2D™, and high-intensity events (HIE > 1.5, HIE > 2.5, and HIE > 3.5 m/s) were extracted from the tracking devices. The authors modeled within-player and between-player effects of single external load variables on sRPE-TL, and multiple levels of variability, using a linear mixed model. The effect of 2 SDs of external load on sRPE-TL was evaluated with magnitude-based inferences. Results: Total distance, PlayerLoad™, PlayerLoad2D™, and HIE > 1.5 had most likely substantial within-player effects on sRPE-TL (100%–106%, very large effect sizes). Moreover, the authors observed likely substantial between-player effects (12%–19%, small to moderate effect sizes) from the majority of the external load variables and likely to very likely substantial individual responses of PlayerLoad™, high-speed running distance, very high-speed running distance, and HIE > 1.5 (19%–30% coefficient of variation, moderate to large effect sizes). Finally, sRPE-TL showed large to very large between-session variability with all external load variables. Conclusions: External load variables with low intensity-thresholds had the strongest relationship with sRPE-TL. Furthermore, the between-player effect of external load and the individual response to external load advocate for monitoring sRPE-TL in addition to external load. Finally, the large between-session variability in sRPE-TL demonstrates that substantial amounts of sRPE-TL in training sessions are not explained by single external load variables.

Physical Preparation Factors That Influence Technical and Physical Match Performance in Professional Australian Football

2018 ◽  
Vol 13 (8) ◽  
pp. 1021-1027 ◽  
Author(s):  
Samuel Ryan ◽  
Aaron J. Coutts ◽  
Joel Hocking ◽  
Patrick A. Dillon ◽  
Anthony Whitty ◽  
...  
Keyword(s):  
Performance Measures ◽  
High Speed ◽  
Training Session ◽  
Time Trial ◽  
Well Being ◽  
Related Factors ◽  
Positive Effects ◽  
Australian Football ◽  
Collective Influence ◽  
Physical Preparation

Objectives: To examine the collective influence of a range of physical preparation elements on selected performance measures during Australian football match play. Design: Prospective and longitudinal. Methods: Data were collected from 34 professional Australian football players from the same club during the 2016 Australian Football League competition season. Match activity profiles and acute (7-d) and chronic (3-wk) training loads were collected using global positioning system devices. Training response was measured by well-being questionnaires completed prior to the main training session each week. Maximal aerobic running speed (MAS) was estimated by a 2-km time trial conducted during preseason. Coach ratings were collected from the senior coach and 4 assistants after each match on a 5-point Likert scale. Player ratings were obtained from a commercial statistics provider. Fifteen matches were analyzed. Linear mixed models were constructed to examine the collective influence of training-related factors on 4 performance measures. Results: Muscle soreness had a small positive effect (ES: 0.12) on Champion Data rating points. Three-week average high-speed running distance had a small negative effect (ES: 0.14) on coach ratings. MAS had large to moderate positive effects (ES: 0.55 to 0.47) on relative total and high-speed running distances. Acute total and chronic average total running distance had small positive (ES: 0.13) and negative (ES: 0.14) effects on relative total and high-speed running distance performed during matches, respectively. Conclusions: MAS should be developed to enhance players’ running performance during competition. Monitoring of physical preparation data may assist in reducing injury and illness and increasing player availability but not enhance football performance.

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.

Factors Affecting Match Running Performance in Professional Australian Football

2017 ◽  
Vol 12 (9) ◽  
pp. 1199-1204 ◽  
Author(s):  
Samuel Ryan ◽  
Aaron J. Coutts ◽  
Joel Hocking ◽  
Thomas Kempton
Keyword(s):  
Aerobic Fitness ◽  
High Speed ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Time Trial ◽  
Related Factors ◽  
Running Performance ◽  
Total Distance ◽  
Individual Player ◽  
Australian Football

Purpose:To examine the influence of a range of individual player characteristics and match-related factors on activity profiles during professional Australian football matches. Methods:Global positioning system (GPS) profiles were collected from 34 professional Australian football players from the same club over 15 competition matches. GPS data were classified into relative total and high-speed running (HSR; >20 km/h) distances. Individual player aerobic fitness was determined from a 2-km time trial conducted during the preseason. Each match was classified according to match location, season phase, recovery length, opposition strength, and match outcome. The total number of stoppages during the match was obtained from a commercial statistics provider. A linear mixed model was constructed to examine the influence of player characteristics and match-related factors on both relative total and HSR outputs. Results:Player aerobic fitness had a large effect on relative total and HSR distances. Away matches and matches lost produced only small reductions in relative HSR distances, while the number of rotations also had a small positive effect. Matches won, more player rotations, and playing against strong opposition all resulted in small to moderate increases in relative total distance, while early season phase, increased number of stoppages, and away matches resulted in small to moderate reductions in relative total distance. Conclusions:There is a likely interplay of factors that influence running performance during Australian football matches. The results highlight the need to consider a variety of contextual factors when interpreting physical output from matches.

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