Player Wellness (Soreness and Stress) and Injury in Elite Junior Australian Football Players Over 1 Season

2020 ◽  
Vol 15 (10) ◽  
pp. 1422-1429
Author(s):  
Timothy J.H. Lathlean ◽  
Paul B. Gastin ◽  
Stuart V. Newstead ◽  
Caroline F. Finch
Keyword(s):  
Injury Risk ◽  
Training Session ◽  
Estimating Equation ◽  
Decision Makers ◽  
Football Players ◽  
Injury Surveillance System ◽  
System A ◽  
Monitoring Strategies ◽  
Australian Football ◽  
Stress Fatigue

Purpose: To investigate the association between player wellness and injury in elite junior Australian football players over 1 competitive season. Methods: Prospective cohort study. Elite junior Australian football players (N = 196, average age = 17.7 y, range = 16–18 y) were recruited in the under-18 state league competition in Victoria, Australia. They recorded their wellness (sleep, fatigue, soreness, stress, and mood) according to a 5-point Likert scale 3 times weekly, with injuries (missed match/training session) entered into an online sport-injury surveillance system. A logistic generalized estimating equation was used to examine the association (expressed as odds ratio [OR]) between wellness and injury (yes/no). Results: Soreness was associated with injury at each time point across the week, with the strongest association evident for soreness reported 6 d postmatch (OR = 1.30; 95% confidence interval [CI], 1.17–1.44; P < .001). Stress and injury were associated with injury for average stress values across the week, as well as specifically on day 1 postmatch (OR = 1.10; 95% CI, 1.01–1.21; P = .038). Mood reported in the middle of the week (3 d postmatch) was associated with injury (OR = 0.87; 95% CI, 0.78–0.97; P = .014), as was fatigue (OR = 1.10; 95% CI, 1.00–1.22; P = .044). Conclusions: This study demonstrates key associations between wellness and injury in elite junior Australian football, specifically soreness, stress, fatigue, and mood. Monitoring strategies help identify injury-risk profiles, which can help decision makers (coaches or medical staff) intervene when relevant to reduce injury risk.

Absolute and Relative Load and Injury in Elite Junior Australian Football Players Over 1 Season

2020 ◽  
Vol 15 (4) ◽  
pp. 511-519 ◽  
Author(s):  
Timothy J.H. Lathlean ◽  
Paul B. Gastin ◽  
Stuart V. Newstead ◽  
Caroline F. Finch
Keyword(s):  
Injury Risk ◽  
Perceived Exertion ◽  
Fold Increase ◽  
Estimating Equation ◽  
Rating Of Perceived Exertion ◽  
Football Players ◽  
Injury Surveillance System ◽  
Relative Load ◽  
Risk Of Injury ◽  
Australian Football

Purpose: To investigate the association between training and match loads and injury in elite junior Australian football players over 1 competitive season. Methods: Elite junior Australian football players (n = 290, age 17.7 [0.3] y, range 16–18 y) were recruited from the under-18 state league competition in Victoria to report load and injury information. One-week load (session rating of perceived exertion multiplied by duration) and all time-loss injuries were reported using an online sport-injury surveillance system. Absolute load measures (weekly sums) enabled the calculation of relative measures such as the acute:chronic workload ratio. Load measures were modeled against injury outcome (yes/no) using a generalized estimating equation approach, with a 1-wk lag for injury. Results: Low (<300 arbitrary units [au]) and high (>4650 au) 1-wk loads were associated with significantly higher risk of injury. Furthermore, low (<100 au) and high (>850 au) session loads were associated with a higher risk of injury. High strain values (>13,000) were associated with up to a 5-fold increase in the odds of injury. There was a relatively flat-line association between the acute:chronic workload ratio and injury. Conclusions: This study is the first investigation of elite junior athletes demonstrating linear and nonlinear relationships between absolute and relative load measures and injury. Coaches should focus player loads on, or at least close to, the point at which injury risk starts to increase again (2214 au for 1-wk load and 458 au for session load) and use evidence-based strategies across the week and month to help reduce the risk of injury.

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.

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.

scholarly journals In-Competition Severe Injury Events in Elite Alpine Ski Racing from 1997 to 2020: The Case of the Austrian Ski Team

2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Michael Barth ◽  
Hans-Peter Platzer ◽  
Carina Andrea Forstinger ◽  
Gunnar Innerhofer ◽  
Anton Giger ◽  
...  
Keyword(s):  
Injury Risk ◽  
Female Athletes ◽  
Preventive Measures ◽  
Estimating Equation ◽  
Injury Surveillance ◽  
Severe Injury ◽  
Surveillance Systems ◽  
World Cup ◽  
Injury Surveillance System ◽  
Ski Racers

Abstract Background To increase safety in elite alpine ski racing Injury Surveillance Systems were implemented and preventive measures introduced. However, studies analysing the change in athletes’ injury risk by controlling for their exposure are still scarce. Objectives This study aimed to describe and analyse the risk of in-competition severe injury events (SIEcomp) in elite alpine ski racing. Methods Data recorded in the Austrian Ski Federation’s Injury Surveillance System were used to analyse the SIEcomp incidence. Information on athletes’ competition exposure was obtained from the official website of the International Ski Federation. In 23 seasons, 2333 skier seasons were recorded for the Austrian Ski Team. Within a total of 114,531 runs 169 SIEcomp occurred. Generalised Estimating Equation for Poisson Regressions were applied. Results The SIEcomp incidence per 1000 runs was 1.48 [95% confidence interval (CI) 1.26–1.73] for elite alpine ski racers and 2.21 (95% CI 1.79–2.75) for the subgroup of World Cup racers. A significant sex difference was detected for the subgroup of junior racers with a higher risk for female athletes [risk ratio (RR): 2.97, 95% CI 1.46–6.05]. Between the seasons of 1997 and 2020, the seasonal SIEcomp incidence increased by a factor of 2.67 for elite alpine ski racers and 3.53 for World Cup racers. Downhill (2.75, 95% CI 2.18–3.47) had the highest SIEcomp incidence, followed by super-G (1.94, 95% CI 1.30–2.88), giant slalom (1.40, 95% CI 1.06–1.85), and slalom (0.64, 95% CI 0.43–0.96). Conclusion Although many preventive measures have been implemented in elite alpine ski racing, the risk of SIEcomp has increased over the last two decades.

An evaluation of the presentation and severity of Australian football injury in children

Trauma ◽  
2020 ◽  
pp. 146040862094133
Author(s):  
Leopold Simma ◽  
Cameron S Palmer ◽  
Alan Ngo ◽  
Helen E Jowett ◽  
Warwick J Teague
Keyword(s):  
Injury Risk ◽  
Football Players ◽  
Psychosocial Wellbeing ◽  
Risk Of Injury ◽  
Trauma Service ◽  
Australian Rules Football ◽  
High Participation ◽  
Australian Football ◽  
Active Research ◽  
Substantial Morbidity

Introduction Child participation in sport is important for physical, cognitive and psychosocial wellbeing. Australian rules football has high participation, but also carries a high risk of injury due to the contact nature of the sport. This study aimed to evaluate changes in the presentation and hospital admission of paediatric Australian rules football-related injuries, and to compare the severity of these injuries with those from other team ball sports. Materials and methods At an Australian paediatric major trauma service, ED and hospital trauma registry data relating to Australian rules football injury between 2009 and 2015 were obtained. Data from other common team ball sports with a shared field of play were also identified. Results During the study period, there were 10,003 ED presentations, and 1110 admissions resulting from team ball sports. With 4751 ED presentations and 616 admissions, Australian rules football accounted for almost one-third of all sports-related presentations and admissions, and around half of the team ball sports cohort. Compared to other team ball sports patients, Australian rules football-related patients were 40% more likely to be admitted, and nearly twice as likely to be classified as severe injury. Australian rules football players presented with different injury patterns were compared to other team ball sports players; admitted players were significantly more likely to have sustained head or neck injuries, and were more than twice as likely to sustain truncal injury. Conclusions Australian rules football is a common cause of ED presentations and results in substantial morbidity, both overall and when compared with other team ball sports. Australian rules football should remain a focus for ongoing and active research into strategies which reduce injury risk.

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.

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