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CONTACT Dr Sean Williams | [email protected] DEPARTMENT FOR HEALTH Sport, Health and Exercise Science Presented by Dr. Sean Williams Modelling the load-injury relationship Latest evidence and future directions

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Page 1: Sport, Health and Exercise Science Modelling the load-injury ...medicine.exeter.ac.uk/media/universityofexeter/medical...CT Drn ams | S. ath. ac. uk DEPARTMENT FOR HEALTH Sport, Health

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Dr

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DEPARTMENT FOR HEALTHSport, Health and Exercise Science

Presented by Dr. Sean Williams

Modelling the load-injury

relationshipLatest evidence and future directions

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MODELLING THE LOAD-INJURY RELATIONSHIP

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Theoretical basis for monitoring loads

Time

Tra

inin

g e

ffect

Fatigue

Fitness Performance

Banister, E., Calvert, T., Savage, M. & Bach, T. (1975) A systems model of training for athletic performance. Aust J Sports Med, 7,

57-61.

Injury risk?

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MODELLING THE LOAD-INJURY RELATIONSHIP

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Theoretical basis for monitoring loads

Soligard, T., Schwellnus, M., Alonso, J. M., Bahr, R., Clarsen, B., Dijkstra, H. P., ... & Van Rensburg, C. J. (2016). How much is too

much? International Olympic Committee consensus statement on load in sport and risk of injury. British Journal of Sports

Medicine, 50(17), 1030-1041.

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MODELLING THE LOAD-INJURY RELATIONSHIP

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Theoretical basis for monitoring loads

Windt, J., & Gabbett, T. J. (2016). How do training and competition workloads relate to injury? The workload—injury aetiology model. British Journal of Sports

Medicine, bjsports-2016.

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Current best practice?

Acute:Chronic Workload Ratio [ACWR]

Acute | Recent loads (e.g. one week), analogous to state of ‘fatigue’

Chronic | Average loads over last 3-6 weeks, analogous to state of ‘fitness’

50

100

150

200

125

0

50

100

150

200

250

1 2 3 4

Load [

AU

]

Week

Load Chronic Load Acute:Chronic

= 200/125

= 1.60

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Acute:Chronic Workload Ratio

Gabbett, T. J. (2016). The training—injury prevention paradox: should athletes be training smarter and harder?. British Journal of

Sports Medicine, 50(5), 273-280.

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Acute:Chronic Workload Ratio

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Smoothed averages

1.52

1.03

0.00

0.50

1.00

1.50

2.00

2.50

0

100

200

300

400

500

600

700

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41

Acu

te:C

hro

nic

Wo

rklo

ad

L

oa

d [A

U]

Loads EWMA ACWR Rolling ACWR

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ACWR and injury prediction

Fanchini, M., Rampinini, E., Riggio, M., Coutts, A. J., Pecci, C., & McCall, A. (2018). Despite association, the acute:

chronic work load ratio does not predict non-contact injury in elite footballers. Science and Medicine in Football, 1-7.

Sensitivity

Specificity

20%

85%

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Acute:chronic workload ratioPre

dic

ted

pro

bab

ilit

y o

f in

jury

in

su

bse

qu

en

t 4

we

ek p

eri

od

Individual effects

• Using mixed models, it’s possible to get unique effects for each athlete:

ACWR

Su

bse

qu

en

t in

jury

ris

k

Warren, A., Williams, S., McCaig, S., & Trewartha, G. (2017). High acute: chronic workloads are associated with injury in England & Wales Cricket Board Development

Programme fast bowlers. Journal of Science and Medicine in Sport.

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Moderators in workload–injury investigations

Windt, J., Zumbo, B. D., Sporer, B., MacDonald, K., & Gabbett, T. J. (2017). Why do workload spikes cause injuries, and which athletes are at higher risk?

Mediators and moderators in workload–injury investigations.

Malone, S., et al. "Aerobic Fitness and Playing Experience Protect Against Spikes in

Workload: The Role of the Acute: Chronic Workload Ratio on Injury Risk in Elite Gaelic

Football." International journal of sports physiology and performance (2016).

0

1

2

3

4

5

6

7

8

9

3.00 to 3.15 3.16 to 3.30 3.31 to 3.45 3.46 to 4.00

Od

ds r

atio

1 km time trial time

ACWR > 1.50

Aerobic fitness

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Moderators in workload–injury investigations

Windt, J., Zumbo, B. D., Sporer, B., MacDonald, K., & Gabbett, T. J. (2017). Why do workload spikes cause injuries, and which athletes are at higher risk?

Mediators and moderators in workload–injury investigations.

Malone, S., Hughes, B., Doran, D. A., Collins, K., & Gabbett, T. J. (2018). Can the

workload–injury relationship be moderated by improved strength, speed and repeated-

sprint qualities?. Journal of Science and Medicine in Sport.

Strength

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Moderators in workload–injury investigations

Windt, J., Zumbo, B. D., Sporer, B., MacDonald, K., & Gabbett, T. J. (2017). Why do workload spikes cause injuries, and which athletes are at higher risk?

Mediators and moderators in workload–injury investigations.

Blanch, P., & Gabbett, T. J. (2015). Has the athlete trained enough to return to play

safely? The acute: chronic workload ratio permits clinicians to quantify a player's risk of

subsequent injury. Br J Sports Med, bjsports-2015.

Previous injury

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Moderators in workload–injury investigations

Heart Rate Variability

Williams, S., Booton, T., Watson, M., Rowland, D., & Altini, M. (2017). Heart Rate Variability is a Moderating Factor in the Workload-

Injury Relationship of Competitive CrossFit™ Athletes. Journal of sports science & medicine, 16(4), 443.

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HRV as a stress/recovery marker

p(t) = k1g(t)e –t / τ1 – k2h(t)e – t / τ2

p(t) = Performance k1 , k2 = Multipliers

g(t) = Fitness τ1 , τ2 = Time constants

h(t) = Fatigue t = Time

Performance Fitness Fatigue

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Planning optimal workloads

Carey, D. L., Crow, J., Ong, K. L., Blanch, P., Morris, M. E., Dascombe, B. J., & Crossley, K. M. (2017). Optimising

Pre-Season Training Loads in Australian Football. International Journal of Sports Physiology and Performance, 1-19.

AIM:

Maximise total load, whilst keeping ACWR within safe

zone

https://progressiveathleticperformance.com/

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Future Directions

Technology

Integration of loads

Analysis

Life loads

Match loads

Training loads

Sperlich, B., Düking, P., & Holmberg, H. C. (2017). A SWOT analysis of the use and potential misuse of implantable monitoring devices by athletes. Frontiers in

Physiology, 8, 629.

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Additional issues with ACWR?

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ConclusionsConclusions

• Current best practice: High chronic loads are required to optimally prepare athletes

for competition demands, but these must be achieved gradually and rapid ‘spikes’

in workloads should be avoided.

• Calculating the ACWR using EWMA may be more sensitive to injury risk than rolling

averages.

• Our understanding of the moderators of this workload injury relationship is

developing.

• Optimisation techniques may be used to create objective training plan designs that

satisfy injury risk constraints.

• Technology, analysis and the integration of different forms of load are areas for

future direction.