Running (fast) as a hamstring injury risk factor, treatment and injury prevention strategy blanch

1. Training load as a hamstring injury
risk factor, treatment and injury
prevention tool
Peter Blanch

3. Time trend analysis showed an annual average 2.3% increase in
hamstring incidence and 4.1% increase in burden
2001-2004- approx 15 days per injury……………2011-2014 –approx 19 days per injury
• 13 years
• 209 club seasons
• 5216 player seasons

4. Not all sports have an increasing hamstring problem
3
4
5
6
7
8
10
15
20
25
30
2006 2008 2010 2012 2014 2016 2018
Incidence(totalinjuriesperclub)
Prevalence(matcheslostper
club)
Prevalence Incidence
AFL
• 10 years
• 180 squad seasons
• 7200 player seasons
• Severity been static (3.1
to 4 matches)
0.5
1
1.5
2
2.5
10
15
20
25
30
2006 2008 2010 2012 2014 2016 2018
Prevalence(%losttrainingand
matchdays)
Incidence(totalinjuriesperseason)
Incidence Prevalence
Cricket
• 10 years
• 70 squad seasons
• Approx 2450 player seasons

6. Injury studies
• Leave out acute collision type injuries
• Hamstring make up a fair proportion
• Cricket 2007-2017 - 24% of time lost
• AFL – 2007-2016
• Incidence 26 %
• Time loss 25%

7. Load
Time
• Biomechanics
• Age
• Training and injury history

8. Likelihoodofinjurynextweek(%)
• 28 fast bowlers
• 43 player seasons
• Over 6 years
Relative workload is more important than absolute

9. Acute Load
(Load in 1 week)
Debate on the modelling
Rolling averages
Chronic load
(average 1 week load over 4 weeks)

10. Debate on the modelling
Exponentially weighted moving average
Better way to determine the acute:chronic workload ratio? Williams S, West S, Cross
MJ, Stokes KA
http://dx.doi.org/10.1136/bjsports-2016-096589
EWMAtoday = Loadtoday X λa + ((1 - λa) X
EWMAyesterday)
λa = 2/(N + 1)

11. Acute Load
(Load in 1 week)
Debate on the modelling
Uncoupled windows
Chronic load
(average 1 week load over 4 weeks)
Lolli L, Batterham AM, Hawkins R, et al Mathematical coupling causes spurious correlation within
the conventional acute-to-chronic workload ratio calculations Br J Sports Med Published Online
First: 03 November 2017. doi: 10.1136/bjsports-2017-098110

12. If you do more this week than you are prepared
for you are more likely to get injured next week.
• Cricket
• Rugby League
• Soccer
• Gaelic football
• Australian Rules Football
• Baseball

13. That’s him and he’s here….
• Followed AFL squad for 2years
• 22 hamstring injuries
• High speed running >24 km/hr
• Rapid increases in HSR above the
players 2 year average resulted in
increases of hamstring injury risk by as
high as 6.44 (OR)(95%CI 3-14, p<.001)
Did more than what you were used to……

15. High speed running is special

16. Fast Running
• Usain Bolt world record 9.58 sec-
•Average velocity- 10.44 m/sec or 37.6 km/hr
•Peak velocity (60-80m)- 12.42 m/sec or 44.72 km/hr

17. Typical GPS speed bands
• 0-6 km/hr - walking
• 6-18 km/hr – running
• 18-24 km/hr – high speed running
• >24 km/hr – very high speed running
• Player load

19. Early
stance
y = 0.0132x2 - 0.2378x + 0.1967
R² = 0.4358
-4
-2
0
2
4
0 2 4 6 8 10 12
y = 0.0239x2 - 0.2834x
R² = 0.095
-4
-2
0
2
4
0 2 4 6 8 10 12
Knee
Ankle
Work - Joules/Kg

20. Late
stance
Knee
Ankle
Work - Joules/Kg
y = -0.017x2 + 0.29x + 0.22
R² = 0.5
-4
-2
0
2
4
0 2 4 6 8 10 12
y = -0.002x2 + 0.012x + 0.4
R² = 0.043
-4
-2
0
2
4
0 2 4 6 8 10 12
y = -0.007x2 - 0.014x - 0.02
R² = 0.56
-4
-2
0
2
4
0 2 4 6 8 10 12
Hip
Velocity (m/sec)

21. Late
swing
Knee
Work - Joules/Kg
Hip
y = 0.05x2 - 0.26x + 0.64
R² = 0.87
-4
-2
0
2
4
0 2 4 6 8 10 12
y = -0.016x2 - 0.095x + 0.07
R² = 0.94
-4
-2
0
2
4
0 2 4 6 8 10 12
Velocity (m/sec)

22. Running at 90% of top speed is not 90% of top work by the muscles
10 m/sec = 36 km/hr
Positive work at the hip
Negative work at the knee
Speed %Max Speed Speed (msec) Work (J/Kg) %Max work
Max 34 100 9.4 4.81 100
32 94 8.9 4.23 88
30 88 8.3 3.70 77
28 82 7.8 3.20 67
26 76 7.2 2.75 57
24 71 6.7 2.34 49
22 65 6.1 1.96 41
20 59 5.6 1.63 34

23. • 37 players over 1 season
• Injury-anything that prevented a player participating
in training and or games for >24 hrs
• Fast running training load split into quartiles, lowest
group as the ‘reference’ group
• Relative max velocity
• Weekly max velocity distance
• Total number of maximal velocity exposures
• Overall training load dichotomised: low < 4750 AU,
high > 4750 AU
• Running velocity measured by GPS (validated against
timing gates)
• ACWR by rolling averages
• 91 injuries

24. 1
0.72
0.22
0.12
0
0.5
1
1.5
2
2.5
<85% (reference) 85-90% 90 -95% >95%
Oddsratioofinjuryinsubsequentweek
Peak running velocity current week
Relative maximal velocity as a risk factor

25. 0.22
0
0.5
1
1.5
2
2.5
3
3.5
4
< 5(reference) 5-10 exposures 10-15 exposures >15 exposures
Oddsratioofinjurysubsequentweek
Number of maximal velocity (95%) bouts in current week
Combination of training loads and max speed exposures
Low training High training
Overall training load dichotomised: low < 4750 AU, high > 4750 AU

26. High-speed running and sprinting as an injury risk factor in
soccer: Can well-developed physical qualities reduce the risk?
• 37 soccer players followed over 1 x 48 week season
• Portuguese Premier League (Liga Nos, Portugal)
• Internal and external training loads measured
• High speed running (>14.4 km/hr)
• Sprint speed running (>19.8 km/hr)
• Lower limb injuries, low (1-3 sessions), moderate (1-2 weeks),
severe ( 3 or more weeks)
• 21 day chronic load, 3 day acute load
• Aerobic fitness (30-15 intermittent fitness test)
• Low load (<2584 AU), high load (>2584 AU)
• 75 injuries from 7104 player exposures

27. 1
1.02
0.12
5.02
0
1
2
3
4
5
6
7
<674m
675-700m
701-750m
750-1025m
Oddsriskoflowerleginjurynextweek
Total 1 week high speed distance
High speed running and
subsequent risk of injury
1 1.12
0.54
3.44
0
1
2
3
4
5
6
<165m
165-200m
201-350m
350-525m
Oddsriskoflowerleginjurynextweek
Total 1 week sprint speed distance
Weekly sprint speed running
and subsequent risk of injury
Error bars = 90% confidence intervals

28. 0
1
2
3
4
5
6
7
8
0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4
Oddsratioofsubsequentlowerleginjury
Acute:chronic workoad ration (3:21days)
Acute to chronic workload ratio for running and
subsequent injury
High speed Sprint
Error bars = 90% confidence intervals

29. • 60 players over 3 seasons
• GPS derived data
Standard risk

30. The Goldilocks Zone

31. • Establish extent of the problem
• Identify possible mechanisms
• Introduce preventions strategies
• Re-do step 1
Did you do what you said you were going to do…

32. Load as an injury prevention strategy
Nick Murray PhD

33. 4.1
4.6
5.4
1.9
2014 2015 2016 2017
Injuriesper1000play/trainhours
Injury Incidence
93.2
133.6
155.2
34.4
2014 2015 2016 2017
Playertrain/playdayslostper1000hrstrain/play
Injury Burden

34. Average ‘spikes’ (>1.5 EWMA ACWR) per player during the whole season
0
10
20
30
40
50
2014 2015 2016 2017
Total Distance
0
10
20
30
40
50
2014 2015 2016 2017
High speed distance
0
10
20
30
40
50
2014 2015 2016 2017
Player load
0
10
20
30
40
50
2014 2015 2016 2017
Very high speed distance
Error bars = SD

35. 10000
15000
20000
25000
2014 2015 2016 2017
Total Distance
1500
2000
2500
3000
2014 2015 2016 2017
High speed distance
0
100
200
300
400
500
2014 2015 2016 2017
Very high speed distance
1000
1500
2000
2500
2014 2015 2016 2017
Player load
Average Chronic workload (rolling average) per player within season

36. Pre-season1
Pre-season2
Pre-season3
Pre-season4
Pre-season5
Pre-season6
Pre-season7
Pre-season8
Pre-season9
Pre-season10
Pre-season11
Pre-season12
Pre-season13
Pre-season14
IntroComp
IntroComp
IntroComp
IntroComp
Week1
Week2
Week3
Week4
Week5
Week6
Week7
Week8
Week9
Week10
Week11
Week12
Week13
Week14
Week15
Week16
Week17
Week18
Week19
Week20
Week21
Week22
Season
Incidence
Season
Prevalence
Injuryseverity
Injury1 3
Injury2 2
Injury3 1
Injury4 2
Injury5 2
Injury6 3
Injury1 2
Injury2 2
Injury3 2
Injury4 2
Injury5 11
Injury6 1
Injury7 5
Injury8 1
Injury9 1
Injury10 4
Injury11 1
Injury1 1
Injury2 6
Injury3 1
Injury4 3
Injury5 3
Injury6 2
Injury7 3
Injury8 3
Injury9 2
Injury10 2
Injury1 1
Injury2 1
Injury3 3
Injury4 3
Injury5 2
Injury6 1
Injury7 1
2014
2015
2016
2017
6
7
7
6
13
24
18
11
2.2
3.4
2.6
1.8
Brisbane Lions Hamstring Injuries Past 4 years
AFL 10 year average (approx) 6 22 3.5

37. So why do the European footballers have increasing hamstring injuries?

38. NB- sprinting >25.1 km/hr
26-28km/hr
Game demands- 200 – 350 m of 25 + km/hr running

39. NB- sprint speed > 19.8km/hr
Portuguese footballers in lowest band of injury
risk cover 200-350 metres of running 20+
km/hr in a week.

40. 0
5
10
15
20
25
30
35
Numberofteams
2012
2013
2014
10 week induction
0
5
10
15
20
25
30
Weekly
maintenance
every week
Most weeks Sporadically Not at all
Numberofteams
2012
2013
2014
Ongoing maintenance

41. So why do the European footballers have increasing hamstring injuries?
• The demands of the game are increasing
• They don’t run fast enough often enough
• They don’t do their nordics

42. Take home message
• Sprint speed needs to be measured at a % of maximum capable
speed, current bands are too slow
• There is a Goldilocks zone where too little and too much sprint speed
running can increase injury risk
• The Goldilocks zone isn’t very big
• Sprint speed training needs to be considered as a component (an
important component) for the preparation of football code athletes

43. What your Nanna could have told you!!!
When you go and exercise dear,
make sure you don’t over do it. If
you haven’t done too much
recently don’t do too much
now… I’ll have a nice cool drink
for you when you are finished…

44. NB- Sprint speed >23 km/hr
4460
4362
2429
881
571
Total
4024
5103
2887
627
397
Brisbane Lions