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A Review of Football Injuries on Thirdand Fourth Generation Artificial TurfsCompared with Natural TurfSean Williams,1 Patria A. Hume1 and Stephen Kara1,2

1 Sports Performance Research Institute New Zealand (SPRINZ), School of Sport and Recreation,

Auckland University of Technology, Auckland, New Zealand

2 Blues Super 14 Rugby Team, Auckland, New Zealand

Contents

Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9031. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9042. Literature Search Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 905

2.1 Search Parameters and Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9052.2 Assessment of Study Quality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9052.3 Data Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9052.4 Analysis and Interpretation of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 905

3. Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9083.1 Types of Natural and Artificial Surfaces Used by Football Codes . . . . . . . . . . . . . . . . . . . . . . . . . . 9083.2 Incidence and Nature of Injury as a Result of Playing on Natural Turf or Artificial Turf . . . . . . . . . 908

3.2.1 Ankle Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9093.2.2 Knee Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9093.2.3 Muscle Strains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9093.2.4 Injury Severity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 909

3.3 Mechanisms and Risk Factors for Injury on Artificial and Natural Turf . . . . . . . . . . . . . . . . . . . . . . . 9133.3.1 Shoe-Surface Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9183.3.2 Foot Loading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9193.3.3 Impact Attenuation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9193.3.4 Physiological Response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9193.3.5 Gender. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9193.3.6 Age. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9193.3.7 Level of Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9193.3.8 Training and Matches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9203.3.9 Weather . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9203.3.10 Changing between Surfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 920

4. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 920

Abstract Football codes (rugby union, soccer, American football) train and playmatches on natural and artificial turfs. A review of injuries on different turfswas needed to inform practitioners and sporting bodies on turf-related injurymechanisms and risk factors. Therefore, the aim of this review was to comparethe incidence, nature and mechanisms of injuries sustained on newer generation

REVIEW ARTICLESports Med 2011; 41 (11): 903-9230112-1642/11/0011-0903/$49.95/0

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artificial turfs and natural turfs. Electronic databases were searched using thekeywords ‘artificial turf’, ‘natural turf’, ‘grass’ and ‘inj*’. Delimitation of 120articles sourced to those addressing injuries in football codes and those usingthird and fourth generation artificial turfs or natural turfs resulted in 11 ex-perimental papers. These 11 papers provided 20 cohorts that could be assessedusing magnitude-based inferences for injury incidence rate ratio calculationspertaining to differences between surfaces. Analysis showed that 16 of the 20cohorts showed trivial effects for overall incidence rate ratios between sur-faces. There was increased risk of ankle injury playing on artificial turf in eightcohorts, with incidence rate ratios from 0.7 to 5.2. Evidence concerning risk ofknee injuries on the two surfaces was inconsistent, with incidence rate ratiosfrom 0.4 to 2.8. Two cohorts showed beneficial inferences over the 90% like-lihood value for effects of artificial surface on muscle injuries for soccerplayers; however, there were also two harmful, four unclear and five trivialinferences across the three football codes. Inferences relating to injury severitywere inconsistent, with the exception that artificial turf was very likely to haveharmful effects forminor injuries in rugby union training and severe injuries inyoung female soccer players. No clear differences between surfaces were evi-dent in relation to training versus match injuries. Potential mechanisms fordiffering injury patterns on artificial turf compared with natural turf includeincreased peak torque and rotational stiffness properties of shoe-surface in-terfaces, decreased impact attenuation properties of surfaces, differing footloading patterns and detrimental physiological responses. Changing betweensurfaces may be a precursor for injury in soccer. In conclusion, studies haveprovided strong evidence for comparable rates of injury between new gen-eration artificial turfs and natural turfs. An exception is the likely increasedrisk of ankle injury on third and fourth generation artificial turfs. Therefore,ankle injury prevention strategies must be a priority for athletes who play onartificial turf regularly. Clarification of effects of artificial surfaces on muscleand knee injuries are required given inconsistencies in incidence rate ratiosdepending on the football code, athlete, gender or match versus training.

1. Introduction

In football codes, such as rugby union, soccerand American football, training and matches arenow being played on both natural and artificialturf surfaces. First and second generation artifi-cial surfaces have been associated with an in-creased injury risk versus natural grass surfacesacross a number of sports.[1-5] The properties offirst and second generation turfs differ distinctlyfrom recent third and fourth generation sur-faces.[6] The drawbacks of earlier generation ar-tificial surfaces, such as hardness and excessiveheat retention, are purported to have been ad-dressed in newer generation surfaces.[7] A recentreview by Dragoo and Braun[8] concluded that

although injury patterns differ on new generationturfs, the overall injury rate is comparable withnatural turfs. Our review expands on Dragoo andBraun’s by using magnitude-based inferences touniformly analyse studies. We have also analysedseveral additional papers that will add to theknowledge base. Our question is whether thirdand fourth generation artificial turfs are asso-ciated with increased injury risk versus naturalgrass surfaces across three football codes. Rugby,soccer (male and female) and American foot-ball have dissimilar playing styles and may havedifferent injury incidence patterns on differentsurfaces.

The aim of this review was to compare theincidence, nature and mechanisms of injuries

904 Williams et al.

ª 2011 Adis Data Information BV. All rights reserved. Sports Med 2011; 41 (11)

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sustained on newer generation artificial turfs andnatural turfs.

2. Literature Search Methodology

Cochrane Collaboration[9] review methodology(literature search; assessment of study quality; datacollection of study characteristics including par-ticipants, sport, outcome measures and results;analysis and interpretation of results; and rec-ommendations for injury prevention strategiesand further research) was used to evaluate injurycharacteristics and risk factors for injury on arti-ficial turfs compared with natural grass turf.

2.1 Search Parameters and Criteria

Web of Knowledge, Scopus, MEDLINE,SportDiscus�, ProQuest Direct, Google Scholar,CINAHL� and Scirus databases from 1975 toNovember 2010 were searched using the key-words ‘artificial turf’, ‘natural turf’, ‘grass’ and‘inj*’. Inclusion criteria for the article were providedas follows: (i) data for injury on natural or artificialturf in football codes, including rugby union, soccerandAmerican football; (ii) relevant information forepidemiology, possiblemechanisms and risk factorsof injury on natural or artificial turfs in general; or(iii) football studies that may provide insight topossible mechanisms or risk factors associated withinjury on turf. Exclusion criteria were as follows:(i) unavailable in English and not previously re-ferred to by other sources; or (ii) not specific tothird or fourth generation artificial turf and didnot add knowledge to the aim of the manuscript.Additional supportive articles were sought througharticle reference lists and a further search using thekey words ‘torque’, ‘stiffness’ and ‘surface*’ to findpapers attending to potential mechanisms. Of the120 articles sourced, 11 experimental papers pro-vided data for 20 cohorts that could be assessedusing magnitude-based inferences for injury inci-dence rate ratio calculations for differences betweennew generation artificial and natural turfs.

2.2 Assessment of Study Quality

Methodological limitations were associatedwith many of the studies reviewed; namely, a

failure to clearly describe the specific type of ar-tificial turf used, the condition of the natural turfsurface, the characteristics of the cohort, the en-vironmental conditions, specifications of footwearused or the p-value associated with the outcomemeasure. Variations in injury definitions and se-verity were encountered, while the data qualitywas further reduced by a lack of uniform collec-tion methods. Many studies in the literature hadmade inferences about injury risks based only onthe p-value derived from a null hypothesis test.This can result in misleading conclusions beingmade, depending on the magnitude of the effectstatistic, sample size and error of measurement.[10]

One study in American football[11] was funded bythe artificial turf manufacturer used within thestudy and so its conclusions should be treated withcaution. An unsponsored study that also investi-gated the effects of new generation artificial turfon injury risk in American football found higherrates of anterior cruciate ligament injury andankle eversion sprains on artificial turf.[12] Un-fortunately, this study has only been published asan abstract and so we were unable to include theirstudy in our data analyses.

2.3 Data Extraction

For studies passing the quality criteria data wereextracted, including participant characteristics, inci-dence and nature of injuries on natural or artificialturfs, and main findings (table I). Note that foranalysis of type of injury and risk factors thenumber of cohorts was less than the total of 20cohorts used for the overall analysis, given thatsome studies did not report specific injury data.

2.4 Analysis and Interpretation of Results

The outcomemeasure used to assess each studywas the incidence rate ratio for injuries on artifi-cial and natural turf, calculated using natural turfas the reference. Several studies provided morethan one cohort, such as males versus females ormatches versus training information. Clinical in-ferences regarding the true value of effects weremade in a manner outlined by Batterham andHopkins.[10] Where provided, the p-value relatingto the outcome measure (incidence rate ratio) was

Artificial Turf Injury Review 905


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Tab

leI.

Stu

dy

chara

cte

ristics,

incid

ence

of

inju

ries,

incid

ence

rate

ratios

and

90

%confidence

inte

rvals

,and

perc

enta

ge

likelih

oods

for

beneficia

l,tr

ivia

lor

harm

fuleff

ects

when

com

paring

inju

ryin

cid

ence

on

art

ific

ialand

natu

raltu

rfs

surf

aces

for

soccer,

rugby

unio

nand

Am

erican

footb

all

Stu

dy

No.ofsubje

cts

or

team

s,gender

and

age

(mean

–S

Dor

range

y)

Levelof

perf

orm

ance

Tra

inin

g

or

matc

h

inju

ries

Incid

ence

(n/1

000

hexposure

)

Incid

ence

rate

ratio

a

90

%C

I

Clin

icalin

fere

nce

Lik

elih

ood

(%)

thattr

ue

valu

eofth

e

eff

ectsta

tistic

is:

natu

ral

turf

art

ific

ial

turf

substa

ntially

beneficia

l

triv

ial

substa

ntially

harm

ful

So

ccer

Ekstr

and

etal.

[13]

613

male

s

Age

25

–5

y

Elit

eM

atc

h21.7

222.3

71.0

30.1

3M

ostlik

ely

triv

ial

0.0

99.9

0.1

Solig

ard

etal.

[14]

~60

000

pla

yers

(~one-t

hird

were

fem

ale

)

Age

13–19

y

Regio

nal

Matc

h39.7

034.2

00.9

30.1

5V

ery

likely

triv

ial

2.4

97.6

0.0

Ste

ffen

etal.

[15]

2020

fem

ale

s

Age

15

–1

y

Regio

nal

Matc

h8.3

08.7

01.0

50.2

0V

ery

likely

triv

ial

0.6

95.2

4.2

Bjo

rneboe

etal.

[16]

Male

s

14

team

s

No

age

data

Elit

eM

atc

h17.0

017.6

01.0

40.1

6V

ery

likely

triv

ial

0.1

99.9

0.0

Fulle

retal.

[17]

Male

s

2005

season:

52

team

s

2006

season:

54

team

s

No

age

data

Colle

gia

teM

atc

h23.9

225.4

31.0

60.1

5V

ery

likely

triv

ial

0.0

99.2

0.8

Fulle

retal.

[17]

Fem

ale

s

2005

season:

64

team

s

2006

season:

72

team

s

No

age

data

Colle

gia

teM

atc

h21.7

919.1

50.8

80.1

3Lik

ely

triv

ial

7.3

92.7

0.0

Ekstr

and

etal.

[18]

492

male

s

Age

25

–5

y

Elit

eM

atc

h21.4

819.6

00.9

10.1

8Lik

ely

triv

ial

8.4

91.4

0.2

Ekstr

and

etal.

[13]

154

fem

ale

s

Age

23

–4

y

Elit

eM

atc

h12.5

114.8

81.1

90.4

0U

ncle

ar;

get

more

data

1.6

65.3

33.1

Fulle

retal.

[19]

Fem

ale

s

2005

season:

64

team

s

2006

season:

72

team

s

No

age

data

Colle

gia

teT

rain

ing

2.7

92.6

00.9

30.1

5V

ery

likely

triv

ial

2.6

97.3

0.1

Fulle

retal.

[19]

Male

s

2005

season:

52

team

s

2006

season:

54

team

s

No

age

data

Colle

gia

teT

rain

ing

3.0

13.3

41.1

10.1

6V

ery

likely

triv

ial

0.0

96.9

3.1

Continued

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Tab

leI.

Contd

Stu

dy

No.ofsubje

cts

or

team

s,gender

and

age

(mean

–S

Dor

range

y)

Levelof

perf

orm

ance

Tra

inin

g

or

matc

h

inju

ries

Incid

ence

(n/1

000

hexposure

)

Incid

ence

rate

ratio

a

90

%C

I

Clin

icalin

fere

nce

Lik

elih

ood

(%)

thattr

ue

valu

eofth

e

eff

ectsta

tistic

is:

natu

ral

turf

art

ific

ial

turf

substa

ntially

beneficia

l

triv

ial

substa

ntially

harm

ful

Bjo

rneboe

etal.

[16]

Male

s

14

team

s

No

age

data

Elit

eT

rain

ing

1.8

01.9

01.0

70.1

9V

ery

likely

triv

ial

0.1

96.5

3.4

Ekstr

and

etal.

[13]

613

male

s

Age

25

–5

y

Elit

eT

rain

ing

3.4

73.5

21.0

20.1

6V

ery

likely

triv

ial

0.2

99.2

0.6

Aokie

tal.

[7]

301

pla

yers

Age

15

–2

y

No

gender

data

Uncle

ar

Tra

inin

g4.4

73.8

01.1

80.1

9Lik

ely

triv

ial

0.0

83.6

16.4

Ste

ffen

etal.

[15]

2020

fem

ale

s

Age

15

–1

y

Regio

nal

Tra

inin

g1.2

01.2

01.0

00.4

0P

ossib

lytr

ivia

l13.1

73.8

13.1

Ekstr

and

etal.

[18]

290

male

s

Age

25

–5

y

Elit

eT

rain

ing

2.9

42.4

20.8

20.2

2P

ossib

ly

beneficia

l;use

34.6

65.2

0.2

Ekstr

and

etal.

[13]

154

fem

ale

sA

ge

23

–4

yE

lite

Tra

inin

g2.7

92.9

11.0

40.4

4P

ossib

lytr

ivia

l11.3

70.2

18.5

Am

eri

can

foo

tball

Meyers

[11]

465

gam

es

No

gender

or

age

data

Colle

gia

teM

atc

h51.2

0b

45.7

0b

0.8

90.0

3M

ostlik

ely

triv

ial

0.0

100.0

0.0

Meyers

and

Barn

hill

[20]

240

gam

es

No

gender

or

age

data

Hig

hschool

Matc

h13.9

0b

15.2

0b

1.0

90.1

6V

ery

likely

triv

ial

0.0

97.5

2.5

Ru

gb

y

Fulle

retal.

[21]

282

male

s

129

backs,age

26

–4

y

153

forw

ard

s,

age

27

–6

y

Com

munity

Matc

h26.9

038.2

01.4

20.5

6P

ossib

lyharm

ful;

don’t

use

0.4

34.8

64.8

Fulle

retal.

[21]

169

male

s

85

backs,age

25

–4

y

84

forw

ard

s,age

26

–8

y

Elit

eT

rain

ing

2.3

03.0

01.3

30.5

4P

ossib

lyharm

ful;

don’t

use

1.1

45.1

53.8

aIn

cid

ence

rate

ratio

for

inju

ryin

cid

ence

on

art

ific

ialand

natu

raltu

rfsurf

aces,usin

gnatu

raltu

rfas

the

refe

rence

gro

up.

bIn

cid

ence

giv

en

as

inju

ries

per

ten

team

gam

es

=(n

ofin

juries

/nofte

am

gam

es)

·10.

~in

dic

ate

sappro

xim

ate

ly.



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used to determine the likelihood that the truemagnitude of the effect was substantial in a bene-ficial or harmful way. An incidence rate ratio of0.77 represented a substantial benefit of playingon artificial turf, while an incidence rate ratio of1.30 indicated that it was substantially harmful toplay on artificial turf.[22] These thresholds werechosen as they correspond approximately to thethresholds for standardized differences in means(0.20, 0.60, 1.2, 2.0 and 4.0) of the log of time toinjury in the two groups.[23] When investigatingpotential mechanisms, the standardized differencebetween means for the variable on each surfacewas used, with thresholds of –0.2 used to deter-mine a meaningful difference.[22] Where a studyreported a p-value as ‘p< 0.05’, ‘p= 0.05’ was usedin the analysis.Where a rate ratio was reportedwithconfidence limits, inferences were calculated using aspreadsheet for combining independent groups,with a weighting factor of one for the effect.[24] Aneffect was clinically unclear if there was a >25%likelihood that the true value was beneficial, withodds of benefit relative to odds of harm (odds ratio)<66. The effect was otherwise clinically clear: bene-ficial if the likelihood of benefit was >25%, andtrivial or harmful for other outcomes, depending onthe observed value. The likelihood that an effectwas substantially harmful, trivial or beneficial wasgiven in plain language terms[10] using the followingscale: 0–0.5%, most unlikely; 0.6–5.0%, very un-likely; 5.1–25.0%, unlikely; 25.1–75.0%, possible;75.1–95.0%, likely; 95.1–99.5%, very likely; and99.6–100%, most likely.[25]

3. Findings

3.1 Types of Natural and Artificial SurfacesUsed by Football Codes

Football codes use two main types of surfaces:natural (grass) turf or artificial surfaces. The per-formance of either type of surface is dependentupon their structural characteristics, response tophysical wear (e.g. shoe-surface interaction andfrequency of use) and environmental exposure(e.g. sun and rain). Ekstrand and Nigg[1] suggestedthat 24% of soccer injuries could be attributed tounsatisfactory playing surfaces.

Many species of grass may be used for naturalturf surfaces in sport, all of which possess differentproperties pertaining to shoe-surface traction.[26]

Natural turf’s response towear is determined by thespecies of grass, surface compaction and drainageability.[27] Properties of natural turf surfaces thatmay be connected with injury prevalence includeinappropriate friction characteristics, hardness andbeing uneven.[1] Natural turf requires considerablemaintenance throughout the year, including mow-ing, fertilizing, irrigation, aeration, reseeding andcontrol against pests, weeds and disease.[6]

The structure of artificial turf has developedsince the initial use of first generation Astroturf�in the late 1960s.[28] Astroturf� consisted of a shortgrass fibre carpet on top of padding over concreteand possessed increased stiffness, heat retentionand sliding friction in comparison to natural grasssurfaces.[6] Second generation turfs, developed inthe late 1980s, were characterized by longer, thickerfibres (22–25mm), sand fillings and a rubber baseunder the turf itself to reduce stiffness.[15] A thirdgeneration of turf with longer fibres (50–60mm)and a sand and/or rubber infill was designed forsoccer and is believed to more accurately mimic thecharacteristics of natural turf.[29] Fieldturf (a fourthgeneration turf) infill consists of a bottom layer ofsilica sand, a middle layer that is a combination ofcryogenic rubber and sand and a top layer of rub-ber.[30] No studies to date have compared injuryrisk on third versus fourth generation turfs.

Artificial turfs possess various advantagesover natural turfs, including lower maintenancecosts, greater utility and the ability to be used inclimates where the development of natural turf isdifficult.[18] Use of artificial turf has grown con-siderably in recent years with its use in matchesapproved by the Federation Internationale deFootball Association (FIFA),[31] as well as by theInternational Rugby Union.[6] Artificial turf isalso used in over one-third of the stadiums for theUS National Football League.[32]

3.2 Incidence and Nature of Injury as a Resultof Playing on Natural Turf or Artificial Turf

The incidence rate ratio for injuries on artifi-cial and natural turf surfaces, using natural turf

908 Williams et al.


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as the reference, ranged from 0.82 to 1.42, withthe highest rate ratio for rugby (table I). Trivialeffects for the injury rate between surfaces wereshown by 16 of the 20 cohorts, with 13 cohortsshowing trivial percentage likelihoods over 90%.However, our analysis of Fuller et al.’s study[21]

resulted in the discovery of possibly harmful ef-fects for rugby union athletes playing matchesand training on artificial turf. Conversely, anal-ysis of Ekstrand et al.’s study resulted in the dis-covery of a possibly beneficial effect for elite malesoccer players in training but not matches.[18] Gi-ven the possible harmful effects for rugby versussoccer on artificial turf, further research is neededto investigate the mechanisms that may underliethese differences in order to reduce the risk of in-jury when playing rugby on artificial turf.

3.2.1 Ankle Injury

Our analyses showed evidence for an increasedrisk of incurring an ankle injury when playing onartificial turf in 8 of the 14 cohorts, with incidencerate ratios from 0.71 to 5.20 (see table II). How-ever, none of the percentage of likelihood cate-gories had values >95% (very likely harmful).Evidence of a harmful effect of incurring ankleinjuries whilst playing soccer on artificial turf wasfound for elite males in matches and train-ing,[13,16,18] elite females in training,[13] collegiatemales in training[19] and young females duringmatches.[15] A trivial effect was calculated for fe-male soccer players in training[19] and collegiatemale soccer players during matches.[17] Con-versely, a beneficial effect was inferred for soccermatches involving youths[14] and collegiate fe-males (unlike the trivial effect during training).[17]

A likely harmful effect was calculated for rugbyunion match injuries.[21] Unclear effects were cal-culated for elite female soccer matches[13] and elitemale soccer training.[18] Given the likely increasedrisk of incurring an ankle injury on artificial turf,injury prevention strategies to prevent ankle in-jury must be a priority for soccer players whotrain and play matches on artificial turf regularly.

3.2.2 Knee Injury

Overall, the evidence concerning the risk ofknee injuries on the two surfaces was inconsistent

with incidence rate ratios from 0.4 to 2.8 (seetable II). An unclear inference was made across6[11,13,17,18] of the 16 cohorts analysed. A likelybeneficial inference was calculated for high schoolAmerican footballers[20] (the only likelihood over90% for knee injuries), and a possibly beneficialeffect was calculated for female collegiate soccerplayers in training.[19] A likely harmful effect wasinferred for community-level male rugby unionplayers during matches[21] and young femalesoccer players in matches,[15] while a possiblyharmful effect was calculated for elite male soccerplayers in matches.[16] Trivial effects were inferredfor male and female collegiate soccer playersduring matches,[17] male collegiate soccer playersduring training,[19] youth soccer players[14] andelite male soccer players in training.[13] Given theinconsistencies in incidence rate ratios dependingon the sport, gender of athlete or match versustraining, more research is required to elucidate theeffect of surface type on knee injuries.

3.2.3 Muscle Strains

Two cohorts[15,18] showed beneficial inferencesover the 90% likelihood value for the effect ofartificial surface on muscle injuries for soccerplayers (see table II). A likely beneficial effect wasalso calculated for elite male soccer players inmatches,[18] while possibly beneficial effects werecalculated for three other soccer cohorts.[13] Highschool American footballers[20] had likely harm-ful inferences and elite rugby union players hadpossibly harmful inferences during training.[21]

Given the six beneficial, two harmful, four un-clear and five trivial inferences across the threesports, more research is needed to clarify the ef-fect of artificial surfaces on muscle strain injury,particularly given soccer players may have a re-duced risk of muscle strain injury on artificial sur-faces compared with American football or rugby.

3.2.4 Injury Severity

Many reviewed studies attempted to quantifyand describe differences between surfaces withregards to the varying degrees of injury severity(see table III). However, the range of definitionsused to describe severity made comparisons be-tween studies difficult. Ekstrand et al.,[13,18] Fuller



This material is


original publisher.


and distribution

is prohibited.

Tab

leII

.S

tudy

chara

cte

ristics,

inju

red

body

part

or

inju

ryty

pe,

incid

ence

ofin

juries,

incid

ence

rate

ratios

and

90

%confidence

inte

rvals

,and

perc

enta

ge

likelih

oods

for

beneficia

l,

triv

ialo

rharm

fuleff

ects

when

com

paring

inju

ryin

cid

ence

on

art

ific

ialand

natu

raltu

rfs

surf

aces

for

soccer,

rugby

unio

nand

Am

erican

footb

all

Stu

dy

No.ofsubje

cts

or

team

s,gender

and

age

(mean

–S

Dor

range

y)

Levelof

perf

orm

ance

Tra

inin

gor

matc

h

inju

ries

Inju

red

body

part

or

inju

ry

type

Incid

ence

(n/1

000

hexposure

)

Incid

ence

rate

ratio

a

90

%C

I

Clin

icalin

fere

nce

Lik

elih

ood

(%)

thattr

ue

valu

eofth

e

eff

ectsta

tistic

is:

natu

ral

turf

art

ific

ial

turf

substa

ntially

beneficia

l

triv

ial

substa

ntially

harm

ful

So

ccer

Ekstr

and

etal.

[18]

492

male

s

Age

25

–5

y

Elit

eM

atc

hA

nkle

2.6

64.8

31.8

10.9

4Lik

ely

harm

ful;

don’t

use

0.2

13.5

86.3

Knee

2.6

62.0

70.7

80.4

9U

ncle

ar;

get

more

data

48.5

43.6

7.9

Muscle

str

ain

6.1

63.7

60.6

00.2

5Lik

ely

beneficia

l;

use

83.9

16.0

0.1

Solig

ard

etal.

[14]

~60

000

pla

yers

(~one-t

hird

were

fem

ale

)

Age

13–19

y

Regio

nal

Matc

hA

nkle

8.4

04.3

00.5

90.2

0Lik

ely

beneficia

l;

use

90.6

9.4

0.0

Knee

5.6

04.6

00.9

60.3

2Lik

ely

triv

ial

13.3

80.3

6.4

Muscle

str

ain

3.0

02.2

00.8

80.4

3U

ncle

ar;

get

more

data

31.8

59.8

8.4

Bjo

rneboe

etal.

[16]

Male

s

14

team

s

No

age

data

Elit

eM

atc

hA

nkle

2.2

03.1

01.3

90.5

5P

ossib

lyharm

ful;

don’t

use

0.6

38.2

61.3

Knee

2.0

03.0

01.4

60.5

9P

ossib

lyharm

ful;

don’t

use

0.4

30.9

68.7

Muscle

str

ain

5.1

04.5

00.8

80.2

8P

ossib

lytr

ivia

l23.6

74.5

1.8

Fulle

r

etal.

[17]

Colle

gia

tem

ale

s

2005

season:52

team

s

2006

season:54

team

s

No

age

data

Colle

gia

teM

atc

hA

nkle

4.5

74.5

91.0

00.3

3Lik

ely

triv

ial

9.1

81.8

9.1

Knee

3.0

93.7

51.2

10.4

0U

ncle

ar;

get

more

data

1.1

63.2

35.7

Muscle

str

ain

6.4

75.7

00.8

80.2

5Lik

ely

triv

ial

21.8

77.0

1.2

Fulle

r

etal.

[17]

Colle

gia

tefe

male

s

2005

season:64

team

s

2006

season:72

team

s

No

age

data

Colle

gia

teM

atc

hA

nkle

4.2

13.0

00.7

10.2

8P

ossib

ly

beneficia

l;use

63.4

36.1

0.5

Knee

4.9

44.8

60.9

80.3

1Lik

ely

triv

ial

9.9

83.5

6.6

Muscle

str

ain

3.1

73.5

71.1

30.4

2U

ncle

ar;

get

more

data

4.1

69.5

26.4

Ste

ffen

etal.

[15]

2020

fem

ale

s

Age

15

–1

y

Regio

nal

Matc

hA

nkle

3.0

04.0

01.4

00.5

0P

ossib

lyharm

ful;

don’t

use

0.2

35.6

64.2

Knee

1.1

01.9

01.7

00.8

0Lik

ely

harm

ful;

don’t

use

0.3

17.3

82.4

Muscle

str

ain

1.5

00.6

00.4

00.3

0Lik

ely

beneficia

l;

use

93.4

6.3

0.3

Continued

nextpage

910 Williams et al.


This material is


original publisher.


and distribution

is prohibited.

Tab

leII

.C

ontd

Stu

dy

No.ofsubje

cts

or

team

s,gender

and

age

(mean

–S

Dor

range

y)

Levelof

perf

orm

ance

Tra

inin

gor

matc

h

inju

ries

Inju

red

body

part

or

inju

ry

type

Incid

ence

(n/1

000

hexposure

)

Incid

ence

rate

ratio

a

90

%C

I

Clin

icalin

fere

nce

Lik

elih

ood

(%)

thattr

ue

valu

eofth

e

eff

ectsta

tistic

is:

natu

ral

turf

art

ific

ial

turf

substa

ntially

beneficia

l

triv

ial

substa

ntially

harm

ful

Ekstr

and

etal.

[13]

154

fem

ale

s

Age

23

–4

y

Elit

eM

atc

hA

nkle

2.6

32.8

91.1

00.9

0U

ncle

ar;

get

more

data

21.5

43.0

35.6

Knee

2.3

03.5

51.5

41.2

6U

ncle

ar;

get

more

data

6.4

29.1

64.5

Muscle

str

ain

2.9

63.5

51.2

00.8

9U

ncle

ar;

get

more

data

14.3

43.4

42.4

Ekstr

and

etal.

[13]

613

male

s

Age

25

–5

y

Elit

eM

atc

hA

nkle

3.5

34.8

01.3

60.4

1P

ossib

lyharm

ful;

don’t

use

0.1

40.1

59.8

Knee

4.3

44.6

21.0

60.3

0Lik

ely

triv

ial

3.1

85.2

11.7

Muscle

str

ain

7.4

45.3

20.7

20.1

7P

ossib

ly

beneficia

l;use

67.7

32.3

0.0

Ekstr

and

etal.

[18]

492

male

s

Age

25

–5

y

Elit

eT

rain

ing

Ankle

0.3

30.5

31.6

11.3

0U

ncle

ar;

get

more

data

5.0

26.7

68.3

Knee

0.3

30.3

10.9

50.8

3U

ncle

ar;

get

more

data

33.0

41.2

25.7

Muscle

str

ain

1.3

10.6

20.4

80.2

2V

ery

likely

beneficia

l;use

95.9

4.1

0.0

Fulle

r

etal.

[19]

Colle

gia

tem

ale

s

2005

season:52

team

s

2006

season:54

team

s

No

age

data

Colle

gia

teT

rain

ing

Ankle

0.5

80.8

31.4

40.4

1P

ossib

lyharm

ful;

don’t

use

0.0

27.4

72.6

Knee

0.4

30.4

20.9

90.3

8P

ossib

lytr

ivia

l13.6

74.6

11.8

Muscle

str

ain

1.1

61.2

61.0

80.2

4Lik

ely

triv

ial

0.6

90.9

8.5

Fulle

r

etal.

[19]

Colle

gia

tefe

male

s

2005

season:64

team

s

2006

season:72

team

s

No

age

data

Colle

gia

teT

rain

ing

Ankle

0.4

50.4

51.0

00.4

0P

ossib

lytr

ivia

l13.5

73.0

13.5

Knee

0.5

40.4

00.7

40.3

1P

ossib

ly

beneficia

l;use

56.3

42.6

1.1

Muscle

str

ain

1.2

11.0

40.8

60.2

2Lik

ely

triv

ial

23.1

76.6

0.3

Ekstr

and

etal.

[13]

154

fem

ale

s

Age

23

–4

y

Elit

eT

rain

ing

Ankle

0.1

50.7

65.2

013.3

7Lik

ely

harm

ful;

don’t

use

3.0

5.6

91.3

Knee

0.2

90.5

61.9

02.9

6U

ncle

ar;

get

more

data

11.2

19.3

69.5

Muscle

str

ain

1.6

21.0

00.6

20.3

8P

ossib

ly

beneficia

l;use

73.1

25.2

1.7

Continued

nextpage



This material is


original publisher.


and distribution

is prohibited.

Tab

leII

.C

ontd

Stu

dy

No.ofsubje

cts

or

team

s,gender

and

age

(mean

–S

Dor

range

y)

Levelof

perf

orm

ance

Tra

inin

gor

matc

h

inju

ries

Inju

red

body

part

or

inju

ry

type

Incid

ence

(n/1

000

hexposure

)

Incid

ence

rate

ratio

a

90

%C

I

Clin

icalin

fere

nce

Lik

elih

ood

(%)

thattr

ue

valu

eofth

e

eff

ectsta

tistic

is:

natu

ral

turf

art

ific

ial

turf

substa

ntially

beneficia

l

triv

ial

substa

ntially

harm

ful

Ekstr

and

etal.

[13]

613

male

s

Age

25

–5

y

Elit

eT

rain

ing

Ankle

3.2

44.4

51.3

70.4

3P

ossib

lyharm

ful;

don’t

use

0.1

38.9

61.0

Knee

3.8

33.9

91.0

40.3

2Lik

ely

triv

ial

4.9

84.1

11.0

Muscle

str

ain

1.3

91.1

30.8

10.2

1P

ossib

ly

beneficia

l;use

37.1

62.8

0.1

Ru

gb

y

Fulle

r

etal.

[21]

282

male

s

129

backs

Age

26

–4

y

153

forw

ard

s

Age

27

–6

y

Com

munity

Matc

hA

nkle

n=

1n

=5

3.8

211.1

9Lik

ely

harm

ful;

don’t

use

7.2

9.1

83.7

Knee

n=

3n

=11

2.8

03.6

2Lik

ely

harm

ful;

don’t

use

2.4

9.6

88.0

Muscle

str

ain

35.7

0b

32.7

0b

0.9

20.4

8U

ncle

ar;

get

more

data

28.1

58.8

13.1

Fulle

r

etal.

[21]

169

male

s

85

backs

Age

25

–4

y

84

forw

ard

s

Age

26

–8

y

Elit

eT

rain

ing

Muscle

str

ain

51.4

0b

66.7

0b

1.3

00.3

6P

ossib

lyharm

ful;

don’t

use

0.1

49.9

50.0

Am

eri

can

foo

tball

Meyers

and

Barn

hill

[20]

240

hig

hschoolg

am

es

No

gender

or

age

data

Hig

hschool

Matc

hK

nee

1.0

0c

0.4

0c

0.4

00.3

5Lik

ely

beneficia

l;

use

91.3

8.0

0.7

Muscle

str

ain

1.1

0c

2.1

0c

1.9

11.0

9Lik

ely

harm

ful;

don’t

use

0.3

12.0

87.7

Meyers

[11]

465

colle

gia

tegam

es

were

evalu

ate

d

No

gender

or

age

data

Colle

gia

teM

atc

hK

nee

1.3

0c

1.0

0c

0.7

70.3

7U

ncle

ar;

get

more

data

50.0

47.0

3.0

Muscle

str

ain

7.2

0c

6.2

0c

0.8

60.0

9Lik

ely

triv

ial

5.1

94.9

0.0

aIn

cid

ence

rate

ratio

for

inju

ryin

cid

ence

on

art

ific

ialand

natu

raltu

rfsurf

aces,usin

gnatu

raltu

rfas

the

refe

rence

gro

up.

bIn

cid

ence

giv

en

as

pro

port

ion

(%)

ofin

juries.

cIn

jury

incid

ence

rate

=(n

ofin

juries

/tota

ln

ofin

juries)

·10.

~in

dic

ate

sappro

xim

ate

ly.

912 Williams et al.


This material is


original publisher.


and distribution

is prohibited.

et al.[17,19] and Soligard et al.[14] divided injuriesinto four categories of severity according to thelength of absence from matches and training ses-sions: slight (1–3 days); minor (4–7 days); mod-erate (8–28 days); and severe (>28 days). Fulleret al.,[21] in a study of rugby union match injuries,also used this set of definitions, except for quan-tifying a slight injury as one that caused 2–3 daysof time loss. Steffen et al.,[15] Fuller et al.[21] andBjorneboe et al.[16] used three categories of severity:minor (1–7 days); moderate (8–21 days); and severe(>21 days). Meyers[11] and Meyers and Barnhill[20]

used comparable definitions: minor (0–6 days);moderate (7–21 days); and severe (>22 days).

The difference in incidence of slight injuriesbetween natural and artificial surfaces was as-sessed as likely trivial for female collegiate soccerplayers during matches,[17] and possibly harmfulfor the same group during training.[19] A likelytrivial effect was calculated for elite male soccerplayers in training and matches.[13] A likely trivialinference was also calculated for male collegiatesoccer players during matches,[17] while a possiblybeneficial difference was calculated for this co-hort during training.[19] A possibly beneficial ef-fect was calculated for elite male soccer players.[18]

Unclear effects were calculated in five co-horts.[13,14,18,21] No harmful effects were calcu-lated in any of the soccer cohorts, suggesting thatartificial turf does not have a negative influencefor slight injury. More studies are required toclarify the effect of surface for rugby union.

For minor injuries, our analysis showed trivialresults in 6 of the 17 cohorts: namely, collegiatemale soccer matches,[17] collegiate American foot-ballers[11] and elite male soccer players in trainingand matches.[13,16,18] A likely beneficial inferencewas made for collegiate female soccer players intraining and matches,[17,19] while a possibly bene-ficial effect was inferred for young female soccerplayers.[15] A very likely harmful effect was calcu-lated for minor injuries in training within a cohortof rugby union players,[21] while a likely harmfuleffect was found for male collegiate soccer playersparticipating in training.[19] An unclear inferencewas made for rugby union match injuries,[21] highschool American football games,[20] elite femalesoccer players in matches and training,[13] elite

male soccer matches[18] and youth level soccerplayers.[14] The inconsistent results preclude a clearconclusion with respect to minor injuries.

Evidence concerning moderate injuries wassimilarly mixed, with trivial effects calculatedfor 7 of the 17 cohorts,[13,15-19] while possiblyharmful inferences were made for 2 cohorts.[19,21]

Conversely, a likely beneficial inference was cal-culated for elite soccer players,[18] collegiateAmerican footballers[11] and youth soccer play-ers,[14] while a possibly beneficial inference wasmade for male collegiate soccer players duringmatches.[17] An unclear inference was made forhigh school American football games,[20] rugbytraining,[21] and elite female soccer players inmatches and training.[13] There appears to be noclear pattern for moderate injury severity.

For severe injury, a very likely harmful infer-ence was calculated for young female soccerplayers.[15] A possibly harmful inference wasmade for collegiate males during matches[17] andelite male soccer players in matches.[16] A likelytrivial effect was calculated for female collegiatesoccer players in training.[19] Likely beneficialinferences were calculated for both the Americanfootball cohorts[11,20] and elite males in soccermatches,[13] while clinically unclear inferences weremade in the remaining ten cohorts.[13,14,17-19,21] Themajority of unclear references suggest there is noclear pattern, although the very likely harmful in-ference poses questions regarding the role of arti-ficial turf in the aetiology of severe injuries foryoung female soccer players.

Inferences made relating to severities of injurywere inconsistent across cohorts, although certainfindings warrant further investigation; namely,the very likely harmful effects calculated forminor injuries in rugby union training[21] and forsevere injuries in young female soccer players.[15]

3.3 Mechanisms and Risk Factors for Injuryon Artificial and Natural Turf

Whiting and Zernicke[33] defined injury me-chanism as ‘‘the fundamental physical processresponsible for a given action, reaction or result’’(i.e. the mechanism of injury is the physical actionor cause of injury). Mechanisms of injury are



This material is


original publisher.


and distribution

is prohibited.

Tab

leII

I.S

tudy

chara

cte

ristics,in

jury

severity

,in

cid

ence

ofin

juries,in

cid

ence

rate

ratios

and

90

%confidence

inte

rvals

,and

perc

enta

ge

likelih

oods

for

beneficia

l,tr

ivia

lor

harm

ful

eff

ects

when

com

paring

inju

ryin

cid

ence

on

art

ific

ialand

natu

raltu

rfs

surf

aces

for

soccer,

rugby

unio

nand

Am

erican

footb

all

Stu

dy

No.ofsubje

cts

or

team

s,gender

and

age

(mean

–S

Dor

range

y)

Levelof

perf

orm

ance

Tra

inin

g

or

matc

h

inju

ries

Inju

ry

severity

(d)

Inci

dence

(n/1

000

hexp

osu

re)

Incid

ence

rate

ratio

a

90

%C

I

Clin

icalin

fere

nce

Lik

elih

ood

(%)

thattr

ue

valu

eofth

e

eff

ectsta

tistic

is:

natu

ral

turf

art

ific

ial

turf

substa

ntially

beneficia

l

triv

ial

substa

ntially

harm

ful

So

ccer

Fulle

r

etal.

[17]

Male

s

2005

season:52

team

s

2006

season:54

team

s

No

age

data

Colle

gia

teM

atc

hS

light(1–3)

7.8

08.3

41.0

70.2

6Lik

ely

triv

ial

1.2

89.6

9.2

Min

or

(4–7)

6.9

17.3

71.0

70.2

8Lik

ely

triv

ial

1.7

87.9

10.4

Modera

te

(8–28)

6.1

95.0

00.8

10.2

5P

ossib

ly

beneficia

l;use

39.1

60.4

0.5

Severe

(>28)

2.8

14.1

71.4

90.5

3P

ossib

lyharm

ful;

don’t

use

0.1

26.0

73.9

Fulle

r

etal.

[17]

Fem

ale

s

2005

season:64

team

s

2006

season:72

team

s

No

age

data

Colle

gia

teM

atc

hS

light(1–3)

6.3

66.2

90.9

90.2

7Lik

ely

triv

ial

6.0

89.3

4.7

Min

or

(4–7)

6.2

53.8

60.6

20.2

1Lik

ely

beneficia

l;

use

85.2

14.8

0.0

Modera

te

(8–28)

3.9

24.1

41.0

60.3

6Lik

ely

triv

ial

5.8

78.3

15.9

Severe

(>28)

4.7

54.0

00.8

40.2

8U

ncle

ar;

get

more

data

33.0

65.5

1.5

Ekstr

and

etal.

[18]

492

male

s

Age

25

–5

y

Elit

eM

atc

hS

light(1–3)

5.8

34.9

70.8

50.3

4U

ncle

ar;

get

more

data

33.6

62.8

3.6

Min

or

(4–7)

6.6

66.0

70.9

10.3

4P

ossib

lytr

ivia

l22.3

72.4

5.3

Modera

te

(8–28)

6.8

36.3

50.9

30.3

4Lik

ely

triv

ial

18.9

75.1

6.0

Severe

(>28)

2.1

62.2

11.0

20.6

7U

ncle

ar;

get

more

data

22.5

51.7

25.8

Ekstr

and

etal.

[13]

613

male

s

Age

25

–5

y

Elit

eM

atc

hS

light(1–3)

6.4

17.3

41.1

50.2

7Lik

ely

triv

ial

0.2

80.6

19.2

Min

or

(4–7)

6.1

96.1

30.9

90.2

4Lik

ely

triv

ial

4.4

92.3

3.3

Modera

te

(8–28)

6.6

36.0

70.9

20.2

2Lik

ely

triv

ial

10.6

88.6

0.8

Severe

(>28)

2.3

61.9

70.8

30.3

5U

ncle

ar;

get

more

data

38.0

58.5

3.5

Continued

nextpage

914 Williams et al.


This material is


original publisher.


and distribution

is prohibited.

Tab

leII

I.C

ontd

Stu

dy

No.ofsubje

cts

or

team

s,gender

and

age

(mean

–S

Dor

range

y)

Levelof

perf

orm

ance

Tra

inin

g

or

matc

h

inju

ries

Inju

ry

severity

(d)

Inci

dence

(n/1

000

hexp

osu

re)

Incid

ence

rate

ratio

a

90

%C

I

Clin

icalin

fere

nce

Lik

elih

ood

(%)

thattr

ue

valu

eofth

e

eff

ectsta

tistic

is:

natu

ral

turf

art

ific

ial

turf

substa

ntially

beneficia

l

triv

ial

substa

ntially

harm

ful

Ekstr

and

etal.

[13]

154

fem

ale

s

Age

23

–4

y

Elit

eM

atc

hS

light(1–3)

3.9

54.8

91.2

40.7

8U

ncle

ar;

get

more

data

9.8

46.0

44.8

Min

or

(4–7)

2.6

34.0

01.5

21.1

5U

ncle

ar;

get

more

data

5.4

30.3

66.8

Modera

te

(8–28)

2.9

64.4

41.5

01.0

7U

ncle

ar;

get

more

data

4.8

31.3

63.9

Severe

(>28)

2.9

61.5

51.5

20.4

8Lik

ely

beneficia

l;

use

78.4

18.3

3.3

Solig

ard

etal.

[14]

~60

000

pla

yers

(~one-t

hird

were

fem

ale

)

Age

13–19

y

Regio

nal

Matc

hS

light(1–3)

2.7

02.8

01.1

20.5

1U

ncle

ar;

get

more

data

8.1

63.0

28.9

Min

or

(4–7)

0.7

01.0

01.5

01.1

9U

ncle

ar;

get

more

data

6.5

30.8

62.7

Modera

te

(8–28)

0.7

00.2

00.2

80.7

0Lik

ely

beneficia

l;

use

84.3

9.4

6.3

Severe

(>28)

0.4

00.2

00.4

91.2

5U

ncle

ar;

get

more

data

67.2

16.0

16.7

Fulle

r

etal.

[19]

Male

s

2005

season:52

team

s

No

age

data

Colle

gia

teT

rain

ing

Slig

ht(1–3)

1.2

71.0

30.8

10.1

9P

ossib

ly

beneficia

l;use

39.2

60.8

0.0

Min

or

(4–7)

0.6

20.9

71.5

80.4

2Lik

ely

harm

ful;

don’t

use

0.0

11.3

88.7

Modera

te

(8–28)

0.5

90.8

51.4

40.4

1P

ossib

lyharm

ful;

don’t

use

0.0

27.4

72.6

Severe

(>28)

0.5

20.4

10.7

90.3

1U

ncle

ar;

get

more

data

45.4

53.1

1.5

Ekstr

and

etal.

[18]

492

male

s

Age

25

–5

y

Elit

eT

rain

ing

Slig

ht(1–3)

1.0

90.7

40.6

80.3

2P

ossib

ly

beneficia

l;use

67.4

31.7

0.9

Min

or

(4–7)

0.5

40.6

41.1

80.7

5U

ncle

ar;

get

more

data

11.9

48.7

39.4

Modera

te

(8–28)

1.0

90.6

80.6

30.3

0Lik

ely

beneficia

l;

use

76.0

23.5

0.5

Severe

(>28)

0.2

20.3

51.6

11.6

7U

ncle

ar;

get

more

data

9.0

25.9

65.1

Continued

nextpage



This material is


original publisher.


and distribution

is prohibited.

Tab

leII

I.C

ontd

Stu

dy

No.ofsubje

cts

or

team

s,gender

and

age

(mean

–S

Dor

range

y)

Levelof

perf

orm

ance

Tra

inin

g

or

matc

h

inju

ries

Inju

ry

severity

(d)

Inci

dence

(n/1

000

hexp

osu

re)

Incid

ence

rate

ratio

a

90

%C

I

Clin

icalin

fere

nce

Lik

elih

ood

(%)

thattr

ue

valu

eofth

e

eff

ectsta

tistic

is:

natu

ral

turf

art

ific

ial

turf

substa

ntially

beneficia

l

triv

ial

substa

ntially

harm

ful

Fulle

r

etal.

[19]

Fem

ale

s

2005

season:64

team

s

2006

season:72

team

s

No

age

data

Colle

gia

teT

rain

ing

Slig

ht(1–3)

0.8

11.0

41.2

90.3

4P

ossib

lyharm

ful;

don’t

use

0.1

51.8

48.1

Min

or

(4–7)

0.6

80.3

60.5

30.2

3Lik

ely

beneficia

l;

use

92.6

7.4

0.0

Modera

te

(8–28)

0.5

40.4

90.9

10.3

5P

ossib

lytr

ivia

l22.9

71.3

5.8

Severe

(>28)

0.6

70.6

20.9

20.3

1Lik

ely

triv

ial

18.8

76.8

4.4

Ekstr

and

etal.

[13]

613

male

s

Age

25

–5

y

Elit

eT

rain

ing

Slig

ht(1–3)

1.0

81.1

61.0

80.3

1Lik

ely

triv

ial

2.4

83.6

14.0

Min

or

(4–7)

0.8

80.8

00.9

10.3

0Lik

ely

triv

ial

19.4

77.2

3.3

Modera

te

(8–28)

0.9

81.0

81.1

10.3

3Lik

ely

triv

ial

2.1

78.9

19.0

Severe

(>28)

0.4

90.4

00.8

30.3

7U

ncle

ar;

get

more

data

38.7

56.7

4.6

Ekstr

and

etal.

[13]

154

fem

ale

s

Age

23

–4

y

Elit

eT

rain

ing

Slig

ht(1–3)

0.8

80.7

90.9

00.7

3U

ncle

ar;

get

more

data

36.4

42.8

20.8

Min

or

(4–7)

0.8

80.8

81.0

00.8

0U

ncle

ar;

get

more

data

27.8

44.5

27.8

Modera

te

(8–28)

1.0

30.8

50.8

30.6

3U

ncle

ar;

get

more

data

42.9

42.7

14.4

Severe

(>28)

0.0

00.3

5N

AN

AU

ncle

ar;

get

more

data

––

–

Ste

ffen

etal.

[15]

2020

fem

ale

s

Age

15

–1

y

Regio

nal

Matc

hM

inor

(1–7)

4.0

02.7

00.7

00.2

8P

ossib

ly

beneficia

l;use

65.7

33.9

0.4

Modera

te

(8–21)

2.6

02.8

01.0

00.3

5Lik

ely

triv

ial

10.7

78.6

10.7

Severe

(>21)

1.7

03.3

02.0

00.7

5V

ery

likely

harm

ful;

don’t

use

0.0

2.6

97.4

Bjo

rneboe

etal.

[16]

Male

s

14

team

s

No

age

data

Elit

eM

atc

hM

inor

(1–7)

8.5

08.0

00.9

40.2

2Lik

ely

triv

ial

7.6

91.3

1.0

Modera

te

(8–21)

4.9

04.8

00.9

90.3

0Lik

ely

triv

ial

7.9

85.7

6.4

Severe

(>21)

3.6

04.8

01.3

40.4

2P

ossib

lyharm

ful;

don’t

use

0.1

43.4

56.5

Continued

nextpage

916 Williams et al.


This material is


original publisher.


and distribution

is prohibited.

Tab

leII

I.C

ontd

Stu

dy

No.ofsubje

cts

or

team

s,gender

and

age

(mean

–S

Dor

range

y)

Levelof

perf

orm

ance

Tra

inin

g

or

matc

h

inju

ries

Inju

ry

severity

(d)

Inci

dence

(n/1

000

hexp

osu

re)

Incid

ence

rate

ratio

a

90

%C

I

Clin

icalin

fere

nce

Lik

elih

ood

(%)

thattr

ue

valu

eofth

e

eff

ectsta

tistic

is:

natu

ral

turf

art

ific

ial

turf

substa

ntially

beneficia

l

triv

ial

substa

ntially

harm

ful

Ru

gb

y

Fulle

r

etal.

[21]

282

male

s

129

backs

Age

26

–4

y

153

forw

ard

s

Age

27

–6

y

Com

munity

Matc

hS

light(2–3)

2.9

03.7

01.2

71.9

3U

ncle

ar;

get

more

data

24.7

26.5

48.8

Min

or

(4–7)

7.7

08.1

01.0

50.8

9U

ncle

ar;

get

more

data

25.2

42.5

32.3

Modera

te

(8–28)

10.6

016.9

01.6

01.0

2P

ossib

lyharm

ful;

don’t

use

2.3

26.3

71.4

Severe

(>28)

5.8

09.6

01.6

61.5

0U

ncle

ar;

get

more

data

6.0

25.1

68.9

Fulle

r

etal.

[21]

169

male

s

85

backs

Age

25

–4

y

84

forw

ard

s

Age

26

–8

y

Elit

eT

rain

ing

Min

or

(1–7)

0.7

01.6

02.1

11.0

0V

ery

likely

harm

ful;

don’t

use

0.0

4.1

95.9

Modera

te

(8–21)

0.7

00.8

01.1

50.7

8U

ncle

ar;

get

more

data

14.9

47.5

37.6

Severe

(>21)

0.6

00.7

01.1

50.8

5U

ncle

ar;

get

more

data

16.7

44.9

38.4

Am

eri

can

foo

tball

Meyers

[11]

465

gam

es

No

gender

or

age

data

Colle

gia

teM

atc

hM

inor

(0–6)

39.9

0b

38.0

0b

0.9

50.0

2M

ostlik

ely

triv

ial

0.0

100.0

0.0

Modera

te

(7–21)

7.2

0b

5.0

0b

0.6

90.0

9Lik

ely

beneficia

l;

use

90.5

9.5

0.0

Severe

(>22)

4.1

0b

2.7

0b

0.6

60.1

5Lik

ely

beneficia

l;

use

87.0

13.0

0.0

Meyers

and

Barn

hill

[20]

240

gam

es

No

gender

or

age

data

Hig

hschool

Matc

hM

inor

(0–6)

10.7

0b

12.1

0b

1.1

3N

o

data

Uncle

ar;

get

more

data

––

–

Modera

te

(7–21)

1.3

0b

1.9

0b

1.4

6N

o

data

Uncle

ar;

get

more

data

––

–

Severe

(>22)

1.9

0b

1.1

0b

0.5

80.3

1Lik

ely

beneficia

l;

use

81.8

17.7

0.5

aIn

cid

ence

rate

ratio

for

inju

ryin

cid

ence

on

art

ific

ialand

natu

raltu

rfsurf

aces,usin

gnatu

raltu

rfas

the

refe

rence

gro

up.

bIn

cid

ence

giv

en

as

inju

ries

per

ten

team

gam

es

=(n

ofin

juries

/nofte

am

gam

es)

·10.

NA

=notapplic

able

;~

indic

ate

sappro

xim

ate

ly;–

indic

ate

sth

eeff

ectsta

tistics

could

notbe

calc

ula

ted.



This material is


original publisher.


and distribution

is prohibited.

usually multifactorial. Information on injurymechanisms must be considered in a model thatalso considers how internal and external risk fac-tors can modify injury risk.[34] Risk factors are,therefore, predisposing factors that combinedwiththe mechanism of injury may make an athletemore prone to injury. Artificial and natural turfinjuries are the result of many inter-relating fac-tors, some of which can be isolated to reduce in-jury risk. However, research-based interventionstrategies to reduce the injury risk are sparse.

3.3.1 Shoe-Surface Interface

The shoe-surface interface has been postulatedas a potential risk factor for differences in injurypatterns between surfaces. Orchard[26] suggestedthatmeasures to reduce shoe-surface traction, suchas ground watering and softening, play duringwinter months and player use of boots with shortercleats, would reduce the risk of injury. Villwocket al.[35] highlighted the potential for using shoeswith a more pliable upper, allowing more time forneuromuscular protectivemechanisms and therebyreducing injury risk. Unfortunately, few studieshave investigated changes in the shoe-surface in-terface using new generation artificial turfs or havecontrolled adequately for confounding variables,so limited quality evidence exists.

Peak Torque

A strong body of evidence exists to suggestthat a high peak torque between the shoe andplaying surface presents an injury risk to thelower extremity.[36-39] High frictional forces be-tween the foot and playing surface result in footfixation, which may be responsible for lower ex-tremity injuries.[40] We calculated a 99.9% like-lihood that peak torque was substantially higheron artificial turf from the results of a study byVillwock et al.[35] Significantly lower torque wasnoted in the turf cleat above all other groups. Theturf cleat pattern was described as ‘‘a dense pat-tern of short elastomeric cleats distributed overthe entire sole.’’ This study used a mobile testingapparatus with a surrogate leg to collect data, theaim being to investigate the shoe-surface inter-action of a number of shoes and surfaces currentlyemployed in soccer. Similarly, Livesay et al.[41]

reported higher peak torques on new generationartificial turf, although insufficient data wereprovided to allow us to make a magnitude-basedinference. Highest peak torques were developedby the grass shoe and third generation turf and theturf shoe and first generation turf combinations,with lowest peak torques developed on grass.This suggests that wearing appropriate footwearcould be an important injury prevention strategy.Higher speeds are generated in games played onsurfaces with greater traction, a factor that maybe responsible for differences in injury patterns.[26]

While larger peak torque forces on artificial turfmay be implicated in the aetiology of injuries, fur-ther in vivo human biomechanical analyses are re-quired to substantiate this observation.

Rotational Stiffness

Rotational stiffness is the rate at which torqueincreases with applied rotation at the shoe-surface interface,[41] and is a more sensitive mea-sure of the mechanical interaction between theshoe and surface than peak torque alone. Lowerrotational stiffness indicates a lower rate ofloading upon a joint andmay allowmore time fora protective form of neuromuscular control tostabilize the ankle and knee joints during cuttingmanoeuvres, potentially reducing the risk of in-jury.[35] We inferred a 99.8% likelihood that therotational stiffness measured by Villwock et al.[35]

was substantially higher on artificial turf. Vary-ing cleat patterns did not yield any differences inrotational stiffness in this study. A similar studyby Livesay et al.[41] suggested that the rotationalstiffness produced on new generation artificialturf did not differ significantly from that experi-enced on grass, and both turf shoes and grassshoes produced a similar initial rotational stiff-ness on third generation artificial turf and naturalturf. However, the compressive load used to col-lect the data was limited to a maximum of 511 N,which is much less than the weight of a typicalsoccer player and, therefore, reduces the externalvalidity of these results. We were unable to makea magnitude-based inference as insufficient datawere provided. The association between rota-tional stiffness and rate of loading upon lowerlimb joints warrants further investigation.

918 Williams et al.


This material is


original publisher.


and distribution

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3.3.2 Foot Loading

Foot loading patterns invoked during a cut-ting manoeuvre performed on artificial and nat-ural turf by American football players have beeninvestigated[32] using an in-shoe pressure dis-tribution-measuring insole. Natural grass pro-duced higher relative loads on the medial forefootand lateral midfoot, whilst on artificial turf, peakpressures within the central forefoot and lessertoe regions were higher. Larger lateral forces seenon artificial turf could indicate a greater degree offoot inversion[28] and may explain the higher in-cidence of ankle injuries seen in some of the co-horts discussed. Increased pressure of the medialforefoot on natural turf could potentially belinked to the ‘cleat-catch’ mechanism, which hasbeen implicated in the aetiology of knee ligamentinjuries,[28] but this was not observed in our anal-ysis of knee injuries on the two surfaces. Whilethese results are interesting, insufficient data wereprovided to allow any calculation of magnitude-based inferences.

3.3.3 Impact Attenuation

Impact attenuation describes how efficientlythe energy from an impact is absorbed.[42] In-sufficient impact attenuation is linked to an in-creased injury risk as a result of overloading intissues.[15] Theobald et al.[29] investigated the im-pact attenuation properties of six third genera-tion artificial turfs and a grass turf to assess therisk of incurring a mild traumatic brain injuryafter a head impact. A range of impact attenua-tion properties were reported across different ar-tificial surfaces, with fall heights ranging from0.46m to 0.77m causing a 10% mild traumaticbrain injury risk. Natural turf was the best per-former, requiring fall heights exceeding thoseachievable during games to reach 10% risk for amild traumatic brain injury. However, impactattenuation performance of natural turf appearedto be dependent on usage. Impact attenuation ofthe third generation turfs tested was independentof moisture content; hence, risk remained con-sistent in both dry and wet conditions. These re-sults led the authors to recommend the use ofthird generation turfs. However, the relationshipbetween surface impact attenuation properties

and incidence of injuries resulting from player-to-surface contact is yet to be investigated.

3.3.4 Physiological Response

Di Michele[43] compared blood lactate con-centrations and heart rate responses to an incre-mental running test (which was ended whenblood lactate concentration exceeded 4mmol/L)on third generation artificial turf, natural turfand a treadmill in youth soccer players. Runningspeed at the 4mmol/L threshold was substantiallylower (92.4% likelihood) on artificial turf. Run-ning on artificial turf at 10 km/h resulted in asignificantly higher heart rate, although the differ-ence between surfaces was trivial at the 4mmol/Lthreshold. Fatigue has been associated with an in-creased risk for injury[44] and players have reportedperceived greater physical effort to run on artificialturf.[45] Therefore, the apparent increased physio-logical cost of exercising on artificial turf may be acontributing mechanism to injury.

3.3.5 Gender

Agender differencemay exist for minor injuriessustained at soccer training given that femalesoccer players showed a likely beneficial inferencefor minor training injuries, whilst the equivalentmale group showed a likely harmful inference.There were no clear gender effects relating to anyother injury patterns given the lack of comparablecohorts.

3.3.6 Age

Our review included a number of age groups,ranging from youths (aged 12–17 years) throughto adult cohorts. The spread of age within singlestudies, coupled with the lack of information re-garding subject age in some studies, made anal-ysis difficult. Qualitative assessment did not showany clear patterns related to age.

3.3.7 Level of Performance

It was difficult to determine injury patterns thatmay vary by performance level given the smallnumber of studies: two studies used elite ath-letes;[18,21] two used junior regional athletes;[7,15]

one used high school athletes;[20] and three useduniversity/collegiate athletes.[11,17,19] Theoreti-cally, several factors relating to performance may



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predispose to differing injury patterns, such asplayer fitness, pitch quality (elite players are morelikely to play on a higher standard of surface),quality of officiating, incidence of foul play,differences in postural/joint integrity, muscu-loskeletal structure and biomechanics of move-ment. Assessment of the contribution of thesefactors needs to be addressed in well controlledstudies.

3.3.8 Training and Matches

Seven studies[13,15-19,21] provided data wheretraining versus match injuries could be com-pared. For overall injury incidence, a likely trivialinference was calculated for match injuries in-volving elite male soccer players, while a possiblybeneficial inference was made for training in-juries. For ankle injuries, the risk was likely tri-vial for collegiate male soccer players in matchesbut possibly harmful during training. For femalecollegiate soccer players, we calculated a possiblybeneficial effect during matches but a possiblytrivial effect for training. With respect to kneeinjuries, a difference was evident for collegiatefemales, with a likely trivial effect in matches buta possibly beneficial effect during training. Noclear differences existed between the match andtraining cohorts for muscle strain injuries. Insummary, no clear differences between naturaland artificial surfaces were evident in relation totraining versus match injuries. Potentially, theinferior impact attenuation properties of artificialturf[29] could contribute to the formation of microdamage and result in the development of chronicinjuries. The only study to investigate the devel-opment of chronic injuries on artificial turf wasby Aoki et al.,[7] who highlighted a higher inci-dence of lower back pain amongst adolescentsoccer players who trained on artificial turf. Giventhat exposure to a certain surface is often muchhigher for training as opposed to match play,[15] aninvestigation of the long-term risks associated withtraining on artificial turf is warranted.

3.3.9 Weather

The potential influence of weather conditionsupon injury risk on the two types of surface has re-ceived limited attention. Meyers and Barnhill[20]

reported an increased incidence of injuries duringAmerican high school football games on artificialturf during temperatures >70�F (or >21.1�C), anincrease calculated to be likely harmful. Thisfinding was similar to results reported on earliergeneration artificial turfs.[46] The authors sug-gested an increased shoe traction at higher turftemperature as a potential mechanism. These re-sults are in contrast to Meyers,[11] from which weinferred a 95.4% likelihood that injury incidenceon artificial turf was substantially lower on hotdays (>70�F or >21.1�C). These differing resultswere postulated to be due to the condition of thenatural turf used in each study, although exactdetails regarding the condition of the surfaceswere not provided. During play on wet fields, amost likely beneficial decrease in injuries oc-curred on artificial turf.[11] This concurred withlaboratory testing of the surfaces, in which im-pact attenuation properties of artificial turf werefound to be independent of moisture contrast,while natural turf varied depending on itsusage.[29] The more consistent nature of artificialturf may well be beneficial across varying weatherconditions, although these results are yet to beconfirmed in other football codes. How risk ofinjury on both forms of surface may change de-pending on the environmental conditions needsto be determined.

3.3.10 Changing between Surfaces

Rapid changes between playing on differentsurface types may act as a precursor to injury insoccer,[1] which is a finding that is evident inAmerican football.[39] Ekstrand and Gillquist[47]

proposed that it took six games for players toadapt to the new surface, although this related toolder generation turfs. Nevertheless, it appearsthat players who change frequently from playingon one surface to another may be at a greater riskof injury.

4. Conclusions

� Studies have provided strong evidence overallfor a trivial difference in injury incidence ratesbetween third and fourth generation artificialturf compared with natural turf.

920 Williams et al.


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� Artificial turf increased risk of ankle injuriesfor 8 of 14 cohorts.

� Six cohorts showed beneficial effects of artifi-cial turf on muscle injuries for soccer players(two were over the 90% likelihood value). Noharmful effects were found.

� Inferences made relating to severities of injurywere inconsistent across cohorts, except artifi-cial turf had very likely harmful effects forminor injuries in rugby union training andsevere injuries in young female soccer players.

� No clear differences between natural andartificial surfaces were evident in relation totraining versus match injuries.

� Inconsistent results from a limited number ofstudies made drawing clear conclusions diffi-cult for analyses by sport, gender, age orperformance level.

� Potential mechanisms for differing injurypatterns on artificial turf include increasedpeak torque properties and rotational stiffnessproperties of shoe-surface interfaces, differingfoot loading patterns, decreased impact at-tenuation properties and detrimental physio-logical responses compared with natural turf.Research on optimal shoe surface/turf releasefactors is required.

� Potential injury prevention strategies includeusing boots with shorter cleats and a morepliable upper on artificial turf, and playing onone type of surface rather than changingbetween surfaces.

� More controlled intervention studies, similarto the FIFA 11+ scheme,[48] are needed toprovide research-based strategies for injuryprevention as few evidence-based best practicemodels for injury risk reduction on natural orartificial turf exist.

� A proposed benefit of installing artificial turfis a reduction in ground maintenance costs.Any money saved could be invested in injurysurveillance to ensure the surface is safe.

� Future research should focus on the long-term risk of chronic injuries, mechanisms andrisk factors for specific injuries and effective-ness of injury prevention strategies associat-ed with match and training on artificialsurfaces.

� Future research requires uniformity regardinginjury definitions, statistical reporting and de-scription of surfaces, subjects and data collec-tion methods used, as outlined, for example,by Phillips.[49] Studies should use longitudinal,prospective cohort designs conducted overseveral teams and with one recorder wherepossible to ensure high intra-rater reliability.Definitions of injury and injury severityshould be specific and uniform to allow forcomparison between studies.[49]

Acknowledgements

Auckland University of Technology funded this review.The authors have no conflicts of interest relevant to the con-tent of this review. We thank Kelly Sheerin from the SportsPerformance Research Institute New Zealand Running Me-chanics Clinic for reviewing this manuscript.

There are no competing interests by the authors. Thecorresponding author has the right to grant on behalf of allauthors, and does grant on behalf of all authors, an exclusivelicense (or nonexclusive for government employees) on aworldwide basis to the journal editor to permit this article tobe published in the journal.

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Correspondence: Professor Patria Hume, Sports PerformanceResearch Institute New Zealand (SPRINZ), School of Sportand Recreation, Auckland University of Technology, PrivateBag 92006, Auckland, New Zealand.E-mail: [email protected]



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