Assessing Youth Sprint Ability Methodological Issues, Reliability and Performance Data

7/29/2019 Assessing Youth Sprint Ability Methodological Issues, Reliability and Performance Data

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Pediatric Exercise Science, 2011, 23, 442-467

© 2011 Human Kinetics, Inc.

review article

Assessing Youth Sprint Ability—Methodological Issues, Reliability

and Performance Data

Michael C. Rumpf and John B. Cronin

University of Technology

Jon L. Oliver and Michael Hughes

University of Wales Institute

The primary purpose of this paper was to provide insight into the methodological

issues and associated reliability of assessments used to quantify running sprint

ability in youth athletes aged 8–18 years. Over-ground sprinting was the most

reliable and common used choice of assessment to measure sprint performance of

youth. In addition, the performance data of those athletes over distances ranging

from 5 to 40 meters was collated from 34 published articles and tabulated with

regards to the athlete’s chronological age. Torque or nonmotorized treadmills have

been used to quantify sprint performance in youth with acceptable reliability, this

technology providing deeper insight into sprint kinetics and kinematics; however

there is limited performance data on youth using the torque and the nonmotorized

treadmill. It is suggested that future research should use this technology in youth

to better understand changes associated with growth, maturation and training.

Sprinting is an essential component in many sports and can distinguish betweengood and better athletes during team sports performance (49). The sprint can be

divided into a number of phases: the start including rst step quickness, acceleration,maximum velocity, and deceleration. First step quickness, dened as the rst 0–5m is usually included in the acceleration phase, particularly characterized by highpropulsion force (39,50), and of extreme importance in many sports (12,19,25). Theacceleration phase can also be dened as the distance needed to attain maximumvelocity. Maximum velocity is the highest speed during the sprint. Decelerationfollows the maximum velocity phase and is characterized by a percentage decreasein velocity until the completion of the sprint. Depending on the sport and position,the phases of the sprint can have different importance. For example the accelerationphase of untrained is shorter (8) compared with professional sprinters who are ableto accelerate until 50–60 m (8,40), whereas professional soccer players use only17–20 m in distance (9).



Assessing Youth Sprint Ability 443

Testing and monitoring athletes sprinting speed is important and can havedifferent purposes i.e., comparison between athletes, controlling training efcacy,talent identication and monitoring long-term-athlete development. However, most

of the literature relates to adults, even though more young athletes are becominginvolved in advanced level athletics (23) and long term athlete/player developmentprograms, which suggests the needs for accurate and reliable tests and performancedata in youth. Currently a variety of assessment equipment and techniques can beused to assess the sprint ability of athletes’ e.g., timing lights, torque treadmillsand nonmotorized treadmills. The quantity and quality of the information providedby these technologies varies markedly and the reader needs to be cognizant of theadvantages and limitations as well as the contribution each technology providesin understanding sprint capability, particularly in youth. Given this informationthe aim of this article is to: 1) describe the most common tests used for assessing

sprint running in youth; 2) present the associated reliability for the tests; and, 3)present performance data for each assessment where appropriate.

Methods

To obtain articles for the review, a database search of PubMed, Google Scholar,Sport Discus and Medline was conducted. The search terms used as separate wordsor in combination with each other for “title”, “keywords” and “in-text search” were:“sprint”, “sprinting”, “acceleration”, “velocity”, “running”, “power”, “speed”,“agility”, “ability”, “repeated”, “youth”, “short term power output”, “long termdevelopment”, “physical activity”, “children”, “performance”, “assessment”,“motor”, “competence” and “skills”. The bibliographies of all reviewed articleswere then searched and also reviewed. The search ended on the 18th of November2010. Studies were included if they fullled the following 6 selection criteria:(a) the study clearly detailed the outcome measures of interest (e.g., sprint timeover 30 m) which had to be less than 40 m; (b) the study gave information aboutparticipants characteristics (i.e., number, age); (c) the study clearly outlinedmeasurement procedures (i.e., used equipment, testing procedures); (d) the studypresented group means for the appropriate sample; (e) the study was published in

a peer-reviewed book or as peer-reviewed journal article or abstract; and (f) thestudy had to have been written in the English or German language. The followingcharacteristics were recorded for all articles: Author, year, sample size, gender,training status, age, maturation, testing distance, testing equipment, data analysis,dependent variables and sprint time.

Results

Overground Running Tests

A total of 106 studies were found of which 34 studies were included and 72 excludedin this section. Reasons for exclusion included an insufcient description of the:subject’s characteristics; age range; or assessment procedures i e measurement



Table 1 Cross-Sectional Studies That Assessed Overground Sprinting

Performance of Boys

Author (Ref)

Subject Characteristics

Number and genderTraining status

Age/maturation

Babel et al. (1) 17♂

Nonathletic boys

TS 1

8 Caucasian group

11.2 y, 1.41 m

9 Afro-Caribbean group

11.7 y, 1.47 m

Berg et al. (2) 14♂, 11.8 y, 1.54 m, 42.2 kg

Buttifant et al. (4) 21♂ junior national and state representative footballplayers, 16.1 y, 1.75 m, 69.2 kg

Christou et al. (6) 26♂

4.3 y of soccer experience

Experimental 1:

9♂, 13.8 y, 1.62–1.65 m, 52–57.5 kg, TS 4.0–4.3

Experimental 2:

9♂, 13.3 y, 1.63–1.65 m, 54.1–55.3 kg, TS 3.9–4.2

Control:

8♂, 13.3 y, 1.63–1.66 m, 57.4–55.8 kg, 3.8–4.2 TS

Colella et al. (7) 105♂

8–10 y, 9.2 y, maturation measured but no data given

Overweight♂

17♂, 8.4 y, 1.33 m, 42.46 kg

17♂, 9.5 y, 1.40 m, 45.96 kg

18♂, 10.3 y, 1.45 m, 51.66

Not overweight♂

18♂, 8.4 y, 1.29 m, 27.03 kg

17♂, 9.5 y, 1.31 m, 28.13 kg

17♂, 10.3 y, 1.41 m, 35.52 kg

Dourado et al. (10) 100♂U14 soccer players, 1.57 m, 46.12, kg



ProceduresEquipment

SurfaceDependentVariables Times

30 m on a synthetic track using photo-electriccells with a start 1 m behind the rst light

30 m time (s)

5.59

5.51

Average over 2 sprints on a grass athletic eld,measured with a hand-held stop watch

30 m time (s) 5.68

2× 20 m sprints on a grass surface, measuredwith timing gates

20 m time (s) 3.01

The fastest out of two 30 m sprints using elec-tronic photo cells placed 50 cm above ground forthe rst gate and on the height of the subjects head

for the following two gates. Subjects had to startsprinting 30 cm behind a line.

Experimental 1 Pretraining, 8weeks, 10 weeks

10 m 2.16, 2.18, 2.09

30 m time 5.07, 5.16, 4.94

Experimental 2

10 m 2.0, 2.04, 1.98

30 m time 4.85, 4.88, 4.85

Control

10 m 2.18, 2.20, 2.11

30 m time 5.20, 5.26, 5.22

Best of two 10 and 20 m sprints from a standing

start measured with a handheld stopwatch

10, 20 m time (s)

Overweight♂

8.4 y 2.61, 4.95

9.5 y 2.47, 4.56

10.3 y 2.31, 4.22

Not overweight♂

8.4 y 2.45, 4.45

9.5 y 2.31, 4.29

10.3 y 2.15, 3.92

40 m sprints using electronic timing system 10, 40 m time (s) 1.78, 6.21



Author (Ref)


Number and gender

Training statusAge/maturation

Gabbett (17) 88♂ rugby players

Different amount of playing experience

Forward:

13♂, 12.5 y, 57 kg

7♂, 13.5 y, 67.7 kg

11♂, 14.5 y, 76.5 kg

12♂, 15.4 y, 75.5 kg

Backs:

14♂, 12.3 y, 44.8 kg

10♂, 13.7 y, 52.1 kg

12♂, 14.6 y, 62.1 kg

9♂, 15.6 y, 64.8 kg

Gissis et al. (18) 48♂ football players

18♂ Elite, 16.3 y, 1.69 m, 68.17 kg

18♂ Subelite, 16.4 y, 1.69 m, 67.74 kg

18♂ Recreational, 16.2 y, 1.69 m, 69.87 kg

Hoare (20) 125♂

Participants of Australian U16 basketball championships

125♂, 15.4 y

28♂, 1.78 m, 68.1 kg

25♂, 1.81 m, 71.3 kg

31♂, 1.86 m, 76.4 kg

25♂, 1.91 m, 83.8 kg

16♂, 1.95 m, 84.5 kg

Hoshikawa et al. (22) 24♂ academy youth football players, 17.0 y, 1.72 m,63.7 kg

Kilding et al. (26) 24♂ football players

10.4 y, 4.1 years of playing experience

12♂Experimental

1.32 m, 34.3 kg

Table 1 (continued)



Procedures

EquipmentSurface

DependentVariables Times

Fastest out of two 40 m sprints using electronicgates

10, 20, 40 m time(s)

2.6, 4.24, 7.50

Forward: 2.44, 3.99, 7.00

12.5 y 2.25, 3.72, 6.58

13.5 y 2.22, 3.61, 6.17

14.5 y 2.46, 4.04. 7.11

15.4 y 2.24, 3.7, 6.47

Backs: 2.21, 3.62, 6.26

12.3 y 2.17, 3.55, 6.00

13.7 y

14.6 y

15.6 y

10 m sprint using a dual laser beam in connectionwith a digital chronometer. Best out of three trialsfrom a standing position was used for further dataanalysis

10 m time (s)

Elite 1.95

Subelite 2.14Recreational 2.21

Fastest of all split time in three 20 m sprints ona dry grass surface using electronic timing gates,starting with the front foot on the start line

5, 10, 20 time (s)

1.08, 1.83, 3.12

1.10, 1.84, 3.15

1.13, 1.89, 3.21

1.12, 1.88, 3.24

1.10, 1.87, 3.21

20 m sprint on a grass eld measured by photo-cells

5 m time (s) 1.02

10 m time (s) 1.78

15 m time (s) 2.45

20 m time (s) 3.08

Average of three times 20 m sprints using dualelectronic timing gates, 0.75 m above ground

level, 0.5 m behind the starting line

20 m time (s) Pre, Posttest, Average

Experimental 3.60, 3.52, 3.56



Author (Ref)


Number and gender

Training status

Age/maturation

Kollath et al. (27) 131♂ football players

11♂, 8.3 y, 1.38 m, 32 kg

9♂, 10.1 y, 1.45 m, 35 kg

10♂, 11.0 y, 1.50 m, 40 kg

16♂, 11.8 y, 1.50 m, 39 kg

13♂, 12.8 y, 1.59 m, 46 kg

17♂, 13.6 y, 1.64 m, 52 kg

13♂, 14.8 y, 1.74 m, 62 kg12♂, 15.6 y, 1.69 m, 57 kg

17♂, 16.7 y, 1.77 m, 71 kg

Kotzamanidis (28) 30♂, nonathletic

Experimental group:

15♂, 11.1, 1.57 m, 49.6 kg

Control group:

15♂, 10.9, 1.54 m, 48.7 kg

Kotzamanidis (30) 35♂

Physical educational student

Combined resistance and speed training (CRST)

12♂, 17 y, 1.78 m, 73.5 kg

Resistance training only (RTO)

11♂, 17.1 y, 1.75 m, 72.5 kg

Control (CO)

12♂, 17.8 y, 1.76 m, 75 kg

Kotzamanidis (29) 30♂

Healthy nonathletic boys

10–11, 1.54–1.56 m, 48.7–49.6 kg, TS 1

Experimental group

15♂, 11.1 y, 1.57 m, 49.6 kg, TS 1

Control group

Table 1 (continued)



Procedures

Equipment


Best out of three 20 m sprints on an articial turf,from a standing split start position measured bytiming gates

10, 20 m time (s)

8.3 y 2.13, 3.85

10.1 y 2.14, 3.76

11.0 y 2.04, 3.64

11.8 y 2.08, 3.60

12.8 y 2.07, 3.62

13.6 y 1.97, 3.47

14.8 y 1.79, 3.1715.6 y 1.77, 3.10

16.7 y 1.70, 2.98

Best out of two 30 m indoor sprints measuredwith an electronic chronometer connected to opto-reective switches

Time (s) Pre, Posttest, Average

0–10 m 2.19, 2.14, 2.17

0–20 m 3.82, 3.68, 3.75

0–30 m 5.45, 5.27, 5.36

0–10 m 2.29, 2.30, 2.30

0–20 m 4.04, 4.07, 4.06

0–30 m 5.74, 5.77, 5.76

Fastest of two 30 m sprints using photocellsplaced at shoulder height. Start from the standingposition


CRST 4.34, 4.19, 4.27

RTO 4.33, 4.31, 4.32

CO 4.50, 4.48, 4.49

Fastest of two 30 m sprints on an indoor sporthall, using electronic chronometer connected to 4pairs of opto-reective switches

Experimentalgroup

Pre, Posttest, Average

0–10 time (s) 2.24, 2.19, 2.22

10–20 time (s) 1.71, 1.65, 1.68

20–30 time (s) 1.61, 1.56, 1.59

0–30 m time (s) 5.55, 5.41, 5.48

Control group Pre, Posttest, Average

0–10 time (s) 2.29, 2.30, 2.30

10–20 time (s) 1.75, 1.78, 1.77



Author (Ref)



Age/maturation

Kruger and Pienaar (31) 39♂ talented children

12.1 y, 1.41 m, 34.3 kg, Diverse TS

Kruger and Pienaar (32) 62♂ school children

Experimental group

16♂, 10.92 y

Control group

16♂, 12.38 y

Le Gall (33) 328♂ football players 11–18

10♂, 11–11 1/2 y, 39.8 kg

10♂, 12 y, 41.2 kg

22♂, 12 1/2 y, 42.5 kg

35♂, 13 y, 45.6 kg

31♂, 13 1/2 y, 49.9 kg

57♂, 14 y, 56.6 kg

36♂, 14 1/2 y, 58.2 kg

15♂, 15 y, 59.7 kg

27♂, 15 1/2 y, 62.6 kg

21♂, 16 y, 64.7 kg

44♂, 17 y, 66.3 kg

20♂

, 18 y, 68.1 kg

Table 1 (continued)



ProceduresEquipment


Fastest of two 100 m sprints using electronictiming lights

0–5 time (s) 1.8

Fastest of two 100 m sprints using electronictiming lights.

Experimentalgroup

Pre, Posttest, Average

0–40 m time (s) 7.41, 7.3, 7.36

Control group Pre, Posttest, Average

0–40 m time (s) 7.44, 7.6, 7.52

Fastest of two 40 m sprints using photoelectriccells

10, 10–20,20–30, 30–40, 40time (s)

11–11 1/2 y 2.01, 1.43, 1.38,1.37, 6.19

12 y 2.01, 1.40, 1.34,

1.33, 6.0812 1/2 y 2.00, 1.40, 1.33,

1.32, 6.05

13 y 1.99, 1.39, 1.32,1.31, 6.01

13 1/2 y 1.96, 1.37, 1.30,1.29, 5.92

14 y 1.94, 1.34, 1.26,1.25, 5.79

14 1/2 y 1.91, 1.31, 1.24,1.24, 5.70

15 y 1.91, 1.30, 1.24,1.23, 5.68

15 1/2 y 1.90, 1.31, 1.23,1.21, 5.65

16 y 1.87, 1.28, 1.20,1.17, 5.52

17 y 1.85, 1.27, 1.19,1.17, 5.48

18 y 1.85, 1.27, 1.19,1.17, 5.48



Author (Ref)



Age/maturation

Lidor et al. (34) 279♂, national trials in handball

U12♂

29

118

U13♂

24109

U14♂

18

42

Luhtanen et al. (36) 106 football players from six First Division clubs

17♂, 18 y

21♂, 16 y

Maio Alves et al. (37) 23♂ football players

17.4 y, 1.75, 70.3 kg

McMillan et al. (38) 11♂ football players, 16.9 y, 1.77 m, 70.6 kg

Meyer et al. (41) 103♂State selection football players

30♂U14, 1.64 m, 53 kg

29♂U15, 1.71 m, 61 kg

22♂U16, 1.75 m, 67 kg

12♂U17, 1.77 m, 69 kg

10♂U18, 1.77 m, 72 kg

Meylan and Malatesta (42) 25♂ football players

14♂U13, 1.60 m, 49.0 kg

11♂U13, 1.64 m, 47.9 kg

Reilly et al. (49) 31♂, 16.4 years

16♂ elite, 1.71 m, 63.1, kg

15♂ subelite, 1.75 m, 66.4 kg

Table 1 (continued)



ProceduresEquipment


Best of two 20 sprints from a stationary start withthe front foot behind the starting line. Time wasmeasured using a handheld stopwatch

20 m time (s)

Selected 3.66

Nonselected 3.81

Selected 3.55Nonselected 3.67

Selected 3.44

Nonselected 3.54

30 m sprint measured with photocells 30 m time (s)

18 y 4.26

16 y 4.41

Best of two 5 meter sprint measured with photo-electric cells


Experimental 1 1.09, 0.99, 1.04

Experimental 2 1.13, 1.06, 1.10

Control 1.13, 1.11, 1.12

Average of three 30 m sprint runs, starting behindthe rst gate, on an indoor track, using photocells


1.96, 1.96, 1.96

Mean time of the best four out of ve 30 m indoorsprints, starting 1 m behind the rst timing gate

5, 10 m time (s)

1.04, 1.82

1.00, 1.75

1.01, 1.75

0.99, 1.71

0.99, 1.70

Better of two 10 meter sprints measured by infra-red photoelectric cells, starting 0.3 m behind therst gate


1.96, 1.92, 1.94

2.06, 2.01, 2.04

Average of three 30 m sprints measured by elec-

tronic timing gates

5, 30 m time (s)

1.04, 4.31

1.07, 4.46



Author (Ref)



Age/maturation

Tumilty (53) 21♂ U17 national australian football players

Venturelli et al. (55) 16♂ members of a football team involved in the nationalchampionship

11y, 1.50m, 40.5 kg, TS 1

7♂, Sprint training group STG

9♂, Coordination training group CTG

Wong et al. (56) 70♂ U14 regional representative football players

10 GK, 13.4 y, 1.69 m, 54.6 kg

20 DF, 13.3 y, 1.67 m, 56.2 kg,

25 MF, 13.4 y, 1.65 m, 52.2 kg

15 FW, 13.0 y, 1.56 m, 43.9 kg

Wong et al. (57) 62♂, U14 regional representative football players

Experimental

28♂, 13.5 y,, 1.67 m, 52.0 kg

Control

23♂, 13.2 y, 1.64 m, 52.5 kg

Key:♂ = Male, PHV = Peak Height Velocity; TS = Tanner Stage

Table 1 (continued)



ProceduresEquipment


Three 20 m sprints using dual beam timing gates,starting with the front foot on the starting line atthe rst gate. Best split times from all runs

5 m time (s) 1.11

10 m time (s) 1.85

20 m time (s) 3.12

Best out of three 20 m sprints on a grass turf usingphotoelectric cells


STG 3.75, 3.66, 3.71

CTG 3.64, 3.56, 3.60

Fastest out of three 30 m spritns using photoelec-tric cells, with split times every 10 m and the frontfoot was placed right behind the starting line

10, 30 m time (s)

10 GK 2.06, 4.92

20 DF 2.09, 4.81

25 MF 2.05, 4.82

15 FW 2.07, 4.96

30 m sprint from a stationary start with the front

foot right behind the starting line, measured withinfrared photoelectric cell. Best out of three trialswas used for analysis

10, 30 m time (s) Pre, Posttest, Average

10 m time (s) 2.05, 1.95, 2.00

30 m time (s) 4.85, 4.74, 4.80

10 m time (s) 2.07, 2.04, 2.06

30 m time (s) 4.95, 5.00, 4.98



Table 2 Cross-Sectional Studies That Assessed Overground Sprinting

Performance of Girls

Author (Ref)

Subject CharacteristicsNumber and gender

Training status

Age/maturation

Colella et al. (7) 88♂

8–10 y, 9.2 y, maturation measured but no data given

Overweight♂

17♂, 8.3 y, 1.32 m, 40.35 kg

18♂, 9.5 y, 1.38 m, 44.09 kg18♂, 10.2 y, 1.43 m, 50.49 kg

Not Overweight♀

18♀, 8.3 y, 1.28 m, 27.27 kg

17♀, 9.5 y, 1.32 m, 28.21 kg

17♀, 10.2 y, 1.40 m, 34.47 kg

Ellis et al. (13) 17♀ U18 state level female netball players

Ellis et al. (13) 76♀ U17 female netball players

Ellis et al. (13) 11♀ U17 state level female netball players

Fedotova (15) 141♀

Well-trained young female eld hockey players

16♀, 10 y, 1.39 m, 33.57 kg,

15♀, 11y, 1.43 m, 35.34 kg

20♀, 12y, 1.50 m, 39.07 kg

14♀, 13y, 1.57 m, 43.31 kg

20♀, 14y, 1.60 m, 49.84 kg

15♀, 15y, 1.63 m, 53.99 kg

15♀, 16y, 1.64 m, 57.98 kg

14♀, 17y, 1.65 m, 59.95 kg

12♀, 18y, 1.66 m, 60.59 kg



Procedures

Equipment


Best of two 10 and 20 m sprints from a standingstart measured with a handheld stopwatch

10, 20 m time (s)

Overweight♀

8.3 y 2.71, 5.11

9.5 y 2.58, 4.7810.2 y 2.50, 4.63

Not Overweight♀

8.3 y 2.64, 4.87

9.5 y 2.5, 4.72

10.2 y 2.41, 4.57

Three 20 m sprints using dual beam timing gates,starting with the front foot on the starting line at therst gate. Best split times from all runs

5 m time (s) 1.19

10 m time (s) 2.01

20 m time (s) 3.47

Three 20 m sprint overground, using double beamtiming gates, starting with the front foot on the start-ing line at the rst gate. Best split times from all runs

5 m time (s) 1.23

10 m time (s) 2.05

20 m time (s) 3.49

Three 20 m sprints, using dual beam timing gates,starting with the front foot on the starting line at therst gate. Best split times from all runs

5 m time (s) 1.18

10 m time (s) 2.09

20 m time (s) 3.41

30 m sprint on a track using stop-watch 30 m time (s)

10 y 5.83

11 y 5.62

12 y 5.42

13 y 5.30

14 y 5.23

15 y 5.11

16 y 4.95

17 y 4.87

18 y 4.79

(continued)



Author (Ref)



Age/maturation

Hoare (20) 123♀

Participants of Australian U16 basketball championships

130♀, 15.2 y

32♀PG, 1.66 m, 57.8 kg

30♀OG, 1.69 m, 61.6 kg

17♀SF, 1.73 m, 64.1 kg

25♀PF, 1.77 m, 69.4 kg

19♀C, 1.81 m, 70.5 kg

Hoare and Warr (21) 17♀ selected football players 15.4 y, 1.64 m, 55.3 kg,

Lidor et al. (34) 126♀, national trials in handball

U12♀

20

54

U13♀

20

51

Luhtanen et al. (36) 35♀ football players from six First Division clubs

17♀, 18 y

18♀, 16 y

Key:♀ = Female, PHV = Peak Height Velocity; TS = Tanner Stage

Table 2 (continued)



ProceduresEquipment


Fastest of all split time in three 20 m sprints on a drygrass surface using electronic timing gates, startingwith the front foot on the start line

5, 10, 20 time (s)

♀PG 1.18, 1.98, 3.40

♀OG 1.19, 2.01, 3.46

♀SF 1.28, 2.08, 3.56

♀PF 1.25, 2.07, 3.53

♀C 1.19, 2.03, 2.53

Fastest of all split times in three 20 m sprints usingelectronic timing gates, starting with the front footup on the start line, measured on grass surface

5 m time (s) 1.18

10 m time (s) 2.01

20 m time (s) 3.47

Best of two 20 sprints from a stationary start withthe front foot behind the starting line. Time wasmeasured using a handheld stopwatch

20 m time (s)

Selected 3.98

Nonselected 3.90

Selected 3.83

Nonselected 3.94

30 m sprint measured with photocells 30 m time (s)

18 y 4.90

16 y 4.92



460 Rumpf et al.

of the studies and 9% used a stopwatch. Twenty-three studies (68%) used thefastest sprint time out of multiple sprints for data analysis, six studies (18%) usedthe average time of multiple sprints and an additional ve studies (15%) did not

mention how the sprint time was selected i.e., data analysis.The total number of subjects from which the performance data were generated

was 2864. Of these 2864, 77% were males and the remaining 23% females. Seventysix percent of the studies included used athletic participants, while the remainderwere categorised as nonathletic (19%) or the training status was not reported (5%).

In terms of the age of the participants, the age range was 8–18 yrs with themean age of 13.95 years for the male sample and a mean age of 13.7 for the females.Only two studies described the maturation of the participants (6,31) and two studiesreported sprinting time in relation to the subjects’ peak height velocity (46,58).

Methodological Issues. As can be observed from Table 1 and Table 2 severalmethodological issues make comparison of the data difcult. Time measurementdevices were single or double beam timing gates, and stop-watches, the greatestmeasurement error associated with the use of stopwatches the least with dualbeam infra red timing light technology. Different starting stances (standing start,split start, three point start, track and eld start), starting distance behind the startline (30 cm—20 m) and different running surfaces will inuence the sprint time.Several studies also did not mention which data (fastest vs. average trial) wereused for data analysis.

Reliability of Overground Sprint Running Assessments. A total of sevenstudies reported the reliability of overground sprinting in youth population(6,11,16,28–30,32). Intra- and interday CVs for sprinting distances of 10, 20,30 and 40 m ranged from 0.83–2.07% (6,16). Intra- and interday ICCs rangedfrom 0.88 and 0.98 for 10–40 m (6,16,29) and Pearson correlation coefcientfrom 0.90–0.97 (28–30,32).

Performance Data of Overground Sprinting. Specic performance data fordifferent populations, distances, gender and assessement methodologies can beobserved in Tables 1 and 2. Figures 1 and 2 summarize this data so as to provideinsight into the trends regarding sprint performance over time (chronological age).

The reader needs to be cognizant of the limitations cited previously when viewingthis data. Average sprint times for male subjects (n = 2864) over 5, 10, 20, 30,and 40 m, calculated from all subjects and age groups, are shown in Figure 1.Average sprint time for boys decreased markedly with age over all distances untilapproximately the age of 15 years, after which the rate in decrease of sprint timeslessened (i.e.,16–18 years).

Average sprint times for female subjects (n = 670) over 5, 10, 20, 30, and 40m, calculated from all subjects and age groups, are shown in Figure 2. It seems thatwhen females are compared with males at the same chronological age, the maletimes were less over all distances. Average sprint time for girls decreased markedly

with age over all distances until approximately the age of 16 years, after which therate in decrease of sprint times lessened (i.e.,17–18 years).



Figure 1 — Sprint times over 5–40 m distances for males 8–18 years of age.



462 Rumpf et al.

caused by the subjects’ weight, while a harness connected to a strain gauge mea-sures the subjects’ horizontal force, with a goniometer recording the angle at whichhorizontal force was created. Horizontal displacement of the belt is measured by

a sensor system attached to the rear rolling drum (24).

Methodological Issues. Generally, studies which examined single running sprintswith a duration over 10 s were excluded. The highest speed and power duringsprinting on a torque treadmill was achieved within the rst 10 s, and longer testdurations will affect mean power output, trigger different energy systems and testother running qualities/abilities of the participants. Peak power is a measurement of the highest power achieved in a dened period of time and is usually the averagedpeak power of the number of foot strikes in that time period. Methodological issuesalso arise when a rolling or a standing start is used for data collection. Furthermore

the elasticity of the tether will affect horizontal force output.Reliability of Torque Treadmill Sprint Running Assessments. One studyinvestigated the reliability of peak and mean power of pediatric populationperforming a 30-s sprint on a torque treadmill (14). Interday ICC values were 0.80and 0.81 for peak and mean power respectively.

Test-retest reliability using a Pearson correlation of power variables measuredfor a 5-s sprint duration in adults were 0.8–0.89 (24).

Performance Data of Torque Treadmill. Only one study measured single sprintperformance with a duration of less than 10 s using this technology (5). Maximum

velocity, mean power, mean power per kg body weight of 11 male handball players(< 18 years old) during a eight second sprint on a torque treadmill were measured(Table 3). However, a measurement of participant’s maturation was not included.There is a need for further research in this area.

Nonmotorized Treadmill

A nonmotorized treadmill has been used to measure sprint kinetics and kinematicsin youth (3,43–45,47,48,51,54,59). A horizontal load cell, attached with a harnessto the runner, measures the horizontal force. Typically four individual load cells,

Table 3 Cross-Sectional Studies That Accessed Sprinting Performance

Using a Torque Treadmill

Author

(Date)


Number and gender

Training status

Age/maturation

Procedures

Equipment Dependent Variables ResultsChelly andD i (5)

11♂, 16 y, 1.79 m, 68 kg 8 s sprint on at t d ill

Vmax (m/s) 6.1MP (W) 654




mounted under the running surface, measure the vertical force while running. Therunning speed can be monitored by optical speed photomicrosensors.

Methodological Issues. Considerations about peak and mean power are similarto the torque treadmill. The initial resistance of the belt is another issue that needsto be considered. Studies did not report the initial resistance of the nonmotorizedtreadmill belt, which affects inertia and subsequent sprint kinematics kinetics. Inrelation to the treadmill resistance it can be expected that the weight/strength of the participant would inuence the participant’s ability to overcome the initialresistance of the treadmill and thus lighter/weaker participants at a greaterdisadvantage.

Reliability of Nonmotorized Treadmill Sprint Running Assessments. Thereliability of mean and peak velocity and mean and peak power output have beeninvestigated on a nonmotorized treadmill (45). Interday reliability values for thosevariables were within 2.88 and 8.32%. Sutton et al. (51) presented absolute valuesfor mean (15.3 Watts) and peak (26.6 Watts) power as a coefcient of repeatability.A summary of all reliability values of sprint running assessments can be observedin Table 4.

Reliability values for variables measured on a nonmotorized treadmill duringa single sprint with a duration of 6–10 s including a complete recovery in adults(35,52) were also reported throughout literature. The coefcients of variations(CV) for the variables of interest reported in these studies were 1.3–1.9% for the

speed variables (52), 8.0–9.1% for the force variables (52), and 4.3–9.3% for powervariables (35,52). The ratio limits of agreement (95% LoA) ranged from 1.00–1.05*/÷ 1.03 (52) for speed variables, from 1.01–1.04 */÷ 1.15–1.21 (52) for forcevariables, and 1.02–1.07 */÷ 1.12–1.21 (52) for power variables.

Performance Data of Nonmotorized Treadmill. No study investigated singlesprint performance with a duration of below 10 s using youth participants whichalso including measurement of maturation. There is a need for further research inthis area.

Discussion and ConclusionsMeasuring sprint performance of youth can have various purposes and use differenttechnologies and protocols. Running over-ground is still the easiest, most popularand accurate measurement of youth’s sprint ability. However, the variables of inter-est are typically sprint times between timing lights from which average velocitiescan be calculated. While valuable in terms of monitoring sprint performance, thisinformation is extremely limited in terms of understanding the mechanical deter-minants of sprint performance. In this regard a torque or a nonmotorized treadmillcan provide mechanistic information on sprint kinematics and kinetics in youth.

However, there are a limited number of studies that have used this type of tech-nology in youth and the reliability of many of the variables that can be quantiedfrom these treadmills for the most part have not been established. In addition, the



A b s o

l u t e a n d R e l a t i v e R e l i a b i l i t y o f S p r i n t A s s e s s m

e n t s

A b s o

l u t e

R e l a t i v e

C V

P e a

r s o n C o r r e l a t i o n s

I C C

n t

A u t h o r

V a l u e ( V a r i a b l e )

V a l u

e ( V a r i a b l e )

V a l u e ( V a r i a b l e )

M i s c e l l a n e o

u s

d

C h r i s t o u e t a l . ( 6 )

1 . 4

6 % ( 1 0 m )

0 . 8

3 % ( 3 0 m )

0 . 9

6 ( 1 0 m )

0 . 9

8 ( 3 0 m )

I n t r a d a y r e l i a b i l i t y

d

D r i n k w a t e r e t a l . ( 1 1 )

1 . 3

0 % ( 2 0 m )

I n t e r d a y r e l i a b i l i t y

d

G a b b e t t ( 1 7 )

2 . 0

7 % ( 1 0 m )

1 . 5

2 % ( 2 0 m )

1 . 2

5 % ( 4 0 m )

0 . 8

8 ( 1 0 m )

0 . 8

9 ( 2 0 m )

0 . 9

2 ( 4 0 m )


d

K o t z a m a n i d i s ( 2 8 )

0 . 9 0

( 1 0 m )

0 . 9 1

( 2 0 m )

0 . 9 3

( 3 0 m )

N o t s t a t e d

d

K o t z a m a n i d i s ( 3 0 )

0 . 9 7

( 3 0 m )


d

K o t z a m a n i d i s ( 2 9 )

0 . 9 0

– 0 . 9

6 ( d i v e r s e )


d

K r u g e r a n d P i e n a a r ( 3 2 )

0 . 9 5

( 1 0 0 m )


d m i l l

F a l k e t a l . ( 1 4 )

0 . 8

0 ( P P )

0 . 8

1 ( M P )


z e d

O l i v e r e t a l . ( 4 5 )

2 . 8

8 % ( P V )

2 . 5

9 % ( M V )

8 . 3

2 % ( P P O )

5 . 4

1 % ( M P O )


z e d

S u t t o n e t a l . ( 5 1 )

C o e

f c i e n t o f r e p e a t a b i l i t y :

2 6 . 6

W ( P

P )

1 5 . 3

W ( M

P )


e f c i e n t o f V a r i a t i o n ,

I C C = I n t r a c l a s s C

o e f c i e n t , P V = P e a k V e l o c i t y , M

V = M e a n V e l o c i t y ,

P P O = P e a k P o w e r O u t p u t , M P O = M e a n P o w

e r O u t p u t ,

w e r , M

P = M e a n P o w e r




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Assessing Youth Sprint Ability Methodological Issues, Reliability and Performance Data

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