c3

Chapter III

Relation between multidimensional performance characteristics and level of performance in talented youth field hockey players Elferink-Gemser, M.T., Visscher, C., Lemmink, K.A.P.M., and Mulder, Th.(2004). Journal of Sports Sciences, 22, 1053-1063. Acknowledgements:

This study has been supported by a grant of the Dutch National Olympic Committee NOC*NSF. The authors thank all players, trainers, and staff of the field hockey clubs HC ’s Hertogenbosch and HC Rotterdam for their cooperation.

28

Abstract

To determine the relationship between multidimensional performance characteristics and level of performance in talented youth field hockey players, elite youth players (n = 38, mean age 13.2 years, sd = 1.3) were compared with sub-elite youth players (n = 88, mean age 14.2 years, sd = 1.3) on anthropometric, physiological, technical, tactical and psychological characteristics. Multivariate analyses with performance level and gender as factors, and age as the covariate, showed that the elite youth players scored better than the sub-elite youth players on technical (dribble performance in a peak and repeated shuttle run), tactical (general tactics; tactics for possession and non-possession of the ball) and psychological variables (motivation) (p < 0.05). The most discriminating variables were tactics for possession of the ball, motivation and performance in a slalom dribble. Age discriminated between the two groups, indicating that the elite youth players were younger than the sub-elite players. In the guidance of young talented players to the top as well as in the detection of talented players, more attention has to be paid to tactical qualities, motivation and specific technical skills.

Chapter I II III IV V VI VII VIII

29

3.1 Introduction

In the Netherlands, elite field hockey is played at a higher standard than in many other countries. The Dutch male field hockey players won the gold medal at the Olympic Games in Sydney 2000 while the female players won the bronze medal. In Athens 2004, both teams won silver. To maintain this level of performance, the Dutch National Olympic Committee has chosen ‘talent identification and development’ as one of its main research programmes. A talented young athlete is considered to be someone who performs better than his or her peers during training and competition, and who has the potential to reach the elite level (Howe et al., 1998; Helsen et al., 2000). Whereas in the 1970s and 1980s scientists focused mainly on the detection of talented athletes and developed sport talent-detection models (for a review, see Régnier et al., 1993), recently there has been a shift in emphasis from talent detection to talent guidance and development (Williams and Reilly, 2000). Talent development is based on the prediction of performance and consequently on the assumption that underlying factors determining excellence in sports really do exist (Kroll, 1970; Régnier et al., 1993). In team games like field hockey, however, the prediction of long-term success in young players is complex because multidimensional qualities are needed.

In the present study, we focus on youth field hockey players who were already designated as talented. Every year, many talented Dutch field hockey players are invited to participate in a selection team for their age category. These teams are provided extra training facilities and highly qualified trainers. Selected players compete in the highest Dutch junior competition for field hockey. Although all of these talented players are given the chance to develop their potential to the full, only a few of them ultimately make it to the top. To develop a successful sporting career, talented players have to perform at a high level at a young age, indicating well-developed anthropometric, physiological, technical, tactical and psychological characteristics (see Figure 3.1).

30

Figure 3.1. Multidimensional performance characteristics and level of performance in field hockey.

The multidimensional performance characteristics shown in Figure 3.1 are based on a limited number of determining factors for elite field hockey. Unique to field hockey is the semi-crouched posture, which causes extra physiological strain on players (Reilly and Seaton, 1990). Competitive match-play is a non-continuous, high-intensity, intermittent activity that places heavy demands on the aerobic energy system. The anaerobic system is also important: brief bursts of high-energy release are separated by periods of lower intensity (Bhanot and Sidhu, 1983; Reilly and Borrie, 1992; Boyle et al., 1994; Lothian and Farrally, 1994). Consequently, a successful player has to be able to perform successive short all-out sprints. The intermittent nature of, and the many changes of direction during, match-play underscores the importance of highly developed sprint capacity and performance in repeated sprints, as well as of an outstanding slalom sprint performance and interval endurance capacity of elite players (Reilly and Seaton, 1990; Lemmink et al., 2000).


31

Control of the ball while sprinting, turning, passing, and scoring goals is only possible if a player possesses excellent technical qualities. Straight dribbling is defined as running or sprinting in a straight line, whereas slalom dribbling is defined as running or sprinting with quick changes of direction while maintaining control of the ball (Smith and Chamberlin, 1992; Reilly et al., 2000). In Figure 3.1, these qualities make up the technical characteristics.

Due to the nature of field hockey, good sprinting ability, good endurance and the performance of highly developed technical skills are not sufficient if the timing of actions is not correct. This tactical knowledge is also referred to as “game intelligence”, and includes anticipation and decision-making skills. Tests to measure these qualities in soccer players show consistent differences between skilled and less skilled players (Williams and Davids, 1995; Williams, 2000). Tactical characteristics are part of the multidimensional performance characteristics in Figure 3.1.

To perform at the top level, elite players must be prepared to invest many hours of intensive training over many years (Ericsson et al., 1993). They also have to achieve under high pressure. It is therefore not surprising that psychological characteristics often distinguish elite from non-elite performers (Mahoney et al., 1987; Morris, 2000).

The multidimensional performance characteristics shown in Figure 3.1 are, to a certain extent, responsive to training interventions (Hoare and Warr, 2000). In addition, the environment of a talented player must not be underestimated in that parents and coaches play an important role in helping talented athletes to improve themselves during their sporting careers (Bloom, 1985; Carlson, 1988; 1993; Côté, 1999; Visscher et al., 2004).

Until now, only a few multivariate approaches focusing on identifying talent in team sports have been completed (Deshaies et al., 1979; Pienaar et al., 1998). In these studies, elite players have been compared to their non-elite counterparts. Reilly et al. (2000) used a multidisciplinary approach to distinguish between elite and sub-elite soccer players on the basis of performance on test items. They recommended a study with a pool of already selected talented athletes who were exposed to systematic training. For this reason, the present study focuses on youth field hockey players who were all considered to be talented.

The main aim of this study is to determine whether a relationship exists between multidimensional performance characteristics and level of performance in talented youth field hockey players. A comparison is made between elite youth players and youth players immediately below this level, in terms of anthropometric, physiological, technical, tactical and psychological characteristics.

32

3.2 Methods

Participants A total of 126 talented field hockey players from 12 selection teams participated in this study. There were 63 female and 63 male players. The mean age of the female players was 13.9 years (sd = 1.3, range 12-16), the mean age of the male players 13.9 years (sd = 1.4, range 11-16). All players were considered to be talented, since they were already playing in a selection team of a field hockey club of national prestige. Thus that all participants were playing at the highest level possible for their age category. All players were tested at the end of the 2000-2001 Dutch competitive field hockey season. Each participant was assessed based on the following five categories: anthropometric, physiological, technical, tactical and psychological. Field tests were organized on modern synthetic field hockey playing surfaces (water-based pitches).

In addition to playing in their club’s selection team, talented Dutch players who are considered to be current elite youth players are invited to train and play in a youth selection team of the Dutch Field Hockey Association. Talented players who are considered to be current sub-elite youth players only play in their club’s selection team. This distinction, based on the performance of the players in the 2000-2001 season, was also adopted in this study, resulting in 38 elite youth players and 88 sub-elite youth players. Table 3.1 shows the general training characteristics of the players.

Table 3.1. Scores of general characteristics related to training of talented youth field hockey players

classified by gender and level of performance (mean; standard deviation).

Female youth players Male youth players

Elite players

n = 17

Sub-elite

players

n = 46

Elite players

n = 21

Sub-elite

players

n = 42

Age (years) 13.18 (1.29) 14.15 (1.25) 13.24 (1.26) 14.19 (1.29)

Field hockey experience (years) 8.45 (1.47) 7.65 (1.62) 7.38 (2.01) 7.61 (2.09)

Training sessions per week 2.75 (0.72) 2.21 (0.41) 3.10 (0.62) 2.20 (0.56)

Matches per week 1.05 (0.22) 1.00 (0.00) 1.24 (0.44) 1.00 (0.32)

Procedure All players were informed about the procedures of the study before providing their verbal consent to participate. The governing body of the clubs and the trainers also gave their permission for the study to proceed. The procedures were in accordance with the ethical


33

standards of the Medical Faculty of the University of Groningen. The players completed all tests at the end of the competitive field hockey season. They were told that the results would be used anonymously and were asked to fill in the questionnaire honestly to ensure maximum accuracy and validity of the results. Anthropometric characteristics Three variables were measured for each player: height, body mass and percentage body fat. The latter was estimated by means of leg-to-leg bioelectrical impedance (BIA) analysis (Valhalla BIA, Valhalla, Inc., San Diego, CA, USA). Both within-day and between-day coefficients of variations of these analyses were comparable to conventional commercially available BIA systems (Nunez et al., 1997). Physiological characteristics All players performed three field tests to determine four physiological characteristics. These characteristics included peak shuttle sprint performance, repeated shuttle sprint performance, slalom sprint performance and interval endurance capacity. Peak shuttle sprint and repeated shuttle sprint performance were measured by means of the Shuttle Sprint and Dribble Test (ShuttleSDT; Lemmink et al., 2004a) (see Figure 3.2). In this field hockey specific test, participants have to sprint 30 m three times while carrying a hockey stick. The players are allowed a short rest between successive 30-m sprints. The length of this rest period depends on how fast the sprint is performed: the next sprint starts exactly 20 s after the start of the previous sprint. Each 30-m sprint has three 180-degree turns, which they have to cross with both feet: after 5 m, participants have to turn and sprint back 6 m. Here they turn for the second time and sprint 10 m. After turning for the third time, they sprint back 9 m to the finish. Electronic timing lights are used to measure the time (TAG Heuer, Eraton BV Digital Timing Equipment, Weert, the Netherlands). Peak shuttle sprint performance is indicated by the time covered in the fastest of three 30-m sprints; repeated shuttle sprint performance is the total time covered by all three 30-m sprints.

34

Figure 3.2. Course for the Shuttle Sprint and Dribble Test (ShuttleSDT).

Relative and absolute test-retest reliability were shown for the sprinting part of the ShuttleSDT (Lemmink et al., 2004a). If the intraclass correlation coefficient (ICC) exceeded 0.80 and if zero lay within the 95% confidence interval (CI) of the mean difference, we concluded that no bias existed between the two measurements (peak shuttle sprint performance: ICC = 0.81 and 95% CI for d = -0.141 to 0.162; repeated shuttle sprint performance: ICC = 0.80 and 95% CI for d = -0.520 to 0.434).

Slalom sprint performance was measured by using the Slalom Sprint and Dribble Test (SlalomSDT; Lemmink et al., 2004a) (see Figure 3.3). In this field hockey specific test, players have to sprint 30 m in a zig-zag fashion with twelve 120-degree turns around cones placed 2 m apart while carrying a hockey stick. Relative test-retest reliability was shown for the sprinting part of the SlalomSDT (ICC = 0.91), whereas in terms of absolute reliability there was some evidence of systematic error (95% CI for d = -0.398 to -0.016).


35

Figure 3.3. Course for the Slalom Sprint and Dribble Test (SlalomSDT).

Interval endurance capacity was measured by using the Interval Shuttle Run Test (ISRT; Lemmink et al., 2000; Lemmink and Visscher, 2003) (see Figure 3.4). The ISRT is another sports specific field test that consists of intervals at a work to rest ratio of 2:1, turns at 20 m and an increasing running velocity. Players are required to run back and forth on a 20-m course with pylons positioned 3 m before lines marked out for the turns. The frequency of the sound signals on a pre-recorded compact disc increases in such a way that running speed is increased by 1 km·h-1 every 90 s from a starting speed of 10 km·h-1 and by 0.5 km·h-1 every 90 s from a starting speed of 13 km·h-1. Each 90-s period is divided into two 45-s periods in which players run for 30 s and walk for 15 s. Periods of running and walking are announced on the pre-recorded compact disc. During the periods of walking, players have simply to walk back and forth to the 8-m line. Players are instructed to complete as many runs as possible. The test stops when the player is unable to maintain the required pace (i.e. more than 3 m before the 20-m lines on two consecutive audio signals) or feels unable to complete the run. The number of fully completed 20-m runs is recorded as the test score. Players have to carry a hockey stick during the test. In previous research, this test has been shown to be reliable and sensitive for differences in level of performance (Lemmink et al., 2000; Lemmink et al., 2004b).

36

Figure 3.4. Course for the Interval Shuttle Run Test (ISRT).

Technical characteristics All players performed two field tests to determine three technical characteristics: peak shuttle dribble performance, dribble performance in a repeated shuttle run and performance in a slalom dribble. Peak shuttle dribble performance and dribble performance in a repeated shuttle run were measured using the ShuttleSDT (see Figure 3.2). In performing the test, players had to keep control of the ball while carrying out the 30-m sprint three times. While turning, players had to cross each turning line with both feet and the ball. Performance in the peak shuttle dribble is the time covered by the fastest of three 30-m dribbles; dribble performance in a repeated shuttle run is the total time covered by all three 30-m dribbles.

Relative as well as absolute test-retest reliability was shown for the dribbling part of the ShuttleSDT (peak shuttle dribble performance: ICC = 0.91 and 95% CI for d = -0.305 to 0.035; dribble performance in a repeated shuttle run: ICC = 0.89 and 95% CI for d = -0.840 to 0.494).

Slalom dribble performance was measured using the SlalomSDT (see Figure 3.3). In performing the test, players had to maintain control of the ball while performing the 30-m sprint with twelve 120-degree turns. Absolute test-retest reliability was shown for the dribbling part of the SlalomSDT (95% CI for d = -0.988 to 0.256), whereas in terms of relative reliability there was some evidence of systematic error (ICC = 0.78).


37

Tactical characteristics The trainers evaluated the tactical characteristics of the players. For this purpose, each of the 12 trainers filled out the ‘Tactics in Sports’ questionnaire to give their opinion about three tactical characteristics of each player: general tactics, tactics for possession of the ball and tactics for non-possession of the ball.

The ‘Tactics in Sports’ questionnaire is based on two pilot studies (Elferink-Gemser et al., internal publication 2001). In the first study, 20 highly qualified Dutch field hockey trainers established the most important tactical qualities for successful field hockey players to determine the categories of tactical qualities in the questionnaire. The qualities mentioned by the trainers can be divided into three categories. Category 1 contains general tactics, shifting in tasks from when the team does not possess the ball to when the team does possess the ball, and vice versa. Category 2 contains tactical qualities for when the team possesses the ball: positioning, overview and anticipation. Category 3 contains tactical qualities for when the team does not possess the ball: man-to-man defence, zone defence and interception.

In the second pilot study, six trainers evaluated 88 elite and sub-elite youth players using the ‘Tactics in Sports’ questionnaire, designed as a 6-point Likert scale ranging from ‘low/ moderate’ to ‘excellent’. The trainers were instructed to compare each player with top players in the relevant age category. Test-retest reliability for this checklist on tactical qualities was shown (Pearson correlation coefficient: Category 1: Z = 0.84, p < 0.01; Category 2: Z = 0.85; p < 0.01; Category 3: Z = 0.88, p < 0.01). The discriminatory power was obtained by comparing elite with sub-elite youth players. Scores on tactical qualities differed significantly for different performance levels (Category 1: Z = -3.954, p < 0.01; Category 2: Z = -5.084, p < 0.01; Category 3: Z = -6.622, p < 0.01), which means that the elite youth players were judged to be better than the sub-elite players.

Psychological characteristics All players filled in a sports specific questionnaire, the Dutch youth version of the Psychological Skills Inventory for Sports (PSIS) (Mahoney et al., 1987; Pennings et al., 1992; Bakker, 1995; Companjen and Bakker, 2003). The PSIS was developed for directly assessing an athlete’s psychological skills relevant to athletic training and exceptional performance. It assesses motivation, confidence, anxiety control, mental preparation, team emphasis and concentration. Internal consistency coefficients of all scales ranged from 0.68 for team emphasis to 0.81 for confidence. Pearson correlation coefficients for test-retest reliability ranged from 0.64 for team emphasis to 0.79 for mental preparation. The questionnaire contains forty-four 5-point Likert-type questions. A high score on the scale corresponds to the

38

psychological skill being present to a large extent. The maximum mean score on each scale is 5, and the minimum is 1. Data analysis Mean scores and standard deviations were calculated for each variable for the different sub-groups according to the five categories of performance characteristics (anthropometric, physiological, technical, tactical and psychological). A multivariate analysis of covariance (MANCOVA) was then carried out (factors of performance level and gender) to determine the effect of performance level and gender on the dependent variables in each category of characteristics. Since the relationship between test items may change with growth and development, age in years was considered a covariate. In this way, each variable was adjusted for age.

Where appropriate, analyses of covariances on each dependent variable were conducted as follow-up tests to the MANCOVA. To correct for multiple tests and thereby keep the overall alpha level below 0.05, the Bonferroni method was used.

Finally, all dependent variables were analysed together to determine which combination of measures best discriminated between the elite and sub-elite youth players. A stepwise discriminant function analysis was used in which level of performance was the dependent variable. Besides performance characteristics, age and gender were considered independent variables. An alpha of 0.05 was adopted for all tests of significance.

3.3 Results

Table 3.2 presents means and standard deviations of the multidimensional performance characteristics.

Tab

le 3

.2.

Mea

n sc

ores

(sd)

of a

nthr

opom

etric

, phy

siol

ogic

al, t

echn

ical

, tac

tical

and

psy

chol

ogic

al c

hara

cter

istic

s for

tale

nted

you

th fi

eld

hock

ey

pl

ayer

s cla

ssifi

ed b

y ge

nder

and

leve

l of p

erfo

rman

ce.

Fem

ale

yout

h pl

ayer

s M

ale

yout

h pl

ayer

s

Elite

pla

yers

n

= 17

Su

b-el

ite p

laye

rs

n =

46

Elite

pla

yers

n

= 21

Su

b-el

ite p

laye

rs

n =

42

Ant

hrop

omet

ric

char

acte

rist

ics

Leng

th (m

) B

ody

mas

s (kg

) %

Bod

y Fa

t

1.65

(0.0

1)

54.8

5 (8

.09)

21

.51

(5.5

7)

1.67

(0.0

1)

56.2

2 (7

.35)

21

.77

(5.1

6)

1.69

(0.0

1)

55.0

9 (8

.74)

9.

61 (2

.82)

1.73

(0.0

1)

59.6

9 (1

2.5)

8.

79 (3

.89)

Ph

ysio

logi

cal c

hara

cter

istic

s

Pe

ak sh

uttle

sprin

t per

form

ance

30m

(s)

Rep

eate

d sh

uttle

sprin

t per

form

ance

3x3

0m (s

) Sl

alom

sprin

t per

form

ance

30m

(s)

Inte

rval

end

uran

ce c

apac

ity (r

uns o

f 20m

)

8.82

(0.3

3)

27.1

5 (1

.01)

15

.05

(0.6

9)

55.7

6 (1

0.97

)

8.95

(0.4

0)

27.6

9 (1

.29)

15

.09

(0.7

9)

51.5

7 (1

2.72

)

8.52

(0.4

5)

26.3

1 (1

.43)

14

.52

(0.7

4)

73.0

0 (2

5.73

)

8.45

(0.3

5)

26.2

3 (1

.09)

14

.61

(0.6

5)

69.4

4 (2

1.50

) T

echn

ical

cha

ract

eris

tics

Peak

shut

tle d

ribbl

e pe

rfor

man

ce 3

0m (s

) D

ribbl

e pe

rf.in

repe

ated

shut

tle ru

n 3x

30m

(s)

Perf

orm

ance

in a

slal

om d

ribbl

e 30

m (s

)

10.1

3 (0

.60)

32

.26

(2.0

6)

19.1

8 (1

.83)

10.4

2 (0

.58)

33

.91

(3.2

8)

20.1

9 (4

.98)

9.72

(0.5

1)

30.2

2 (1

.75)

17

.43

(1.1

4)

9.83

(0.5

9)

30.8

3 (1

.98)

18

.48

(2.2

3)

Tac

tical

cha

ract

erist

ics

Gen

eral

tact

ics (

1-6)

Ta

ctic

s (po

sses

sion

of t

he b

all)

(1-6

) Ta

ctic

s (no

n-po

sses

sion

of t

he b

all)

(1-6

)

4.18

(1.0

7)

4.45

(0.7

8)

4.10

(0.6

6)

3.33

(0.7

9)

3.32

(0.5

4)

3.52

(0.6

3)

4.38

(1.0

7)

4.38

(0.8

5)

4.33

(0.7

6)

3.46

(1.0

3)

3.53

(0.8

4)

3.75

(0.7

9)

Psyc

holo

gica

l cha

ract

erist

ics

Mot

ivat

ion

(1-5

) C

onfid

ence

(1-5

) A

nxie

ty C

ontro

l (1-

5)

Men

tal P

repa

ratio

n (1

-5)

Team

Em

phas

is (1

-5)

Con

cent

ratio

n (1

-5)

4.66

(0.2

8)

3.85

(0.5

3)

3.85

(0.5

1)

2.28

(0.6

4)

3.53

(0.4

9)

3.73

(0.3

5)

4.09

(0.5

7)

3.46

(0.5

5)

3.85

(0.5

4)

2.05

(0.8

3)

3.45

(0.4

6)

3.42

(0.5

6)

4.55

(0.3

2)

3.97

(0.6

9)

4.04

(0.4

8)

2.22

(0.6

4)

3.52

(0.4

8)

3.46

(0.3

9)

4.29

(0.4

5)

3.95

(0.6

1)

3.94

(0.6

4)

2.31

(0.7

5)

3.54

(0.4

3)

3.46

(0.7

1)

40

The results of the MANCOVA showed a significant main effect for performance level (see Table 3.3). The univariate analyses of covariance revealed significant differences between elite and sub-elite youth players for two physiological variables (peak shuttle sprint performance [F (1,113) = 3.937, p < 0.05] and repeated shuttle sprint performance [F (1,113) = 7.498, p < 0.01]), for three technical variables (peak shuttle dribble performance [F (1,113) = 11.578, p < 0.01], dribble performance in a repeated shuttle run [F (1,113) = 11.111, p < 0.01] and performance in a slalom dribble [F (1,113) = 4.822, p < 0.05]), for three tactical variables (general tactics [F (1,113) = 20.592, p < 0.001], tactics for possession of the ball [F (1,113) = 48.051, p < 0.001] and tactics for non-possession of the ball [F (1,113) = 21.822, p < 0.001]) and for one psychological variable (motivation [F (1,113) = 20.916, p < 0.001]). In all comparisons, the elite youth players scored better than the sub-elite youth players. However, after correction for multiple tests, differences between the two groups of players were no longer significant for physiological variables and performance in the slalom dribble. No differences were found between the two groups for any of the anthropometric variables. Table 3.3. Results of MANCOVA for performance level, gender and performance level x gender.

Wilks’

lambda

F-value Hypothesis

df

Error

df

p-value

Performance level 0.550 4.084 19 95 < 0.001

Gender 0.192 21.011 19 95 < 0.001

Performance level x Gender 0.837 0.972 19 95 0.500

Besides a main effect on performance level, a significant main effect was found for gender. The univariate analyses of covariance showed significant differences between female and male players for anthropometric, physiological and technical variables but not for any of the tactical or psychological variables, except for confidence. Overall, males scored better than females. No interaction effects were found between performance level and gender.

Significant differences were also found for age, indicating the relevance of age as a covariate. Scores improved with age (Wilks’ lambda = 0.363, F = 8.618, Hypothesis df = 19, Error df = 95, p < 0.001) on the anthropometric, physiological and technical variables, but not on any tactical or psychological variables.

The results of the stepwise discriminant analysis are presented in Table 3.4. The model predicted that a combination of four variables would successfully discriminate between the elite and sub-elite youth players. These measures were selected in the following order of importance: tactics for possession of the ball (0.716), age (-0.518), motivation (0.463) and


41

performance in a slalom dribble (-0.310). Tactics for possession of the ball and motivation had a positive sign because higher scores denote better performance. With performance in a slalom dribble, the sign was negative since here a lower score (i.e., less time needed for the test) indicates better performance. The negative sign of age can be explained by the mean age of the elite youth players, which was lower than that of the sub-elite youth players.

Table 3.4. Summary of stepwise discriminant analysis: variables entered/removed.

Wilks’ Lambda

Exact F

Step Entered Statistic df1 df2 df3 Statistic df1 df2 p-value

1 Tactics (possession of ball) 0.683 1 1 116 53.760 1 116 < 0.001

2 Age 0.626 2 1 116 34.293 2 115 < 0.001

3 Motivation 0.574 3 1 116 28.205 3 114 < 0.001

4 Performance in a

slalom dribble

0.551 4 1 116 23.056 4 113 < 0.001

Note: At each step, the variable that minimizes the overall Wilks’ lambda is entered. Maximum number of steps is 42. Minimum partial F to enter is 3.84. Maximum partial F to remove is 2.71. F level, tolerance, or VIN insufficient for further computation.

Variables Tolerance F to remove Wilks’

lambda

Step

1 Tactics (possession of ball) 1.000 53.760

2 Tactics (possession of ball) 0.999 48.624 0.891

Age 0.999 10.447 0.683


Age 0.989 11.659 0.633

Motivation 0.980 10.414 0.626


Age 0.938 14.401 0.621

Motivation 0.966 11.590 0.607

Performance in a slalom dribble 0.941 4.793 0.574

The average squared canonical correlation was 0.670. This means that, knowing the scores on tactics for possession of the ball, age, motivation and performance in a slalom dribble,

42

estimation of the percent variance accounted for is 67%. When group membership is predicted from these four variables, 82.8% of the original grouped players are classified correctly. The other variables provided no additional information when discriminating further between the two groups of players. 3.4 Discussion

In most studies of the relation between multidimensional performance characteristics and level of performance, elite players have been compared with non-elite players. To gain more insight into the characteristics of “tomorrow’s stars”, it seems that the critical focus should be on talented youth players already detected. Importantly, most of today’s top performers played in a youth selection team when they were younger.

Not all young field hockey players who are considered talented will ultimately make it to the top, as only the very best will achieve elite status in adulthood. One cannot predict with certainty which talented youngsters will become top players, but elite players, who play in selection teams of the Dutch Field Hockey Association and of their club, have a better chance of reaching the top than sub-elite players, who play only in their club’s selection team. This is why we compared between elite youth players and sub-elite youth players.

Our results showed that the group of talented players as a whole obtained high scores on all tests. However, the elite players scored better than the sub-elite players on variables from three categories of characteristics (technical, tactical and psychological). This was the case for young talented female as well as male players. No significant differences were found between the performance groups on any of the anthropometric or physiological variables.

Researchers who have compared elite with non-elite players have reported differences in anthropometric and physiological characteristics (Jankovic et al., 1997; Panfil et al, 1997; Janssens et al., 1998; Malina et al., 2000), but comparisons between talented field hockey players seem to suggest similar scores on these characteristics. Evidently, at the elite level, differences between players are less related to physical and physiological characteristics. This finding is in accordance with the results of a study by Franks et al. (1999) on young soccer players, in which it was not possible to discriminate between players at the highest level on the basis of their physical and physiological profiles.

Elite youth field hockey players scored better than the sub-elite players on the tests for both peak shuttle dribble performance and dribble performance in a repeated shuttle run. Sprinting repeatedly over short distances with rapid changes of direction while maintaining control of the ball is an important attribute for these players. In their multidisciplinary approach to talent identification in soccer, Reilly et al. (2000) found that elite soccer players


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scored better on dribbling tasks than sub-elite soccer players. It does seem that technical qualities remain important at the elite level. Van Rossum and Gagné (1994) also confirmed the importance of technique in field hockey. In their study, Dutch coaches considered technique (motor skill) one of the most important factors affecting the performance of top-level field hockey players.

For all tactical variables, again the elite youth players scored better than the sub-elite players. This was the case for general tactics as well as tactics for possession of the ball and non-possession of the ball. Knowing when to perform the right action, an attribute also referred to as ‘game intelligence’, is crucial for a successful career in field hockey. In a study of perceptual skill in soccer, Williams (2000; p.737) stated that ‘decisions in a match have to be made under pressure with opponents trying to restrict the “time” and “space” available to perform’. A key problem, however, is how to measure this tactical insight. Considering the complex and rapidly changing environment in field hockey matches, it is very difficult to grade players’ tactical insight objectively. The trainers in this study were highly qualified and work with the club selection players throughout the season during training and match-play. These trainers are considered to be experts in the field and their opinion was used to gauge the tactical insight of the players. Reilly et al. (2000) indicated that an interdisciplinary scientific approach has to be combined with the accumulated know-how of experts such as trainers, coaches and scouts.

The only psychological variable for which the elite youth players scored better than the sub-elite players was motivation. According to Ericsson et al. (1993) and Ericsson (1996), expert performance is the end result of individual’s prolonged efforts to improve performance, and since engagement in deliberate practice is not inherently motivating, commitment on the part of the performer is required.

Reilly et al. (2000) indicated that measures of agility, speed, motivation orientation and perceptual skill were the most important indicators of talent in soccer. These findings are in line with Deshaies et al. (1979), who made clear that anaerobic power, speed, perceptual skill and motivation successfully discriminated between elite and sub-elite ice-hockey players. In our study, a stepwise discriminant function analysis was used to determine which combination of measures distinguished most clearly between the two groups of talented field hockey players. The analyses revealed that the groups could be discriminated on the basis of four variables. The most discriminating measures were tactics for possession of the ball (consisting of positioning, overview and anticipation), motivation and performance in a slalom dribble. Age discriminated between both performance groups, indicating that the elite players were younger than the sub-elite players. Although the elite players tended to be shorter and lighter

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than the sub-elite players, one cannot rule out that the most mature children were performing best at this age, since no maturity measures were taken.

The results from this study suggest that talented players cannot be distinguished from each other on the basis of the same performance characteristics that discriminate between elite and non-elite players. At the elite level, differences between players are less related to physical and physiological characteristics, and more to tactics, motivation and specific technical skills in field hockey. It is also interesting that the elite players were younger than the sub-elite players. One explanation is that the elite players started playing earlier and so had more experience than the sub-elite players (see Table 3.1). It is also possible that the time needed to master the important characteristics differs between elite and sub-elite players. Elite players may need less time to develop better performance characteristics. Not only in the guidance of young talented players to the top, but also in the detection of talented players, more attention has to be paid to tactical qualities, motivation and specific technical skills along with the time needed to master these skills.


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