Ghent Developmental Balance Test Manual Example
Ghent developmental balance test, manual Alexandra De Kegel UGent and Hilde. Qas atlas copco manual.pdf Bruininks oseretsky test of motor proficiency- 2 The Bruininks Oseretsky Test. The Ghent Developmental Balance Test aims at offering a complete developmental series of tasks, reflecting specifically the development of the child’s balance abilities. This test is fit for typically developing children between 18 months and six years zero months or for children with a similar level of balance control. Components of Standing Postural Control Evaluated in Pediatric Balance Measures: A Scoping Review. One measure (Ghent Developmental Balance Test 27) was criterion-referenced, whereas the other 20 measures were norm-referenced. Both reliability and validity statistics were presented in the original report for 10 measures (48%), whereas 9 (43.
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Sensory and motor functions are basic to all behavior. In its simplest form, the stimulus-response unit of behavior is composed of a receptor (sense organ), neural impulses traveling over afferent, central, and efferent pathways, and some resultant form of motor (muscular) response. The sense organs respond selectively to various stimuli (visual, auditory, olfactory, thermal, tactual, proprioceptive, chemical, and gravitational), and the resulting responses most often involve some form of muscular reaction appropriate to the nature of the stimuli received. Developmentally, the earliest forms of behavior are simple sensorimotor reflexes. With growth, maturation, and differentiation, the senses become more acute, and the muscles become stronger and function more smoothly. At the same time, the central nervous system matures, with its increasingly meaningful accompanying sensory perceptions, and the motor responses become better organized, while many of the reflexes give way to behaviors under voluntary control.
During the period of earliest development, when the changes are most rapid, there is a close coordination between structure and function. Gradually the functions become relatively independent of the structures. As the rate of growth slows, the structures differentiate, and the functional processes become increasingly complex; that is, once the basic structures are formed, there is little or no correlation between their normal variations in structural complexity or maturity and the increasing complexity and diversification of motor coordinations, perceptions, and other mental processes.
Neural and cortical development. Conel’s studies of the postnatal development of the human cerebral cortex (1939–1963) have been well summarized by Eichorn (1963) and by Eichorn and Jones (1958), who also point out that changes in the histologic structure coincide with developmental changes in neural function as expressed in the electroencephalogram. At birth and even at one month the cortex is very immature, with fragile cell processes, no Nissl bodies, and very few neurofibrils. The greatest cortical development occurs in the primary motor area of the upper trunk, leg, hand, and head, followed in order by primary somesthetic, visual, rhinencephalon (olfactory), and auditory areas, with other parts still very immature. By three months there are marked advances in the number of nerve fibers, both exogenous and associational, with greatest development in the motor area of the hand, frontal eye fields, and striate cortex (Gruner 1962). There is also over this period a rapid advance in myelinization of the neural fibers. This myelinization serves to channel the neural impulses along fibers and to reduce random spread of impulses across neurons. Again, at six months there is marked development, particularly in motor areas controlling the hand and upper trunk, leg, and head, while visual and somesthetic sensory growth is accelerated. Between 6 and 15 months the motor areas of the brain show less marked growth, with the order of maturity being hand, upper trunk, head, and leg. The primary visual area by now is second to the motor, with the visual association areas more developed than the somesthetic association areas.
Parallel with these histological changes, Eichorn and Jones (1958) point out that at birth the electrical activity of the cortex is very slow and irregular, with the greatest regularity in the region of the most mature cortical structure. It is possible, however, to induce some rhythmic EEG patterns in the neonate and in the month-old infant, while between one and three months there is a shift of the EEC from random activity to some patterned slow activity in the visual and auditory sensory areas of the brain.
Fetal development. We find, too, a definite parallel between early behavior and the neural histology and electrical functions in these early months. The very first actions of the fetus, according to Hooker (1943), are muscular: the rhythmic beating of the heart in the third week of gestation. This, however, is a preneural action of the heart muscle. A response (presumably neural) to stimulation was first observed at eight weeks and consisted of a lateral bending of the neck which moved the head away from a hair touching the area of the cheek. Carmichael (1946) has given an excellent account of this early fetal development. He points out the gradual involvement of the entire body and the appearance of reflexes until, by 26 weeks of gestation, the reflexes necessary to life are usually present. These reflexes include functioning of the respiratory, circulatory, and digestive systems as well as the sense organs that respond to light, sound, touch, body position, and so on.
Sensory development
Because the infant’s repertoire of responses is so limited, it is difficult to obtain exact information about sensory acuities. However, it is possible to observe and record such behaviors as visual regard, pupillary reflexes to light, startle, and changes in activity level to sounds and tactile stimulation. More recently, sensory reactivity has been recorded by observing changes in EEC and in heart rate and by such devices as observing eye nystagmus to moving striped patterns (Eichorn 1963; Fantz & Ordy 1959).
It is evident that the intact full-term newborn in some degree sees, hears, and responds to pressure, touch, taste, and change in temperature. There is evidence from his behavior and from the structures of the nervous system that of his various senses, vision is most developed.
Vision. Changes in visual acuity during the first month appear to be very slight. As observed in a standard test of infant development, soon after birth the infant will briefly regard a large moving object (such as a person) nearby and directly in his line of vision. A little less often he will regard a small bright red object in motion, when it is held about eight inches above his eyes (Bayley 1933; White, Castle, & Held 1964). At about two weeks his gaze may follow this moving object (a red plastic ring) across his visual field—right to left or the reverse (Bayley 1933). At three weeks his eyes may follow a moving person two or three feet away. At about one month he follows the red ring with up and down eye movements and, a little later, as it is moved slowly in a circle (18 to 24 inches in diameter). At six or seven weeks the infant appears to inspect his surroundings when carried in an upright position, and he turns his eyes toward the red ring at a thirty-degree angle when it is moved into his field of vision from the side. By the fourth month the infant’s retina is able to accommodate to objects at varying distances in an almost adult fashion (Haynes, White, & Held 1965).
In experimental situations several investigators have found very early evidences of differentiation of visual stimuli. Several studies have shown (Berlyne 1958; Fantz 1958) that infants three to four months of age indicate preference for (that is, spend more time looking at) patterned stimuli as contrasted with plain ones. Fantz and Ordy (1959) have shown that infants under five days of age will look more at black and white patterns than at plain-colored surfaces. Doris and Cooper (1964, p. 456) have reported a clear correlation between age and brightness discrimination among 16 infants 4 to 69 days of age. They tested this by observing nystagmic eye movements to a moving field of black and white stripes. [SeePerception, article On Perceptual Development; Vision, article On Eye Movements.]
These findings are in general agreement with the responses to visual stimulation observed in the infant mental scales. Continuing with the Bayley Scale (Bayley 1933), at around two months the baby blinks at the shadow of a hand passed quickly across his eyes, he visually recognizes his mother, and his eyes follow a moving pencil; at two and one-half months he searches with his eyes for a sound, and he regards a one-inch red cube on a table when he is held upright; at three and one-half months his eyes follow small objects, such as the red ring, a teaspoon, and a ball, as they move across the table before which he is held in a sitting position. A typical four-month-old’s occupation is to inspect his own hands; at four and one-half months he regards a pellet one-quarter inch in diameter; at five months he discriminates between strangers and familiar persons (largely visually, it would appear, from the expressive nature of his gaze). This evidence of visual discrimination of patterned objects shows advancement when at twelve months he looks with interest at colored pictures in a book. Many of his behaviors in the second year give evidence of his utilization of visual discriminations as he imitates motions, builds towers of cubes, adjusts round, square, and triangular blocks into their appropriate form-board holes, and goes on to more complex operations.
Increasing visual acuity in the first few months of life for premature and full-term infants has been assessed by Brown (1961).
Another source of information on visual development comes from the studies of ophthalmologists. Keeney (1951) has tabulated functional development of vision and binocularity for a series of ages from the third fetal month to nine years. Many of his items are identical with, or closely similar to, those already noted. We may add sensitivity to light at the seventh fetal month and a series of visual acuity fractions starting at one year, when visual acuity is about 6/60 with imperfect fusion. At two years it is at least 6/12. At two and one-half years more mature mechanisms of accommodation result in improved acuity. At three years vision is about 6/9, at three and one-half years fusion capacity is improving, at four years vision is near 6/6. At five years ocular pursuit is inferior to fixation, and at five and one-half years fusion is well established and accurate. By six to six and one-half years ocular pursuit is accurate, and the average child can discriminate letters and word symbols and begin to read. Thereafter up to the age of nine, ability to tolerate prism vergences develops and continues to increase. [SeeVision.]
Thus, we see that even though vision is present at birth and, relative to the other senses, advanced, acuity in one aspect or another continues to increase, at least up to nine years. The changes are more rapid at first and become slower with advancing age.
The eye is the most highly developed and complex of the sense organs, and we find, accordingly, that the development of visual acuity is a function of several variables, including the simple ones, brightness and hue; patterned vision, which is related to degree of complexity of both qualitative and quantitative variables; and depth discrimination, both monocular and binocular, together with the development of accommodation and convergence. Much remains to be done in clarifying and identifying the developmental aspects of all of these.
In the senses generally, and most acutely in vision, the pure sensory aspects of development are confounded with perception and the meaningful and adaptive responses to the stimuli which are presented for the study of sensory discrimination.
Hearing. The developmental pattern of auditory acuity is in many ways similar to that of vision. The normal newborn infant responds, by reflex startling, to a sharp, loud clack or the ringing of a bell near his ear (Bayley 1933). Ten days after birth he reacts to the lesser sound of a rattle and at twenty days to the sound of a softly speaking voice. The localization of the source of a sound is incipient in the two-and-a-half-month-old who may be seen to search with his eyes for the bell or rattle when sounded outside his field of vision. By three months his eyes will turn from the bell to the rattle and back, when they are sounded alternately while held eight inches apart in his field of vision. The four-month-old will turn to the right and the left to see the bell which has been rung opposite first one ear and then the other.
There is evidence of rapid cortical development in the auditory area of the cortex in the first four months. Normal acuity appears to be well developed by this age (Wever 1949). Further changes in hearing appear to be primarily perceptual. The sixto seven-month-old is interested in producing sound. He bangs his hand or a toy on the high-chair and listens. He babbles and repetitiously tries out syllables. At eight to nine months he listens selectively to familiar words and begins to respond appropriately to simple commands.
Auditory acuity varies according to the pitch of the sound (Wever 1949, p. 364). However, this variation in pitch sensitivity appears to be a function of individual differences rather than development in the infant and child. After thirty years there is some decrement in auditory acuities, and this is greater for increasingly higher pitches (Wever 1949; Sommers, Meyer, & Fenton 1961). [SeeHearing.]
Tactual and pain sensitivity. There is evidence of increasing sensitivity to pain in the first four days of life (Lipsitt & Levy 1959) and probably for a somewhat longer period of infancy. Schludermann and Zubek (1962) found no changes in pain sensitivity from age 12 through 50, though decrements occurred after that age.
The young infant clearly reacts to tactual stimulation. However, skin sensitivity also appears to increase with age. For example, Ghent (1961) studied tactual thresholds in the hands of children 5 to 11 years old and found that sensitivity increased over this age range. She also found a sex difference, with girls showing greater sensitivity and approaching the adult level of sensitivity at an earlier age. [SeePain; Skin Senses And Kinesthesis.]
Motor development
The development of motor coordinations, evidenced first in simple reflexes, appears to depend on the interactions of muscular response to stimulation, growth and increasing strength of the muscles, and the development of coordination through practice. All of these are interdependent. Practice strengthens the muscles and stimulates their growth. It also promotes learning, for example, through the simultaneous stimulation of visual and muscle senses in the eye-hand coordinations involved in reaching, grasping, and manipulating small objects. In newborn infants these coordinations are seen in such reflex responses as head lifting, various postural adjustments to body position, crawling, and reflex grasping. Soon, between one and two months, we observe playful bursts of activity in the form of arm and leg thrusts. As the muscles grow stronger, the infant is able to hold his head erect, to push his chest up by his arms, to turn from his back to his side at four months, and to sit, at first with support and by six months, alone (momentarily). By three months his hands are no longer tightly fisted, and he holds a small toy with a grasp which is no longer entirely reflex. The six-month-old will reach for a toy with one hand. (Earlier he tends to “close in on” an object, using both hands simultaneously.) He shows early manual coordination in rotating his wrist, in partially using his thumb in opposition to his fingers, in grasping, and in trying to pick up pea-sized pellets. The eight-month-old sits alone steadily, may be starting to crawl or creep, and picks up small objects with complete thumb opposition. By nine months he can get himself into a sitting position and pull to a standing one by his crib rail. The ten-month-old creeps with agility and can often walk with help, sit down, and bring his hands together for games like pat-a-cake.
The one-year-old can take a few steps alone. In the next six months he will be able to throw a ball, walk backwards, and walk up and down stairs with help. The two-year-old walks up and down the stairs without holding on, and by three years he jumps from small heights, runs, walks on tiptoe. The four-year-old can walk a line and can hop a few steps on one foot.
Individual variability. There are of course, large individual differences in the age at which children become able to do these things, as well as differences in the skill and smoothness of motor coordinations. Motor skills after early infancy are very largely determined by practice. Furthermore, there is great specificity in skills. Evidently each motor function must be practiced in order for it to be performed with skill. Ability to catch a ball cannot be used to predict ability at the high jump or the broad jump. Bayley (1951a), for example, found that for ages 4½ to 12 years, scores on a battery of ten tests of manual dexterity were unrelated to strength and showed correlations of about .40 with scores on jumping (sum of three tests) and of .28 with scores on balance (sum of five tests). Scores on jumping, balance, and strength tended to correlate with each other at around .30 for most ages. Similarly, Espenschade (1940) found for children of 13 to 17 years no relation between gross and fine motor skills, though similar gross motor activities were moderately related. For example, scores on the dash usually correlated near .60 with those for the broad jump, near .40 with the jump-and-reach, and near .40 with the distance throw.
Consistency over time. Correlations showing the degree to which scores are consistent over time, on total motor tests, are only moderate in young children. For example, in the Berkeley growth study Bayley (1935) found that correlations of scores at 27 and 30 months with scores at six younger age levels in the first two years are, with two exceptions, below .40. At later ages, between 4 and 12 years, these Berkeley children’s scores on the manual dexterity tests again show only moderate consistency over time. Scores on the 1J year test showed correlations of .29 with scores at 4ǀ years, .50 at 5J years, .49 at 6J, .55 at 7-J, and .49 at 8$ years. Espenschade (1940) gave a series of motor tests to 160 children tested at six-month intervals between the ages of 13 and 17 years. She found a fair degree of consistency over a four-year period for most individual children. Glassow and Kruse (1960) found similar stability in relative scores for girls aged 6 to 14 years, with the running and jumping scores more stable than scores for throwing. Inconsistency in these cases may be attributed to the fact that scores in adolescents tend to be related to the degree of physical maturity and strength.
As measured by scores on standard tests of motor abilities, motor skills are seen to increase continuously through infancy and childhood. The increases are greatest in the first 18 months, after which the rate appears to decelerate gradually (Bayley 1951a).
Sex differences. There is no sex difference in motor-test scores during the first 12 years (Bayley 1939). However, after this age the girls.’ scores tend to stabilize while the boys.’ scores continue to increase (Espenschade 1947). This continued increase in boys.’ scores is correlated with their continuing growth in strength (Govatos 1959). Furthermore, both strength and scores in gross motor abilities are correlated in boys with their degree of physical maturation (Jones 1944; Clarke & Harrison 1962). Those who are accelerated in puberal development are stronger and more skilled in gross motor coordinations than their more slowly maturing age peers. It is also true that the more muscular boys, with strongly masculine physiques, are stronger than those with less masculine builds (Bayley 1951b). [SeeIndividual Differences, article on Sex Differences.]
Specificity. In general, after the first 15 months of age, motor skills evidence much specificity (Bayley 1951b; Espenschade 1947; Letter 1961). It is evident also that motor skills are very responsive to practice and training (Clarke & Henry 1961; Clarke & Petersen 1961). This appears to be evident even in the very young (Holt 1960). Within normal limits and the limits of muscular strength, it should be possible to increase specific motor skills considerably through practice.
Nancy Bayley
[See alsoDevelopmental Psychology; Infancy; Senses. Related material on child development may be found inIntellectual Development; Language, article onLanguage Development; Moral Development; Personality, article On Personality Development.]
BIBLIOGRAPHY
Bayley, Nancy 1933 Mental Growth During the First Three Years: A Developmental Study of Sixty-one Children by Repeated Tests. Genetic Psychology Monographs 14, no. 1.
Bayley, Nancy 1935 The Development of Motor Abilities During the First Three Years. Washington: Society for Research in Child Development.
Bayley, Nancy 1939 Mental and Motor Development From Two to Twelve Years. Review of Educational Research 9:18–37, 114–125.
Bayley, Nancy 1951a Development and Maturation. Pages 145–199 in Harry Helson (editor), Theoretical Foundations of Psychology. Princeton, N.J.: Van Nostrand.
Bayley, Nancy 1951b Some Psychological Correlates of Somatic Androgyny. Child Development 22:47–60.
Bayley, Nancy; and Espenschade, Anna 1944 Motor Development From Birth to Maturity. Review of Educational Research 14:381–389.
Bayley, Nancy; and Espenschade, Anna 1950 Motor Development and Decline. Review of Educational Research 20:367–374.
Berlyne, D. E. 1958 The Influence of the Albedo and Complexity of Stimuli on Visual Fixation in the Infant. British Journal of Psychology 49:315–318.
Brown, C. A. 1961 The Development of Visual Capacity in the Infant and Young Child. Cerebral Palsy Bulletin 3:364–372.
Carmichael, Leonard (editor) (1946) 1954 Manual of Child Psychology. 2d ed. New York: Wiley. → See especially pages 60–185, “The Onset and Early Development of Behavior.”
Clarke, David H.; and Henry, Franklin M. 1961 Neuro-motor Specificity and Increased Speed From Strength Development. American Association for Health, Physical Education, and Recreation, Research Quarterly 32:315–325.
Clarke, H. Harrison; and Harrison, James C. E. 1962 Differences in Physical and Motor Traits Between Boys of Advanced, Normal and Retarded Maturity. American Association for Health, Physical Education, and Recreation, Research Quarterly 33:13–25.
Clarke, H. Harrison; and Petersen, Kay H. 1961 Contrast of Maturational, Structural, and Strength Characteristics of Athletes and Nonathletes 10 to 15 Years of Age. American Association for Health, Physical Education, and Recreation, Research Quarterly 32:163–176.
Conel, Jesse L. 1939–1963 The Postnatal Development of the Human Cerebral Cortex. 7 vols. Cambridge, Mass.: Harvard Univ. Press.
Doris, John; and Cooper, Lowell 1964 Brightness Discrimination in Infancy. American Psychologist 19: 456 only.
Eichorn, Dorothy H. 1963 Biological Correlates of Behavior. Volume 62, pages 4–61 in National Society for the Study of Education, Yearbook. Part 1: Child Psychology. Univ. of Chicago Press.
Eichohn, Dorothy H.; and Jones, Harold E. 1958 Maturation and Behavior. Pages 211–248 in Georgene H. Seward and John P. Seward (editors), Current
Psychological Issues: Essays in Honor of Robert S. Woodworth. New York: Holt.
Espenschade, Anna 1940 Motor Performance in Adolescence. Society for Research in Child Development, Monographs 5, no. 1.
Espenschade, Anna 1947 Motor Development. Review of Educational Research 17:354–361.
Fantz, Robert L. 1958 Pattern Vision in Young Infants. Psychological Record 8:43–47.
Fantz, Robert L.; and Ordy, J. M. 1959 A Visual Acuity Test for Infants Under Six Months of Age. Psychological Record 9:159–164.
Ghent, Lila 1961 Developmental Changes in Tactual Thresholds on Dominant and Non-dominant Sides. Journal of Comparative and Physiological Psychology 54:670–673.
Glassow, Ruth B.; and Kruse, Pauline 1960 Motor Performance of Girls Age 6 to 14 Years. American Association for Health, Physical Education, and Recreation, Research Quarterly 31:426–433.
Govatos, Louis A. 1959 Relationships and Age Differences in Growth Measures and Motor Skills. Child Development 30:333–340.
Gruner, Jean E. 1962 Histological Study of the Maturation of the Nervous System. Developmental Medicine and Child Neurology 4:626–639.
Haynes, Harold; White, Burton L.; and Held, Richard 1965 Visual Accommodation in Human Infants. Science 148:528–530.
Holt, K. S. 1960 Early Motor Development: Posturally Induced Variations. Journal of Pediatrics 57:571–575.
Hooker, Davenport 1943 Reflex Activities in the Human Fetus. Pages 17–28 in Roger Barker, Jacob S. Kounin, and Herbert F. Wright (editors), Child Behavior and Development: A Course of Representative Studies. New York: McGraw-Hill.
Jones, Harold E. 1944 The Development of Physical Abilities. Volume 43, pages 100–122 in National Society for the Study of Education, Yearbook. Part 1: Adolescence. Univ. of Chicago Press.
Keeney, Arthur H. 1951 Chronology of Ophthalmic Development: An Outline Summary of the Anatomical and Functional Development of the Visual Mechanism Before and After Birth. Springfield, 111.: Thomas.
Lipsitt, Lewis P.; and Levy, Nissim 1959 Electro-tactual Threshold in the Neonate. Child Development 30:547–554.
Lotter, Willard S. 1961 Specificity or Generality of Speed of Systematically Related Movements. American Association for Health, Physical Education, and Recreation, Research Quarterly 32:55–62.
Schludermann, E.; and Zubek, John P. 1962 Effect of Age on Pain Sensitivity. Perceptual and Motor Skills 14:295–301.
Sommers, Ronald K.; Meyer, William J.; and Fenton, Ann K. 1961 Pitch Discrimination and Articulation. Journal of Speech and Hearing Research 4:56–60.
Wever, Ernest G. 1949 Theory of Hearing. New York: Wiley.
White, Burton L.; Castle, Peter; and Held, Richard 1964 Observations on the Development of Visually-directed Reaching. Child Development 35:349–364.
Abstract
Objectives
To determine the relationships between physical and performance characteristics and level of skill in youth soccer players aged 12–16 years.
Methods
Anthropometry, maturity status, functional and sport‐specific parameters were assessed in elite, sub‐elite, and non‐elite youth players in four age groups: U13 (n = 117), U14 (n = 136), U15 (n = 138) and U16 (n = 99).
Results
Multivariate analyses of covariance by age group with maturity status as the covariate showed that elite players scored better than the non‐elite players on strength, flexibility, speed, aerobic endurance, anaerobic capacity and several technical skills (p<0.05). Stepwise discriminant analyses showed that running speed and technical skills were the most important characteristics in U13 and U14 players, while cardiorespiratory endurance was more important in U15 and U16 players. The results suggest that discriminating characteristics change with competitive age levels.
Conclusions
Characteristics that discriminate youth soccer players vary by age group. Talent identification models should thus be dynamic and provide opportunities for changing parameters in a long‐term developmental context.
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Structured talent identification and development programmes have been developed for several sports, in particular athletics, rowing and gymnastics, where success has been related to anthropometric, physiological and motor skill attributes., Although corresponding programmes for soccer are less clear, many clubs selectively enrol promising players at a relatively early age and provide specialised programmes with the goal of developing and perfecting playing ability. The selection, development and professional guidance of young players is thus a priority for many top soccer clubs in order to maintain their sporting and financial status.
It is essential, however, to understand the key elements of the talent identification and development process for soccer.3,4 Given a lack of discrete objective measures of performance, as in individual sports, identifying soccer talent is complex and requires a multivariate approach.,4, Potential predictors of soccer talent include anthropometric, physiological, neuromotor, cognitive‐perceptual and psychosocial variables.4
Until recently, talent identification programmes in professional soccer clubs have, as a rule, not been scientifically based. The development of an objective and functional model may thus facilitate the process by identifying essential variables that distinguish elite from sub‐elite soccer players, and by providing a template for the objective evaluation of such programmes. For example, among a battery of 15 anthropometric, eight physiological‐motor, three psychological and two soccer‐specific variables assessed in 31 soccer players (mean 16.4 years of age, range 15.8–16.7), agility, speed, ego orientation and anticipation were the strongest predictors of talent. Weight, aerobic power, fatigue tolerance and dribbling also contributed significantly to the variance.
Research on talented young athletes often focuses on comparisons between youth and professional players and players classified by competitive level or expertise at a certain stage of development., Evaluation of youth players is complicated by individual differences in the timing and tempo of changes in body size, functional capacities and motor proficiency during puberty and the growth spurt.7, Age, maturity status and body size contribute significantly to variation in functional capacities (endurance, speed, power) but relatively little to variation in sport‐specific skills (ball control, dribbling, passing, shooting) in soccer players aged 13–15 years., The present study considers youth soccer players of different levels of skill and expertise. It specifically attempts to identify significant predictors of talent in Flemish youth players of different playing levels in several age groups across adolescence.
Methods
The Ghent Youth Soccer Project (GYSP) was a 5 year mixed‐longitudinal study of the growth, maturation and performance of young players. The study was approved by the Ethics Committee of Ghent University Hospital. Informed parental consent and player assent were obtained.
Participants
At the beginning of the study, 160 youth soccer players playing at different levels were enrolled (mean 12.2±0.7 years of age, range 10.4–13.7). Subsequent test sessions were conducted annually over five consecutive years. Drop‐outs were offset by enrolment of new players yielding a mixed‐longitudinal sample of 232 players over 5 years (table 11).). The most important reasons for drop‐out were being injured at the date of test and being transferred to another club not participating in the study (thus influencing the player's motivation to remain in the study).
| Test session | ||||||||
|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||||
| n | 160 | 139 | 141 | 128 | 97 | |||
| Age categories | ||||||||
|---|---|---|---|---|---|---|---|---|
| Under 13 | Under 14 | Under 15 | Under 16 | |||||
| n | 117 | 136 | 138 | 99 | ||||
Participants were assigned to one of three subgroups according to playing level: elite – players on youth teams of first (highest) or second division clubs; sub‐elite – players on third and fourth division teams; and non‐elite – players on regional teams. The players were grouped on the basis of chronological age into 1 year age categories (table 11):): under 13 (12.0–12.9 years), under 14 (13.0–13.9 years), under 15 (14.0–14.9 years) and under 16 (15.0–15.9 years). Players <12 years and ⩾16 years of age were excluded as were goalkeepers, limiting the analysis to defenders, midfielders and attackers.
Procedures
Chronological age, body dimensions, functional capacities, soccer‐specific skills and skeletal age were noted or measured annually.
Anthropometry
Dimensions included height, body mass, 11 skinfolds (temporal, hyoideal, biceps, triceps, subscapular, mid‐axillary, pectoral, abdominal, suprailiac, supra‐patellar and medial calf), four circumferences (extended and flexed upper arm, mid‐thigh and maximum calf) and two diameters (biepicondylar humerus and biepicondylar femur) using standardised protocols.11 Height was measured with a fixed stadiometer (±0.1 cm) and body weight with a Seca beam balance (±0.1 kg). Skinfolds were measured with a Harpenden calliper, circumferences with a metal tape and diameters with a spreading calliper. The sum of five skinfolds (biceps, triceps, subscapular, abdominal and medial calf (SSK)) was used as an indicator of adiposity. Limb circumferences and skeletal breadths were not included in this analysis.
Functional capacities
Several tests of the EUROFIT battery were used: sit and reach (SAR) – flexibility; standing long jump (SBJ) – explosive power; hand grip strength (HGR) – static strength; bent arm hang (BAH) – upper body muscular strength and endurance; sit‐ups (SUP) – abdominal muscular strength and endurance; shuttle run (SHR) – speed and agility; and endurance shuttle run (ESHR) – cardiorespiratory endurance.12 Two additional tests were administered: vertical jump (VTJ) – explosive power; and shuttle tempo run (STR) – anaerobic capacity. The latter includes a 300 m run divided into five shuttle sprints of 10, 20, 30, 40 and 50 m in succession. Two sprint tests specific to soccer were administered: a 30 m sprint with a flying start (30 m dash, best of three trials) and a 5×10 m shuttle sprint (better of two trials). The anaerobic and soccer‐specific sprint test procedures are described in Philippaerts et al13 and Verheijen.14
Soccer‐specific skills
Four soccer tests were used.15 The slalom dribble required players to navigate a ball around nine cones (2 m apart) from the start to end lines and return (better of two trials). The lob pass required the player to kick a soccer ball from a distance of 20 m into an area divided into three concentric circles (3, 6 and 9.15 m in diameter). Each kick was scored by the circle in which the ball initially landed (3, 2 and 1 points, respectively). Ten attempts (five with each foot) were allowed with a maximum of 30 points. A test of shooting accuracy required the player to kick the ball at a 16 m wide goal target from a distance of 20 m. The goal was divided into five parallel goals: centre, 2 m wide (3 points); two areas 3 m on each side of the centre (2 points); and two areas 4 m wide at each extreme (1 point). Ten shots (five with each foot) were allowed with a maximum of 30 points. For the juggling test, the number of times players touched the ball before it bounced on the ground was recorded. The juggling test (two trials) had a maximum score of 200 points (100 per attempt). The soccer tests were performed on a soccer field and players wore soccer clothing and shoes.
Skeletal age
Skeletal maturation was assessed by a paediatrician using the TW2 method.16 The difference between chronological and skeletal ages was used as a covariate in the analysis as boys advanced in biological maturity generally perform better than boys who are on time or delayed.7,17
Analysis
The 17 dependent variables were grouped into five clusters for analysis: anthropometry (height, weight, SSK); strength, power and flexibility (SAR, SBJ, SUP, BAH, VTJ); speed (30 m dash, SHR, shuttle sprint); cardiorespiratory endurance and anaerobic capacity (ESHR, STR); and technical skill (lobbing, dribbling, shooting, juggling). Multivariate analyses of covariance (MANCOVA) with maturation as the covariate were used to compare the dependent variables among players within each age group by competitive level (elite, sub‐elite and non‐elite). Tukey post hoc tests were used after a significant main effect. Age group‐specific stepwise discriminant analyses were used for performance related components with competitive level as the dependent variable. SPSS version 12.0 was used with a p<0.05 level of significance.
Results
Results of the MANCOVAs are presented in table 22.. Maturity status (that is, the difference between skeletal age and chronological age) significantly affects anthropometry in all age groups. It also significantly affects strength, power and flexibility in U14 and U15 players, and sprint speed and cardiorespiratory endurance in U15 and U16 players. In contrast, maturity status significantly influences soccer‐specific skills only in U14 players.
| Age difference | Playing level (group) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Wilks' lambda | F | df | P | η2 | Wilks' lambda | F | df | P | η2 | |
| Anthropometry | ||||||||||
| Under‐13 | 0.614 | 20.141 | 3, 96 | 0.000 | 0.386 | 0.946 | 0.899 | 6, 192 | 0.496 | 0.027 |
| Under‐14 | 0.441 | 44.361 | 3, 105 | 0.000 | 0.559 | 0.886 | 2.176 | 6, 210 | 0.047 | 0.059 |
| Under‐15 | 0.461 | 34.654 | 3, 89 | 0.000 | 0.539 | 0.852 | 2.470 | 6, 178 | 0.026 | 0.077 |
| Under‐16 | 0.514 | 18.877 | 3, 60 | 0.000 | 0.486 | 0.919 | 0.858 | 6, 120 | 0.528 | 0.041 |
| Strength, power, flexibility | ||||||||||
| Under‐13 | 0.958 | 0.851 | 5, 98 | 0.517 | 0.042 | 0.869 | 1.429 | 10, 196 | 0.170 | 0.068 |
| Under‐14 | 0.811 | 5.216 | 5, 112 | 0.000 | 0.189 | 0.834 | 2.125 | 10, 224 | 0.024 | 0.087 |
| Under‐15 | 0.817 | 3.946 | 5, 88 | 0.003 | 0.183 | 0.562 | 5.871 | 10, 176 | 0.000 | 0.250 |
| Under‐16 | 0.886 | 1.474 | 5, 57 | 0.213 | 0.114 | 0.592 | 3.422 | 10, 114 | 0.001 | 0.231 |
| Speed | ||||||||||
| Under‐13 | 0.998 | 0.050 | 3, 91 | 0.985 | 0.002 | 0.694 | 6.067 | 6, 182 | 0.000 | 0.167 |
| Under‐14 | 0.950 | 1.853 | 3, 106 | 0.142 | 0.050 | 0.755 | 5.319 | 6, 212 | 0.000 | 0.131 |
| Under‐15 | 0.785 | 8.145 | 3, 89 | 0.000 | 0.215 | 0.765 | 4.242 | 6, 178 | 0.001 | 0.125 |
| Under‐16 | 0.717 | 6.856 | 3, 52 | 0.001 | 0.283 | 0.816 | 1.852 | 6, 104 | 0.096 | 0.097 |
| Cardiorespiratory endurance, | ||||||||||
| anaerobic capacity | ||||||||||
| Under‐13 | 0.958 | 1.998 | 2, 91 | 0.142 | 0.042 | 0.911 | 2.174 | 4, 182 | 0.074 | 0.046 |
| Under‐14 | 0.971 | 1.604 | 2, 106 | 0.206 | 0.029 | 0.800 | 6.243 | 4, 212 | 0.000 | 0.105 |
| Under‐15 | 0.816 | 10.042 | 2, 89 | 0.000 | 0.184 | 0.683 | 9.327 | 4, 178 | 0.000 | 0.173 |
| Under‐16 | 0.854 | 4.698 | 2, 55 | 0.013 | 0.146 | 0.691 | 5.582 | 4, 110 | 0.000 | 0.169 |
| Technical skills | ||||||||||
| Under‐13 | 0.960 | 1.028 | 4, 99 | 0.397 | 0.040 | 0.690 | 5.047 | 8, 198 | 0.000 | 0.169 |
| Under‐14 | 0.897 | 2.967 | 4, 103 | 0.023 | 0.103 | 0.697 | 5.086 | 8, 206 | 0.000 | 0.178 |
| Under‐15 | 0.961 | 0.933 | 4, 91 | 0.448 | 0.039 | 0.616 | 6.235 | 8, 182 | 0.000 | 0.215 |
| Under‐16 | 0.961 | 0.564 | 4, 56 | 0.690 | 0.039 | 0.778 | 1.869 | 8, 112 | 0.072 | 0.118 |
Anthropometry
Except for SSK in U15 players, there are no significant differences in height, weight and adiposity among the groups at each age. Elite and sub‐elite U15 players have significantly less adiposity than non‐elite players (table 33).
| Under 13 | Under 14 | |||||
|---|---|---|---|---|---|---|
| Elite (n = 48) | Sub‐elite (n = 25) | Non‐elite (n = 29) | Elite (n = 32) | Sub‐elite (n = 38) | Non‐elite (n = 41) | |
| Height (cm) | 151.8±6.6 | 151.5±5.8 | 153.5±7.6 | 157.7±8.4 | 161.3±7.7 | 160.5±8.4 |
| Weight (kg) | 40.3±6.1 | 40.8±4.8 | 42.3±8.7 | 44.3±6.5 | 48.0±7.8 | 46.7±8.8 |
| SSK (mm) | 34.3±11.0 | 39.6±12.8 | 38.8±15.9 | 36.0±9.1 | 38.5±15.9 | 44.4±19.3 |
| Under 15 | Under 16 | |||||
|---|---|---|---|---|---|---|
| Elite (n = 37) | Sub‐elite (n = 25) | Non‐elite (n = 33) | Elite (n = 35) | Sub‐elite (n = 13) | Non‐elite (n = 18) | |
| Height (cm) | 167.5±8.8 | 167.9±7.5 | 168.4±9.2 | 171.7±7.4 | 174.0±8.3 | 175.1±7.9 |
| Weight (kg) | 53.4±9.6 | 52.9±8.5 | 54.5±10.6 | 57.9±8.2 | 60.6±9.8 | 60.5±9.4 |
| SSK (mm) | 36.9±11.0a | 37.0±12.1a | 46.6±21.8b | 34.6±8.1 | 39.0±11.7 | 37.8±12.0 |
Means in the same row for the same age category having the same subscript are not significantly different at p<0.05.
Strength, power and flexibility
Strength and power differ significantly by competitive level within each age group. Among U13 and U14 players, significant differences occur primarily between the elite and non‐elite groups. Further, elite and sub‐elite U14, U15 and U16 players perform significantly better than non‐elite players on the BAH and VTJ. Flexibility (SAR) does not differ among the groups of U13 and U14 players but is significantly greater among elite U15 and U16 players (table 44).
Ghent Developmental Balance Test Manual Examples
| Under 13 | Under 14 | |||||
|---|---|---|---|---|---|---|
| Elite (n = 47) | Sub‐elite (n = 28) | Non‐elite (n = 31) | Elite (n = 34) | Sub‐elite (n = 41) | Non‐elite (n = 45) | |
| SAR (cm) | 19.0±5.7 | 18.8±6.8 | 18.1±5.1 | 20.9±6.1 | 17.6±7.1 | 18.0±6.2 |
| SBJ (cm) | 170.1±14.5a | 169.5±14.8a,b | 161.7±16.1b | 182.3±17.7a | 180.1±17.4a,b | 171.7±19.3b |
| SUP (n) | 26.4±3.9a | 24.6±3.7a,b | 23.8±3.5b | 27.5±3.1 | 26.8±3.4 | 25.7±3.4 |
| BAH (s) | 26.3±13.0a | 22.3±13.5a,b | 18.7±10.2b | 30.3±18.2a | 28.0±14.0a | 19.2±13.0b |
| VTJ (cm) | 33.7±4.7a | 32.6±5.2a,b | 30.8±4.4b | 37.1±5.4 | 37.0±4.4 | 34.4±5.5 |
| Under 15 | Under 16 | |||||
|---|---|---|---|---|---|---|
| Elite (n = 37) | Sub‐elite (n = 27) | Non‐elite (n = 32) | Elite (n = 35) | Sub‐elite (n = 12) | Non‐elite (n = 18) | |
| SAR (cm) | 22.5±6.1a | 17.1±8.1b | 16.5±6.6b | 23.2±7.1a | 20.6±8.0a,b | 14.1±7.8b |
| SBJ (cm) | 193.4±13.4a | 191.1±22.1a | 179.8±20.7b | 201.5±13.6 | 200.8±20.0 | 194.4±23.7 |
| SUP (n) | 30.2±3.0a | 28.3±3.0b | 26.0±3.9c | 30.2±3.4a | 28.3±2.7a,b | 27.5±3.3b |
| BAH (s) | 40.4±19.2a | 31.6±14.5a | 21.0±13.7b | 40.8±16.4a | 37.1±17.0a,b | 24.4±14.9b |
| VTJ (cm) | 40.1±4.5a | 40.3±4.9a | 35.6±5.9b | 44.7±5.0 | 45.0±5.8 | 41.1±6.4 |
Means in the same row for the same age category having the same subscript are not significantly different at p<0.05.
Speed
Sprint tests differ significantly among competitive levels within each age group (table 55).). Overall, elite players exhibit significantly better sprint capacity, but group differences are most apparent in U13 and U14 players.
| Under‐13 | Under‐14 | |||||
|---|---|---|---|---|---|---|
| Elite (n = 42) | Sub‐elite (n = 24) | Non‐elite (n = 31) | Elite (n = 32) | Sub‐elite (n = 38) | Non‐elite (n = 42) | |
| 30 m sprint (s) | 4.4±0.2a | 4.5±0.2a | 4.7±0.2b | 4.3±0.2a | 4.3±0.2a | 4.5±0.3b |
| SHR (s) | 20.6±1.4a | 21.2±1.6a,b | 21.4±1.2b | 20.1±1.5 | 20.2±1.2 | 20.8±1.5 |
| Shuttle sprint (s) | 14.6±0.8a | 15.2±0.8b | 15.2±0.6b | 14.4±1.2a | 15.0±0.9b | 14.9±0.9b |
| Under‐15 | Under‐16 | |||||
|---|---|---|---|---|---|---|
| Elite (n = 37) | Sub‐elite (n = 25) | Non‐elite (n = 33) | Elite (n = 31) | Sub‐elite (n = 12) | Non‐elite (n = 15) | |
| 30 m sprint (s) | 4.1±0.2a | 4.2±0.2a | 4.4±0.3b | 3.9±0.2 | 4.0±0.2 | 4.0±0.2 |
| SHR (s) | 19.8±1.3 | 20.1±1.4 | 20.4±1.2 | 19.4±1.3 | 19.0±1.0 | 19.9±1.1 |
| Shuttle sprint (s) | 13.9±0.7a | 14.6±1.0b | 14.4±1.1a,b | 13.6±1.0 | 14.2±0.7 | 14.0±0.7 |
Means in the same row for the same age category having the same subscript are not significantly different at p<0.05.
Cardiorespiratory endurance
The ESHR differs significantly by competitive level in each age group with elite and sub‐elite players performing better than their non‐elite peers (table 66).). Among U15 and U16 players, differences between the elite and sub‐elite groups are also significant. The shuttle tempo run of non‐elite players in the three youngest age groups is also significantly inferior compared with more skilled players. Among U16 players, the difference on the ESHR test between the elite players on the one hand and the sub‐elite and non‐elite players on the other is also significant.
| Under 13 | Under 14 | |||||
|---|---|---|---|---|---|---|
| Elite (n = 41) | Sub‐elite (n = 24) | Non‐elite (n = 31) | Elite (n = 32) | Sub‐elite (n = 38) | Non‐elite (n = 41) | |
| ESHR (min) | 8.5±1.5a | 8.2±1.6a,b | 7.6±1.4b | 9.5±1.4a | 9.2±0.9a | 8.2±1.4b |
| Shuttle tempo (s) | 75.3±4.6a | 76.0±5.7a,b | 77.9±4.2b | 72.4±3.8a | 74.6±4.4a,b | 76.4±5.5b |
| Under 15 | Under 16 | |||||
|---|---|---|---|---|---|---|
| Elite (n = 37) | Sub‐elite (n = 25) | Non‐elite (n = 32) | Elite (n = 33) | Sub‐elite (n = 12) | Non‐elite (n = 15) | |
| ESHR (min) | 10.8±1.2a | 9.4±1.4b | 8.7±1.7b | 11.2±1.6a | 9.8±1.0b | 9.3±1.6b |
| Shuttle tempo (s) | 69.6±3.5a | 73.3±6.2b | 75.2±6.2b | 67.5±3.8a | 69.7±3.1a,b | 72.2±4.8b |
Means in the same row for the same age category having the same subscript are not significantly different at p<0.05.
Soccer‐specific skills
Elite U13 players demonstrate significantly better dribbling, lobbing and juggling skills than non‐elite players (table 77).). In the U14 and U15 groups, the elite and sub‐elite players perform significantly better than the non‐elite players on the lobbing, dribbling and juggling tests, while in the U16 groups the elite players perform better than their peers on the lobbing (sub‐elite), juggling (non‐elite) and dribbling (sub‐elite and non‐elite) tests.
| Under 13 | Under 14 | |||||
|---|---|---|---|---|---|---|
| Elite (n = 45) | Sub‐elite (n = 25) | Non‐elite (n = 36) | Elite (n = 31) | Sub‐elite (n = 38) | Non‐elite (n = 41) | |
| Lobbing (points) | 20.8±4.5a | 21.7±4.2a | 16.1±5.3b | 22.5±3.1a | 22.0±3.3a | 19.4±5.1b |
| Dribbling (s) | 18.1±1.3a | 18.9±2.2a,b | 19.4±1.9b | 17.5±1.7a | 17.9±1.1a | 19.3±2.4b |
| Shooting (points) | 23.2±2.4 | 23.0±3.0 | 22.0±3.0 | 23.5±2.5 | 23.6±2.4 | 22.4±2.2 |
| Juggling (n) | 80.2±59.3a | 58.4±46.5a,b | 34.2±35.4b | 101.9±62.0a | 94.1±57.2a | 40.3±35.5b |
| Under 15 | Under 16 | |||||
|---|---|---|---|---|---|---|
| Elite (n = 38) | Sub‐elite (n = 24) | Non‐elite (n = 36) | Elite (n = 34) | Sub‐elite (n = 14) | Non‐elite (n = 15) | |
| Lobbing (points) | 23.1±3.2a | 24.5±2.8a | 20.2±4.3b | 23.1±4.6 | 19.1±6.0 | 21.0±5.7 |
| Dribbling (s) | 17.1±1.1a | 17.4±1.3a | 19.3±2.2b | 16.5±1.3a | 17.2±0.8a,b | 17.4±1.1b |
| Shooting (points) | 23.8±2.5a | 23.8±1.9a,b | 22.4±2.6b | 23.8±2.7 | 22.5±4.3 | 21.7±3.4 |
| Juggling (n) | 117.4±52.0a | 105.3±59.5a | 59.5±57.2b | 135.9±59.4 | 115.2±63.9 | 99.6±70.4 |
Means in the same row for the same age category having the same subscript are not significantly different at p<0.05.
Results of the stepwise discriminant analyses for each age group are summarised in table 88.. A combination of six to eight factors correctly classifies 69% to 75% of the players. Among U13 and U14 players, the variables that discriminate players by skill level include two technical, two endurance and two sprint measures. In both groups, the most discriminating factor is a soccer‐specific technical skill and then two sprints (shuttle sprint and 30 m dash). In contrast, the ESHR is the most important discriminating factor among U15 and U16 players, but technical and sprint competencies are also included. Among strength‐related variables, only abdominal strength‐endurance (sit‐ups) appears in the prediction model in U15 players. Flexibility of the lower back and upper thigh (SAR) is the second most important factor in U16 players.
| Wilks' lambda | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Step | Entered | Exact F | Significance | ||||||
| Statistic | df1 | df2 | df3 | Statistic | df1 | df2 | |||
| U13 analysis | |||||||||
| 1 | 30 m dash | 0.781 | 1 | 2 | 89 | 12.453 | 2 | 89 | 0.000 |
| 2 | Lobbing | 0.688 | 2 | 2 | 89 | 9.052 | 4 | 176 | 0.000 |
| 3 | Shuttle sprint | 0.628 | 3 | 2 | 89 | 7.605 | 6 | 174 | 0.000 |
| 4 | Shuttle tempo | 0.558 | 4 | 2 | 89 | 7.278 | 8 | 172 | 0.000 |
| 5 | Juggling | 0.478 | 5 | 2 | 89 | 7.587 | 10 | 170 | 0.000 |
| U14 analysis | |||||||||
| 1 | Juggling | 0.757 | 1 | 2 | 115 | 18.439 | 2 | 115 | 0.000 |
| 2 | 30 m dash | 0.666 | 2 | 2 | 115 | 12.831 | 4 | 228 | 0.000 |
| 3 | Shuttle sprint | 0.615 | 3 | 2 | 115 | 10.372 | 6 | 226 | 0.000 |
| 4 | ESHR | 0.577 | 4 | 2 | 115 | 8.870 | 8 | 224 | 0.000 |
| U15 analysis | |||||||||
| 1 | Sit ups | 0.679 | 1 | 2 | 87 | 20.587 | 2 | 87 | 0.000 |
| 2 | ESHR | 0.545 | 2 | 2 | 87 | 10.029 | 4 | 170 | 0.000 |
| 3 | SSK | 0.506 | 3 | 2 | 87 | 8.520 | 6 | 168 | 0.000 |
| 4 | Shuttle sprint | 0.469 | 4 | 2 | 87 | 7.630 | 8 | 166 | 0.000 |
| 5 | Dribbling | 0.427 | 5 | 2 | 87 | 7.240 | 10 | 164 | 0.000 |
| 6 | 30 m dash | 0.409 | 6 | 2 | 87 | 7.696 | 12 | 164 | 0.000 |
| U16 analysis | |||||||||
| 1 | ESHR | 0.713 | 1 | 2 | 58 | 11.672 | 2 | 58 | 0.000 |
| 2 | SAR | 0.557 | 2 | 2 | 58 | 9.693 | 4 | 114 | 0.000 |
At each step, the variable that minimises the overall Wilks' lambda is entered. Maximum number of steps is 34; *maximum significance of F to enter is 0.05; minimum significance of F to remove is 0.10; F level, tolerance, or VIN insufficient for further computation.
Discussion
Williams and Reilly have suggested that process measures of performance in young soccer players may be more appropriate than performance‐outcome measures as long‐term predictors of potential in the sport. The present study used performance‐outcome measures in a cross‐sectional analysis of youth players in four age groups (U13, U14, U15 and U16). Biological maturity status (skeletal age minus chronological age) influences the size, adiposity, functional capacities and sport‐specific skills of youth players. When maturity status is statistically controlled for, elite players in each age group are characterised only by less adiposity (SSK). U15 and U16 elite players showed the best results for flexibility. Elite players performed better than their non‐elite peers on strength and power items, but intermediate level players (sub‐elite) did not differ from the elite and non‐elite players on these items. The pattern was similar for speed items, except for the U16 players. Performance on aerobic endurance and anaerobic capacity items also differed by competitive level in favour of elite players.
In contrast to anthropometry and functional capacities, only the dribbling test differed among players by competitive level at all ages. It interesting that the shooting accuracy test showed poor discriminating power and also did not differ among the four age groups. Younger players performed as well on this test as did older players. The results thus suggest that the shooting test may not be a priority item in talent identification models.
The speed items and technical skills did not differ among competitive levels in the U16 group, but elite players demonstrated better performances compared with the non‐elite players. The large within‐group variation was responsible for the non‐significant differences.
Overall, the results are generally consistent with previous research in light of the fact that the sub‐elite players in the earlier study (those not signed for a professional club but playing regularly for various local and school teams) corresponded to the sub‐elite and non‐elite players in the present design. Consistent with previous multidimensional investigations of youth soccer and field hockey, results of the present study highlight the better discriminating power of functional variables compared with anthropometric variables., Note, however, that variation in maturity status was statistically controlled for in this study.
The current data demonstrate differences between elite players and non‐elite players and to a lesser extent between sub‐elite players and non‐elite players. While differences between regional players on the one hand and elite and sub‐elite players on the other are already apparent in early adolescence, it is possible that the distinction between elite and sub‐elite players becomes more apparent in the later stages of an adolescent's soccer career. It has been suggested that it takes at least 10 years to achieve expert performance, while in soccer, on average, 18 years of age appears to be the critical time for decisions (self, club) about continuing in high level competition.21,22, Young adult players (U21) also often experience difficulty by having less playing opportunities to progress from youth to senior level. It is thus possible that in young adulthood there are greater differences between elite players (international and first national division) and sub‐elite players (semi‐professional or playing in lower divisions). Unfortunately, detailed information about player soccer history was not available, but elite youth players participated in 6–7 h/week of combined competitive play and soccer training per week (four or five sessions including a game), sub‐elite youth players had on average 4–5 h/week (three sessions including a game) and non‐elite players had on average 3–4 h/week (two sessions including a game).
Characteristics that significantly discriminated among age groups varied. Speed and soccer technique were important discriminating characteristics in U13 and U14 players, while aerobic endurance was more important in U15 and U16 players. Trunk strength/endurance (SUP), adiposity (SSK), speed (shuttle sprint and 30 m dash) and dribbling were also important discriminating factors in U15 players.
The parameters highlighted by the discriminant analyses correspond well with characteristics suggested as essential in soccer specific test batteries and with the changing physiological demands of senior soccer.,25, Among youth players, the variation in discriminating factors may be associated with differential timing of the adolescent growth spurt and sexual maturation,, and consequently with the timing of the physical components' trainability.,,,31 Samples of 51 and 25 players were measured annually on five and four occasions, respectively, in this study. Estimated age at peak height velocity is somewhat earlier than in the general population of adolescent boys and adolescent changes in functional capacities vary relative to the timing of peak velocity of growth in height. Unfortunately, sample sizes are too small for potential variation in the timing of adolescent changes to be addressed in players by competitive level. Nevertheless, longitudinal change within individual players by skill level merits consideration in future research.
What is already known on this topic
The selection, development and professional guidance of young players is a priority for many top soccer clubs.
Identifying talent in a team sport such as soccer is complex and a multivariate approach is appropriate.
Evaluation of youth players is complicated by individual differences in growth spurt, functional capacities and motor proficiency during puberty.
What this study adds
Speed and soccer technique are important discriminating characteristics in U13 and U14 players, while aerobic endurance is more important in U15 and U16 players.
Discriminating factors among youth players may vary with the timing and tempo of the adolescent growth spurt.
Talent identification and development is a dynamic process and differential opportunities for youths who differ in maturity and progress should be considered.
The results of the present analysis demonstrate that talent identification is a dynamic process and should provide opportunities for development in the long term. This is emphasised in the analysis of Martindale et al3 which highlights four important premises in the process of becoming a top level athlete: long term goals and methods, a wide range of coherent support and messages (philosophy), focus on appropriate development and not on early selection, and focus on individualised development. The results of this cross‐sectional analysis of a mixed‐longitudinal sample of adolescent players are suggestive but point to the need for longitudinal analysis.
As noted, the analysis is limited by its cross‐sectional nature. The variables considered did not include perceptual‐cognitive, tactical and psychological characteristics; although data for psychological parameters were collected at the last two time points, these data were not included because there were too few subjects for the statistical techniques used. Research on perceptual‐cognitive skills of youth players is quite limited and is generally laboratory‐based.
In summary, the present study indicates that elite and non‐elite youth soccer players differ greatly in functional capacities and sport‐specific skills. Performances of sub‐elite players are generally intermediate, although a clear distinction with elite players is not consistently evident. The results also highlight the relevance of specific tests at different ages during adolescence. Age‐specific reference values for the total sample of youth soccer players may be useful for trainers and coaches in both the talent evaluation and development processes.13
Acknowledgements
We thank Filip Stoops and Dominique Cauwelier for their contributions to this project.
Abbreviations
BAH - bent arm hang
ESHR - endurance shuttle run
HGR - hand grip strength
MANCOVA - multivariate analysis of covariance
SAR - sit and reach
SBJ - standing long jump
SHR - shuttle run
STR - shuttle tempo run
SUP - sit‐ups
VTJ - vertical jump
Footnotes
The Ghent Youth Soccer Project was supported by grants from the National Lottery Belgium (Nationale Loterij België) and DEXIA Bank.
Competing interests: None declared.
References
Ent Balance Test
Medical Balance Test
Ghent Developmental Balance Test Manual Examples
