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Abstract

Successful talent identification increases the chances of sporting and financial success since it provides talented children and adolescents with the most optimal learning environment to realize their potential. Hence, coaches and clubs of many sport disciplines are eager to identify talented athletes. General motor skills are often incorporated in talented identification research, as it is considered fundamental to learning sport-specific motor skills. This systematic review aimed to examine to what extent general motor skills can contribute to the identification of talented athletes aged six to eighteen. Five electronic databases were searched, which resulted in 22 eligible studies (13 cross-sectional and 9 longitudinal studies). Quality assessment was done using the Quality Assessment with Diverse Studies tool. The vast majority of both cross-sectional and longitudinal studies found either differences in general motor skills in favour of the talented athletes (59% of the studies) or no differences between talented athletes and their peers (36% of the studies). These results show that assessing general motor skills could contribute to talent identification programs, but caution should be paid prior to the implementation of these general motor skill test batteries due to the inconclusive nature of the findings. Hence, there is a need for future high-quality longitudinal studies which are recommended to conduct sex- and age-specific analyses, address the existing gap in the literature by including athletes from diverse sports beyond football, and investigate whether assessing manipulative skills and capturing movement quality could be a valuable addition to assessing locomotor skills for identifying athletic talent.

Keywords

Adolescents athletic performance children test batteries sports

Introduction

Successful talent identification increases the chances of sporting and financial success by providing talented athletes with the most appropriate learning environment to realize their potential.^1–5 Hence, coaches and clubs of a wide range of sport disciplines are eager to identify talented athletes: individuals whose athletic performances are superior to their peers and who are capable of reaching or have already achieved performances at top level in an event or discipline.^6,7 However, the identification of talented athletes out of a big pool of sports participants is extremely difficult since there are many performance characteristics that contribute to successful sports performance.^8,9 Moreover, determinants of later success are often non-linear, which further complicates the prediction of future performance level.^2,5,10,11 Therefore, evidence-based approaches to unravel the performance characteristics of talented athletes recently received a lot of attention among coaches, clubs, and researchers.^4,12,13

Motor skills performance is one of the characteristics that is often incorporated in talent identification research.^5,12,14 A motor skill is defined as a learned sequence of movements that combine to produce a smooth, efficient action in order to achieve an intended outcome.^15,16 To assess motor skills of athletes, general (i.e., non-sport-specific) as well as sport-specific test batteries were used in previous research of which the former has some advantages over the latter.^12,14 Firstly, the use of general test batteries allow for comparison of motor skills across studies and between sports. Secondly, as general motor skills are considered to be a prerequisite to learn sport-specific skills, general test batteries might give insights into the potential of an athlete rather than current performance level.^17–19 Thirdly, general test batteries can be useful for talent detection, identification and development, whereas sport-specific test batteries are only useful when an individual is and stays involved in a sport (i.e., talent identification).

Talent identification programs aim to discover youth athletes with high potential, thereby facilitating their access to an optimal training environment and enhancing their chances of successful performance at senior levels. Accordingly, previous research that aimed to identify talented athletes on the basis of general motor skills included athletes from varying ages, but most frequently focussed on children and adolescents (6–18 years old) as peak performance is typically achieved in adulthood (> 18 years old) for most sports^12,14,20 Moreover, prior studies incorporated athletes from different sports, levels of expertise and sexes, and vary from assessing general motor skills at one point in time to conducting one or several follow-up measurements.^12,14 Hence, although multiple studies have been performed about the role of general motor skills in talent identification, it remains unknown whether general motor skills can contribute to the identification of talented athletes due to the diversity of study designs that were used. This problem was recognized by O’Brien-Smith et al.¹⁴ who conducted a systematic review about the use of the Körperkoördinationstest für Kinder (KTK) in the talent pathway of youth athletes. The KTK is a valid and reliable general motor skill test battery and consists of four subtests: balancing backwards, moving sideways, jumping sideways, and hopping for height. The results of these subtests are summarized in a Motor Quotient. Results of the study of O’Brien-Smith et al.¹⁴ indicated that the KTK is a useful test battery to incorporate in the talent identification process since it could successfully distinguish higher from lower performing athletes across a range of sports. However, although this systematic review provided novel insights, the study was limited to including one of the multiple general motor skill test batteries that have been used in previous research. Therefore, knowledge regarding the value of the (subtests of the) remaining test batteries which are being used by professionals in the field to identify talent, such as the Test of Gross Motor Development²¹ and the German Motor Test 6–18,²² remains lacking. The current systematic review gives an update on the findings of O’Brien-Smith et al.¹⁴ and broadens its perspective by including multiple general motor skill test batteries which are commonly used in practice.

This systematic review aims to examine to what extent general motor skills can contribute to the identification of talented athletes at the age of six to eighteen years old. To address the aim, the results of cross-sectional studies and longitudinal studies will be subdivided throughout this systematic review as the definition of talent is twofold: talented athletes are defined as (1) individuals whose athletic performances are superior to their peers and (2) who are capable of reaching or have already achieved performances at top level in an event or discipline.^6,7 Cross-sectional studies can identify differences between athletes who are superior compared to their peers, but cannot give insights into whether the athlete will actually achieve a higher performance level in the future. Therefore, the conclusion that can be drawn from cross-sectional studies differs from those of longitudinal studies. Since adequate general motor skills are considered to be fundamental to learn sport-specific skills,^17–19 it is hypothesized that talented athletes outscore their peers on general motor skills. Insights into the role of general motor skills in identifying athletic talent may aid coaches, clubs and researchers in sport sciences to improve talent identification programs, which in turn increases the chances of sporting and financial success.

Methods

This systematic review was written in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines.²³

Search strategy

A systematic search of the electronic databases CINAHL, Embase, PubMed, PsycInfo and Web Of Science was conducted on September 15, 2023. The search consisted of keywords related to four main domains: (1) motor skills, (2) test, (3) children or adolescents, and (4) talent. These domains were combined using the AND operator and keywords within a domain were combined using the OR operator. The complete search strings, adapted according to the requirements of the databases, can be found in Appendix A. The search results of all included databases were combined and duplicates were removed.

Selection process and eligibility criteria

The title and abstract screening was performed independently by two researchers using the Rayyan software. In case of discrepancy, the study was discussed until consensus was achieved. Studies were deemed eligible if (1) a general motor skill test was included and (2) the study population involved healthy athletes with (3) a mean age between the 6 and 18 years old at time of testing the motor skills. Furthermore, (4) the study population had to be divided into talented athletes and participants of a lower performance level based on current performance level or performance level in the future. Studies that were not available in the English language as well studies from secondary data sources (e.g., systematic reviews) were excluded from the selection of studies. Studies that passed or could not be excluded based on the title and abstract screening were checked on eligibility based on full-text screening.

Twenty percent of the full-text screening was performed independently by two researchers. Since the predefined criterium of a Cohens kappa interobserver agreement of above the 0.80 was met (κ = 0.83), the remainder of the full-text screening was conducted by one researcher. Studies were included if a minimum of two items of a validated test battery were used to assess general motor skills. Moreover, studies had to relate the general motor skill test scores to performance level in sports and present these results independent of the results of other tests scores.

The included studies from the database search were searched for relevant studies through citation searching. Potential studies were then screened based on title and abstract. If a study was deemed eligible, a full-text screening was conducted and the study was included if it met the inclusion criteria. Extraction of the study characteristics and outcomes of the included studies was performed independently by two researchers. Differences in retrieval of study characteristics and outcomes were solved by discussion until a consensus was achieved.

Quality assessment

Quality assessment of the included studies was performed independently by two researchers using the Quality Assessment with Diverse Studies (QuADS) tool.²⁴ Discrepancies between researchers were solved by discussion until a consensus was achieved. Previous research has demonstrated that the QuADS tool has a substantial inter-rater reliability (κ = 0.66) and is suitable to apply in systematic reviews that include multi-method research. More information about the application of the QuADS tool in this systematic review and the classification of high, moderate and low methodological quality can be found in Appendix B.

Level of evidence

The following regulations were used to interpret the levels of evidence.^25,26 To state that there is strong evidence for or against talented athletes to outscore their peers on general motor skills, at least three good methodological quality studies with consistent results were needed, or more than four studies of at least moderate methodological quality of which more than 66% found consistent results and no more than 25% found opposite results. Weak evidence was interpreted when two out of three good methodological quality studies found consistent results, or in case more than 66% of at least three studies of low or moderate methodological quality found consistent results and no more than 25% found opposite results. There was insufficient evidence for or against talented athletes to outscore their peers on general motor skills when there were low or moderate methodological quality studies with inconsistent results (< 66% of the results inconsistent or > 25% of the studies finding opposite results) or when there were fewer than three studies of whatever quality. There was no evidence when there was only one study available.

Results

The literature search resulted in 2310 records of which 960 duplicates were removed. The remaining 1350 records were screened on title and abstract. Based on the in- and exclusion criteria, 1241 records were excluded and the remaining 109 included reports were assessed for eligibility based on full-text screening. Eventually, 22 studies were included in this systematic review. From the citation search of these studies, 28 potential studies were screened based on title and abstract. Nine reports were sought for retrieval of which none met the inclusion criteria. The PRISMA flow diagram of the selection process can be found in Figure 1.

Figure 1.

PRISMA flow diagram of the selection process.

Quality of the included studies

The quality assessment of the included studies can be found in Table 1. Twenty-one studies (95%) were classified as moderate quality (mean quality score = 71%) and one study (5%) was classified as good quality (quality score = 87%). The mean quality score of cross-sectional and longitudinal studies was 74% and 76%, respectively. Differences in quality between studies were mainly observed in the provision of recruitment data (item 9), the evidence that the research stakeholders have been considered in the research design or conduct (item 12), and the critical discussion of the strengths and limitations of the study (item 13).

Table 1.

Quality assessment of the included studies using the quality appraisal for diverse studies (QuADS) tool.²⁴

Study	1^a	2	3	4	5	6	7	8	9	10	11	12	13	Total^b	%^c	Quality
Bennet et al. ³⁰	3	3	3	1	2	3	3	3	1	3	3	0	2	30	77	Moderate
Callewaert et al. ³³	2	3	3	1	2	3	3	3	1	3	3	0	2	29	74	Moderate
Deprez et al. ⁶⁰	3	3	3	2	2	3	3	3	1	3	2	0	1	29	74	Moderate
di Cagno et al. ⁴⁷	3	3	3	3	2	3	3	3	1	2	2	0	0	28	72	Moderate
Fortin-Guichard et al. ³⁵	3	3	3	1	2	3	3	3	2	3	3	0	2	31	80	Moderate
Hohmann & Siener, ⁴⁵	3	2	3	2	2	3	3	3	2	3	3	2	3	34	87	Good
Hohmann et al. ⁴⁴	2	3	3	2	2	3	3	2	2	3	3	0	1	29	74	Moderate
Jukic et al. ⁴⁹	3	3	3	1	1	3	3	3	1	3	3	0	1	28	72	Moderate
Lovell et al. ⁴⁰	3	3	3	1	2	3	3	3	2	3	3	0	2	31	80	Moderate
Mostaert et al. ³⁷	3	3	3	1	1	3	3	2	2	3	3	0	1	28	72	Moderate
Mostaert et al. ³⁸	2	3	3	2	2	2	3	3	2	3	3	0	2	30	77	Moderate
Pion et al. ³²	2	1	3	2	1	3	3	3	1	3	3	0	1	26	67	Moderate
Platvoet et al. ⁴¹	3	3	3	1	2	3	3	2	2	3	3	1	2	31	80	Moderate
Robertson et al. ³⁴	3	3	3	1	1	3	3	2	1	2	3	0	1	26	67	Moderate
Siener & Hohmann ⁴⁶	2	3	3	2	2	3	3	3	2	3	3	2	0	31	80	Moderate
Toum et al. ⁶¹	3	3	3	1	2	3	3	1	1	3	3	1	3	30	77	Moderate
Tribolet et al. ⁶²	3	3	3	1	2	3	3	2	1	3	3	0	2	29	74	Moderate
Vandorpe et al. ³⁹	2	3	3	1	2	3	3	3	1	3	2	0	2	28	72	Moderate
Vandorpe et al. ³⁶	3	3	3	2	1	3	3	3	1	3	3	0	1	29	74	Moderate
Norjali Wazir et al. ⁶³	3	2	3	2	1	2	3	3	3	3	3	0	2	30	77	Moderate
Norjali Wazir et al. ⁶⁴	3	3	3	1	2	2	3	3	3	2	3	0	0	28	72	Moderate
Norjali Wazir et al. ³¹	2	3	3	1	2	2	3	3	1	3	2	0	2	27	69	Moderate

Note: Questions can be answered with: 0 = not at all, 1 = very slightly, 2 = moderately, 3 = complete. A higher value indicates a better quality. ^aNumber 1 to 13 correspond with the criteria of the QuADS tool;^b Total number of points calculated by taking the sum of criteria 1 to 13; ^cTotal number of points divided by the maximum number of points (=39) times 100%.

Study characteristics

Extracted data of the included studies can be found in Table 2. Publication year ranged from 2011 to 2022. Of the 22 included studies, 13 were cross-sectional and nine were longitudinal (4 retrospective, 5 prospective) in which time between initial testing and retrieval of performance level ranged from two to eight years. Among the included studies, four different test batteries were used to assess general motor skills. Seventeen studies included the Körperkoördinationstest für Kinder (KTK), three studies used two subtests of the German Motor Test (DMT) 6–18, one study utilized two subtests of the Hirtz's battery and one study assessed general motor skills using the Test of Gross Motor Development-2 (TGMD-2). The sample size of the included studies ranged from 21 to 1738 athletes of whom the age varied from 6 to 17 years old. Four studies included both boys and girls, 13 studies involved only boys and five solely girls. Across the eligible studies, football players (n = 10), artistic gymnasts (n = 2), volleyball players (n = 2), badminton players (n = 1), fencers (n = 1), figure skaters (n = 1), judoka (n = 1), rhythmic gymnasts (n = 1), dynamic hikers (sailors) and optimist sailors (n = 1), table tennis players (n = 1), and taekwondo athletes (n = 1) were represented.

Table 2.

Overview of the study characteristics and key findings of the included studies.

Author(s) (year of publication)	Study design	Sample size	Type of sample	Type of motor competence test used	Key findings
Bennett et al. (2019)	Cross-sectional	165	Australian male football players of two age groups (92 early adolescents (13.0 ± 0.6 years) and 73 mid-adolescents (14.8 ± 0.6 years)) subdivided into two performance levels: 63 tier one players (early adolescence: n = 31 and mid-adolescence: n = 32) who were part of the first league development program and 102 tier two players (early adolescence: n = 61 and mid-adolescence: n = 41) who were part of the second league development program.	Three subtests of the Körperkoördinationstest für Kinder (KTK): balancing backwards, moving sideways and jumping sideways.	No multivariate differences were found between tier one and tier two early adolescent players (F = 2.58, p = .06, ꞃ_p²= .09). Univariate analyses showed tier one players scored better than tier two players on the subtests balancing backwards (F = 4.92, p = .03, ꞃ_p²= .06) and jumping sideways (F = 6.17, p = .02, ꞃ_p²= .07). No differences were found on the subtest moving sideways (F = 2.33, p > .05, ꞃ_p²= .03). Multivariate differences were found between tier one and tier two mid-adolescent players (F = 7.42, p < .001, ꞃ_p²= .25). Univariate analyses showed tier one players scored better than tier two players on the subtests balancing backwards (F = 15.82, p < .001, ꞃ_p²= .19), moving sideways (F = 6.30, p = .01, ꞃ_p²= .09) and jumping sideways (F = 13.17, p < .001, ꞃ_p²= .16).
Callewaert et al. (2015)	Cross-sectional	47	Belgian male sailors of two age groups: 23 optimist sailors (12.3 ± 1.4 years) and 24 dynamic hikers (16.5 ± 1.6 years) were subdivided into two performance levels based on the observations and opinions of the national youth coaches into 16 elites (optimist sailors: n = 7, dynamic hikers: n = 9) who were selected for the Flemish national team and 31 non-elites (optimist sailors: n = 16, dynamic hikers: n = 15).	Three subtests of the KTK: balancing backwards, moving sideways and jumping sideways.	Multivariate differences were found between elite and non-elite optimist sailors (F = 5.606, p = .05). Univariate analyses showed elite optimist sailors scored better compared to non-elite sailors on the subtests moving sideways (F = 8.696, p = .008) and jumping sideways (F = 6.774, p = .017). No differences were found on the subtest balancing backwards (p > .05). No multivariate differences were found between elite and non-elite dynamic hikers (p > .05).
Deprez et al. (2015)	Longitudinal (retrospective)	58	Belgian male football players (16.4 ± 1.2 years). Contract status was retrieved 2.5 years later and divided the group into 29 players who ended up with a contract at a professional football club and 29 who did not.	Three subtests of the KTK: balancing backwards, moving sideways and jumping sideways.	No multivariate differences were found between contracted and non-contracted players (F = 1.804, p = .08).
di Cagno et al. (2014)	Longitudinal (prospective)	100	Italian female rhythmic gymnasts (11.3 ± 0.5 years) of which 41 elites competing at the national level (two age categories: 20 cadet (11.5 ± 0.5 years) and 21 juniors (13.3 ± 0.5 years)) and 59 sub-elite cadets competing at the regional level (10.5 ± 0.5 years). Ranking and performance scores reached by each gymnasts were retrieved up till three years after initial testing.	Three subtests of the Hirtz's battery: the low jump test, the orientation shuttle run test and the backwards ball throw test.	A higher score on the low jump test and backwards ball throw test predicted better competition scores of elite cadets three years later (R²= .28, R²_adj= .24, p < .05; R²= .35, R²_adj= .31, p < .01). A higher score on the low jump test predicted better competition scores of sub-elite cadets three years later (R²= .08, R²_adj= .06, p < .05). A higher score on the orientation shuttle run test predicted better results of junior elite athletes in competition three years later and explained a significant proportion of variance in competition scores (R²= .30, R²_adj= .26, p < .05).
Fortin- Guichard et al. (2022)	Cross-sectional¹	110	Dutch male football players who were part of the U12 youth squad within the development program of a professional football club of which 47 selected (11.8 ± 0.4 years) and 63 deselected (11.8 ± 0.3 years) for the U13 team.	Three subtests of the KTK: balancing backwards, moving sideways and jumping sideways.	Deselected players were found to outperform selected players on the subtest moving sideways (intercept = 142.4, GEE regression coefficient = 5.88, p < .05). No differences were found between selected and deselected players on the subtests balancing backwards (intercept = 91.4, GEE regression coefficient = 0.80, p > .05) and jumping sideways (intercept = 137.3, GEE regression coefficient = 4.53, p > .05)
Hohmann & Siener (2021)	Longitudinal (prospective)	502	German male football players (8.1 ± 0.7 years). Competition level was retrieved 7.9 ± 0.9 years later and divided the group in players playing at the province level (n = 41), regional level (n = 62), county level (n = 182), district level (n = 185) or city level (n = 32).	Two motor coordination subtests of the German Motor Test (DMT) 6–18: balancing backwards and jumping sideways.	Players who reached a higher performance level scored better on the subtests balancing backwards (F = 6.96, p < .001, ꞃ_p²= .06) and jumping sideways (F = 9.15, p < .001, ꞃ_p²= .07).
Hohmann et al. (2018)	Longitudinal (prospective)	316	German male football players (7.9 ± 0.5 years). Competition level was retrieved 4.6 ± 0.8 years later and divided the group in players playing at level 4 (n = 10, regional level), level 3 (n = 85, county level), level 2 (n = 180, district level), level 1 (n = 41, holder of an official club license).	Two motor coordination subtests of the DMT 6–18: balancing backwards and jumping sideways.	Football players who reached level 4 performed better compared to players who reached level 1, 2 or 3 on the subtests balancing backwards (F = 4.85, p < .01; ꞃ_p²= .044) and jumping sideways (F = 10.02, p < .001; ꞃ_p² = .086).
Jukic et al. (2019)	Cross-sectional	23	Croatian male football players (9.7 ± 0.4 years) who were all member of an elite football club were divided based on the assessment of the coach into first team (FT) players (n = 12) and second team (ST) players (n = 11).	Test of Gross Motor Development-2 which consists of locomotor (running, galloping, hopping, leaping, long jumping, and sliding) and manipulative skills (baseball strike, dribble, and catching, kicking, throwing and rolling a ball). The results of all subtests were summarized using the gross motor quotient (GMQ).	No differences were found between FT and ST players in GMQ (F = 3.01, p = .10, d = .73). Moreover, insignificant differences between the groups were found on locomotor skills (F = 3.49, p = .08, d = .82) and manipulative skills (F = 1.35, p = .26, d = .48).
Lovell et al. (2017)	Cross-sectional	140	Australian male football players (14.0 ± 1.5 years) ranging from recreational to regional level were divided into three teams (team 1, N = 48; team 2, n = 53; team 3, n = 39) with team 1 being the highest and team 3 being the lowest playing level. The allocation to the teams was based on a subjective assessment of talent by three coaches.	Three subtests of the KTK: balancing backwards, moving sideways and jumping sideways. The results were summarized in the motor quotient (MQ).	Differences were found in MQ between the three playing levels (F = 5.668, ꞃ_p²= .08, p < .05). Pairwise comparisons revealed team 1 players possessed superior motor competence compared to team 2 and team 3 players (p < .05).
Mostaert et al. (2016)	Cross-sectional	32	Belgian female figure skaters (11.3 ± 1.3 years) of which 11 elites (11.6 ± 1.2 years; selected by the Royal Belgian Figure Skating Federation) and 21 non-elites (11.1 ± 1.4 years; participated in either A, B or C level).	Three subtests of the KTK: balancing backwards, moving sideways and jumping sideways.	Multivariate differences were found between elite and non-elites (F = 3.076, p = .044, ꞃ_p² = .248). Follow-up analyses showed elites outperformed non-elites on the subtest jumping sideways (F = 5.874, p = .022, ꞃ_p² = .164). No differences were found between elites and non-elites on the subtests balancing backwards (F = 1.128, p = .297, ꞃ_p² = .036) and moving sideways (F = 3.462, p = .073, ꞃ_p² = .103).
Mostaert et al. (2020)	Longitudinal (retrospective)	1738	Belgian male (n = 587) and female (n = 1151) volleyball players (11.8 ± 0.8 years). Five years after testing, two groups were made based on performance level: 52 selected athletes (26 male, 25 female; selected for national youth teams and competed at international level) and 1686 non-selected athletes (561 male, 1125 females).	Three subtests of the KTK: balancing backwards, moving sideways and jumping sideways.	Multivariate differences were found between selected and non-selected females (F = 4.099, p = .007, ꞃ_p²= .011). Follow-up analyses showed selected athletes outperformed non-selected athletes on the jumping sideways test (F = 7.812, p = .005, ꞃ_p²= .007). No differences were found between selected and non-selected females on the subtest balancing backwards (F = .486, p = .486, ꞃ_p²< .001) and moving sideways (F = .002, p = .964, ꞃ_p²< .001). No multivariate differences were found selected and non-selected males (F = 1.671, p = .172, ꞃ_p²= .009).
Pion et al. (2014)	Longitudinal (retrospective)	21	Belgian female volleyball players (15.3 ± 1.5 years). Five years after initial testing, competition results were obtained and two groups were distinguished according to playing level: 13 elites (Belgian National Team or Belgian First division champions) and 8 sub-elites (not in the Belgian National Team and playing in any other first division team than the championship team).	Three subtests of the KTK: balancing backwards, moving sideways and jumping sideways.	Multivariate differences were found between elites and sub-elites (F = 3.470, p = .036, ꞃ_p²= .59). Univariate analyses showed elites outperformed sub-elites on the subtests balancing backwards (F = 15.131, p = .001, ꞃ_p² = .49) moving sideways (F = 6.869, p = .019, ꞃ_p² = 0.30) and jumping sideways (F = 6.304, p = .023, ꞃ_p² = 0.28).
Platvoet et al. (2020)	Cross-sectional	103	Dutch male football players (9.3 ± 0.5 years) of which 31 were selected (9.4 ± 0.4 years) and 72 were deselected (9.2 ± 0.5 years) to play in the U11 team of a first division football club.	Three subtests of the KTK: balancing backwards, moving sideways and jumping sideways. The results were summarized in the MQ.	No differences were found between selected and deselected players for the MQ (U = 1027.5, p = .263), and the subtests balancing backwards (U = 1043, p = .300), moving sideways (U = 997.5, p = .197), and jumping sideways (U = 1102, p = .460).
Robertson et al. (2022)	Cross-sectional	34	Belgian male badminton players of which 10 elites (15.8 ± 1.9 years; competed at the highest level of the Belgian competition (A, B1 & B2), international junior or senior tournaments), 24 sub-elites (15.4 ± 1.6 years; participated in the fourth, fifth and sixth levels of competition in Belgium (C2, C1 & D)).	Three subtests of the KTK: balancing backwards, moving sideways and jumping sideways.	Multivariate differences were found between elites and sub-elites (F = 3.933, p < .001, ꞃ_p²= .17). Univariate analyses showed the elites scored higher of the subtest moving sideways (F = 5.860, p = .005, ꞃ_p²= .16) and jumping sideways (F = 12.269, p < .001, ꞃ_p²= .29) compared to sub-elites. No differences were found between elites and sub-elites on the subtest balancing backwards (F = 2.249, p = .115, ꞃ_p²= .07)
Siener & Hohman (2019)	Longitudinal (prospective)	225	German male (n = 141) and female (n = 84) table tennis players (7.8 ± 0.43 years). Three to five years later competition level was retrieved and four groups were distinguished: level 4 (n = 23, national level), level 3 (n = 44, regional level), level 2 (n = 96, local level) and level 1 (n = 96, holder of an official club license).	Two motor coordination subtests of the DMT 6–18: balancing backwards and jumping sideways.	No differences were found between playing levels on the subtests balancing backwards (p > .05) and jumping sideways (F = 2.51, p = .058).
Toum et al. (2020)	Cross-sectional	64	Australian male football players (15.1 ± 0.3 years) within the Australian Football academy of which 32 were selected and 32 were deselected to progress into the U16 cohort of the academy based on the assessment of the coaches.	Three subtests of the KTK: balancing backwards, moving sideways, jumping sideways.	No differences were found between selected and deselected players for balancing backwards (F = 1.013, p = .32, ꞃ_p²= .02), moving sideways (F = 3.238, p = .08, ꞃ_p²= .06) and jumping sideways (F = .496, p = .49, ꞃ_p²= .01).
Tribolet et. (2018)	Cross-sectional	63	Australian male football players (14.9 ± 0.3 years) within the Australian Football academy of which 41 were selected (14.9 ± 0.3) and 22 were deselected (15.0 ± 0.4) to progress into the U16 cohort of the academy based on the assessment of the coaches.	Three subtests of the KTK: balancing backwards, moving sideways, jumping sideways.	No differences were found between selected and deselected players for balancing backwards (F = 0.69, p > .05, ꞃ_p²= .02), moving sideways (F = 0.99, p > .05, ꞃ_p²= .03) and jumping sideways (F = 0.60, p > .05, ꞃ_p²= .02).
Vandorpe et al. (2011)	Cross-sectional	168	Belgian female gymnasts (6–8 years old) of which 103 selected for the national talent development program and 65 non-selected based on the assessment of four expert coaches.	The KTK including the subtests balancing backwards, moving sideways, jumping sideways and hopping for height. The results were summarized in the MQ.	Selected athletes were found to outperform the non-selected athletes on the MQ (Wilks λ = 0.79, F = 22.10, p < .001).
Vandorpe et al. (2012)	Longitudinal (prospective)	23	Belgian female gymnasts (7–8 years old). Two years after initial testing, two groups were distinguished based on performance level: 12 elites (competing at the A-level) and 11 sub-elites (competing at the B-level).	The KTK including the subtests balancing backwards, moving sideways, jumping sideways and hopping for height. The results were summarized in the MQ.	Elites scored higher on the MQ (t = 2.16, p < .05), and jumping sideways (t = 2.13, p < .05) compared to sub-elites. No differences between elites and sub-elites were found on the subtests balancing backwards (t = 1.99, p > .05), moving sideways (t = .70, p > .05), and hopping for height (t = .16, p > .05). The MQ and the moving sideways subtest were found to correlate significantly with competition results of elite gymnasts two years later (MQ: r = .67, p = .02; moving sideways: r = .60, p = .04). In elites, a higher MQ score predicted higher competition level two years later (b = 0.98, t = 2.82, p = .02), and explained a significant proportion of variance in competition score (R2 = 0.44, F(1,11)= 7.95, p = .02). A higher score on the moving sideways subtest measured at initial testing also predicted better results in competition 2 years later (b = 0.80, t = 2.38, P = 0.04), and moving sideways explained a significant proportion of variance in competition score (R2 = 0.36, F(1,11) = 5.64, P = 0.04).
Wazir et al. (2017)	Longitudinal (retrospective)	16	Belgian male judo athletes (12.7 ± 0.9 years). Two to four years after initial testing, two groups were distinguished based on competition level: 6 elites (13.0 ± 0.5 years; achievements at European and world level) and 10 sub-elites (12.5 ± 1.1 years; participated in international tournaments).	Three subtests of the KTK: balancing backwards, moving sideways, jumping sideways.	No differences were found between the elites and sub-elites (p > .05).
Wazir et al. (2018)	Cross-sectional	83	Belgian male (n = 43) and female (n = 40) fencers (11–16 years old) of which 21 medallists (13.0 ± 1.3 years; won at least one medal in national youth championships competitions one year before or after they were tested) and 62 non-medallists (13.5 ± 1.8 years).	Three subtests of the KTK: balancing backwards, moving sideways, jumping sideways.	No multivariate differences were found between medallists and non-medallists (F = 0.740, p > .05)
Wazir et al. (2019)	Cross-sectional	98	Belgian male (n = 52) and female (n = 46) taekwondo athletes (12–17 years old) of which 18 elites (9 male, 9 female; member of the Belgian national team and/or had won at least one medal at an international taekwondo competition) and 80 non-elites (43 male, 37 female).	Three subtests of the KTK: balancing backwards, moving sideways, jumping sideways. The results of these tests were summarized in the MQ.	Multivariate differences were found between elites and non-elites (F = 7.207, p < .001, ꞃ_p²= .19). Follow-up analyses found elites scored higher on the subtests of balancing backwards (F = 7.951, p = .006, ꞃ_p²= .08) and moving sideways (F = 8.790, p < .001, ꞃ_p²= .18) compared to non-elites. No differences were found between elites and sub-elites on the subtest jumping sideways (F = 2.957, p = .089, ꞃ_p²= .03).

Körperkoördinationstest für Kinder

The KTK has shown to be a valid and reliable general motor skill test (r = 0.97).^27–29 The test-retest reliability of the individual subtests ranges from 0.86 to 0.96. The short version, consisting of three subtests, correlates strongly (r = 0.97) with the complete test battery.²⁹ The KTK was used in 17 studies to assess general motor skills of which two studies included the complete test battery (i.e., balancing backwards, moving sideways, jumping sideways, and hopping for height) and 15 made use of the short version of the KTK (i.e., balancing backwards, moving sideways and jumping sideways). Nine of the 17 studies performed multivariate analyses of which seven found significant differences between performance levels and conducted univariate follow-up analyses. Six studies performed solely univariate analyses and two studies conducted solely analyses based on the motor quotient (MQ), the summarized score of the subtests of the KTK.

Balancing backwards

Within the 15 studies (10 cross-sectional, 5 longitudinal; mean quality = 74%) that included analyses for the subtest balancing backwards, three studies (two cross-sectional, one longitudinal; mean quality = 71%) reported significant differences between performance levels. The cross-sectional studies detected differences in favour of the higher performers between tier one (part of first league development program) and tier two (part of second league development program) Australian male early (13.0 ± 0.6 years) and mid-adolescent (14.8 ± 0.6 years) football players,³⁰ and Belgian male and female elite (member of the Belgian national team and/or had won at least one medal at international taekwondo competition) and non-elite taekwondo athletes (12–17 years).³¹ The remaining eight cross-sectional studies reported no significant differences between talented athletes and their peers on the subtest balancing backwards. Therefore, there is insufficient evidence that athletes of a higher performance level in their childhood or adolescence outperform their peers on the balancing backwards subtest.

The longitudinal study of Pion et al.³² revealed that Belgian female volleyball players (15.3 ± 1.5 years) who reached elite level (part of the Belgian national team or Belgian first division champion) five years after initial testing scored better on the balancing backwards subtest than sub-elite volleyball players. Since the remaining four longitudinal studies reported no significant differences, there is insufficient evidence to state that a higher score on the balancing backwards subtest is related to performance level in the future.

Moving sideways

Seven (five cross-sectional, two longitudinal; mean quality = 73%) of the 15 studies (10 cross-sectional, 5 longitudinal; mean quality = 74%) that included analyses regarding the moving sideways subtest reported significant differences between talented athletes and their lower performing counterparts. Four out of five cross-sectional studies found differences in favour of the talented athletes. These differences were prevalent between tier one and tier two Australian male mid-adolescent (14.8 ± 0.6 years) football players,³⁰ Belgian male elite (selected for the Flemish national team) and non-elite optimist sailors (12.3 ± 1.4 years),³³ Belgian male elite (15.8 ± 1.9 years; competed at the highest level of Belgian competition or in international tournaments) and sub-elite (15.4 ± 1.6 years; competing at the fourth, fifth or sixth level of Belgian competition) badminton players,³⁴ and Belgian male and female elite and non-elite taekwondo athletes (12–17 years).³¹ In contrast, one cross-sectional study including Dutch male selected (11.8 ± 0.4 years) and deselected (11.8 ± 0.3 years) players for the U13 team of a professional football club, found that deselected players outperformed selected players on the moving sideways subtest.³⁵ The remaining five cross-sectional studies reported no significant differences between talented athletes and their peers on the subtest moving sideways. Hence, there is insufficient evidence that athletes of a higher performance level in their childhood or adolescence outperform their peers on the moving sideways subtest.

Results of the longitudinal study showed that Belgian female volleyball players (15.3 ± 1.5 years) who reached elite level five years after initial testing scored better on the moving sideways subtests than sub-elite volleyball players.³² Although the results of the longitudinal study of Vandorpe et al.³⁶ showed no differences on the moving sideways subtest between the Belgian female gymnasts (7–8 years) who ended up competing at A-level (elites) and those who competed at B-level two years after initial testing, a higher score on the moving sideways measured at initial testing predicted better results in competition of elite gymnasts two years later. The remaining three longitudinal studies reported no significant differences between talented athletes and their peers on the subtest moving sideways. These results show that the evidence supporting the predictive value of the moving sideways subtest on performance level several years after testing is insufficient.

Jumping sideways

Seven (four cross-sectional, three longitudinal; mean quality = 73%) of the 15 studies (10 cross-sectional, 5 longitudinal; mean quality = 74%) that included analyses for the subtest jumping sideways detected significant differences between talented athletes and their peers. All cross-sectional studies found differences between performance levels in favour of the talented athletes. Differences were found between tier one and tier two Australian male early (13.0 ± 0.6 years) and mid-adolescent (14.8 ± 0.6 years) football players,³⁰ Belgian male elite and non-elite optimist sailors (12.3 ± 1.4 years),³³ Belgian female elite (selected by the Royal Belgian Figure Skating Federation) and non-elite (participating in either A, B or C-level) figure skaters (11.3 ± 1.3 years),³⁷ and Belgian male elite (15.8 ± 1.9 years) and sub-elite (15.4 ± 1.6 years) badminton players.³⁴ The remaining six cross-sectional studies reported no significant differences on the jumping sideways subtest between talented athletes and their peers. This results in insufficient evidence to state that athletes of a higher performance level in their childhood or adolescence outperform their peers on the jumping sideways subtest.

A longitudinal study on Belgian male and female volleyball players (11.8 ± 0.8 years) revealed that those who were selected for the national youth teams five years after initial testing outscored non-selected athletes on the jumping sideways subtest.³⁸ These results were also prevalent between Belgian female volleyball players (15.3 ± 10.5 years) who ended up as elites and sub-elites.³² The longitudinal study of Vandorpe et al.³⁶ found that Belgian female gymnasts (7–8 years) who ended up competing at A-level (elites) outperformed those who ended up competing at B-level on the jumping sideways subtest. The remaining two longitudinal studies reported no significant differences between talented athletes and their lower performing peers levels on the subtest jumping sideways. Hence, there is insufficient evidence to suggest that those athletes with a higher performance level several years after performing the jumping sideways subtest, outscore their peers in childhood or adolescence.

Motor quotient

Four (three cross-sectional, one longitudinal, mean quality = 77%) of the 17 studies (11 cross-sectional, 6 longitudinal; mean quality = 74%) reported results regarding the MQ. Two studies based the MQ on the tests scores of all four subtests of the KTK and both included Belgian female gymnasts between 6 and 8 years old.^36,39 The cross-sectional study of Vandorpe et al.³⁹ found that gymnasts who were selected for the national development program outperformed the non-selected athletes.³⁹ The longitudinal study of Vandorpe et al.³⁶ found that elites scored higher on the MQ compared to sub-elites.³⁶ Moreover, higher scores on the MQ were found to correlate significantly with better competition results of elite gymnasts two years later. Furthermore, a higher MQ score predicted a higher competition level two years later, and explained a significant proportion of variance in competition score. The remaining two studies were of cross-sectional design and based the MQ on three subtests of the KTK (i.e., balancing backwards, moving sideways, jumping sideways). Differences were found between regional and recreational level Australian male football players (14.0 ± 1.5 years old) in favour of the higher performers,⁴⁰ while no differences were found between Dutch male football players who were selected or deselected to play in the U11 team of a first division football club (9.3 ± 0.5 years old).⁴¹ The results show that there is insufficient evidence to state that talented athletes outperform their peers on the MQ in childhood or adolescence. As only one longitudinal study has been conducted up till now, there is no evidence to state that the MQ is predictive of future performance level.

German motor test 6–18

The DMT 6–18 has shown good construct validity (χ²= 112.3; CFI = 0.956; RMSEA = 0.07) and adequate reliability (between r = 0.73 and 0.96).^22,42 Two subtests of the DMT 6–18 (i.e., balancing backwards, jumping sideways) were used to assess general motor skills in three longitudinal studies (mean quality = 80%). The validity and reliability of the balancing backwards subtest has been established at r = 0.90 and r = 0.73, respectively, while for the jumping sideways subtest, these values are r = 0.99 and r = 0.89, respectively.^22,43 Hohmann et al.⁴⁴ revealed that German male football players (7.9 ± 0.5 years) who reached regional level 4.6 (± 0.8) years after initial testing outscored athletes of country level, district level and holders of an official club license on both subtests. Moreover, a study conducted by Hohman and Siener⁴⁵ showed that German male football players (8.1 ± 0.7 years) who reached a higher performance level 7.9 (± 0.9) years after initial testing, scored better on the subtests balancing backwards and jumping sideways. In contrast, Siener and Hohmann⁴⁶ found no differences in test scores between German male and female table tennis players (7.8 ± 0.43 years) who turned out to play at different performance levels (national level, regional level, local level or holder of a club licence) three to five years after conducting the DMT 6–18. Hence, the results show that the evidence supporting the predictive value of the subtests of the DMT 6–18 on performance level several years after testing is insufficient.

Hirtz's battery

Three subtest of the Hirtz's battery (i.e., low jump, orientation shuttle run, and backwards ball throw) were used in one longitudinal study (quality = 72%) to assess general motor skills.⁴⁷ The Hirtz's battery is a valid test battery with a high test-retest reliability (r = 0.97). The results of this study indicated that a higher score on the low jump test and backwards ball throw test predicted better competition scores of Italian elite (competing at national level) female rhythmic gymnast cadets (11.5 ± 0.5 years) three years later. In sub-elite (competing at regional level) cadets (10.5 ± 0.5 years) a higher score on the low jump test predicted better competition scores three years later. Lastly, a higher score on the orientation shuttle run test predicted better results of junior athletes (13.3 ± 0.5 years) in competition three years later and explained a significant proportion of variance (30%) in competition scores. As there is only one study available including the Hirtz's battery to assess general motor skills, there is no evidence to support the predictive value of the Hirtz's battery on performance level several years after testing.

Test of gross motor development-2

The TGMD-2 has demonstrated good construct validity (X²= 280.3; GFI = 0.96; AGFI = 0.95) and test-retest reliability (between r = 0.85 and 0.98).⁴⁸ One of the included studies (quality = 72%) assessed general motor skills among Croatian male football players (9.7 ± 0.4 years years) using the TGMD-2 comprising of the subtests running, galloping, hopping, leaping, long jumping, sliding, baseball strike, dribble, and catching, kicking, throwing and rolling a ball.⁴⁹ This cross-sectional study found no differences between first and second team players of an elite football club. As there is only one study available including the TGMD-2 to assess general motor skills, there is no evidence to support the predictive value of the test battery on performance level several years after testing.

Discussion

The aim of this systematic review was to examine to what extent general motor skills can contribute to the identification of talented athletes at the age of six to eighteen years old in order to aid professionals in the field to improve talent identification programs. Consequently, 22 moderate to good quality studies were included of which 13 cross-sectional and 9 longitudinal studies. Within the cross-sectional studies, seven studies (54% of all included cross-sectional studies) found significant differences in general motor skills in favour of the athletes of a higher performance level in childhood or adolescence, five studies (38%) detected no significant differences and one study (8%) found that the lower performers significantly outscored their higher performing peers. Among the studies of a longitudinal study design, six studies (67% of all included longitudinal studies) found significant differences in childhood or adolescence in favour of the athletes who went on to compete at a higher level years later, and three studies (33%) found no significant differences. Taken together, the vast majority of both cross-sectional and longitudinal studies found either differences in general motor skills in favour of the talented athletes (59% of studies) or no differences between talented athletes and their peers (36% of studies). These results suggest that assessing general motor skills could contribute to talent identification programs by distinguishing higher from lower performing athletes in childhood and adolescence as well as identifying those with the potential to reach a higher performance level in the future. However, caution should be paid prior to the implementation of these general motor skill test batteries in talent identification programs due to the inconclusive nature of the findings.

The most commonly used general motor skill tests in the included studies were balancing backwards, moving sideways and jumping sideways as subtests of either the KTK²⁷ or the DMT 6 −18²² test battery. Differences in favour of the talented athletes were found in 28% of studies (20% of cross-sectional and 38% of longitudinal studies) including the balancing backwards subtest, 47% of studies (40% of cross-sectional and 50% of longitudinal studies) analysing the moving sideways subtest, and 50% of studies (40% of cross-sectional and 62% of longitudinal studies) incorporating the jumping sideways subtest. The remaining studies reported no differences between talented athletes and their peers, except for one cross-sectional study which found that the athletes of a lower performance level outscored their higher performing peers on the moving sideways subtest. Taken together, the majority of studies found no differences in general motor skills between talented athletes and their peers, but when differences were found, they were in favour of the talented athletes. Hence, there was insufficient evidence for the discriminatory and predictive power of talent for all three subtests. This could be explained by general motor skills being a prerequisite to learn sport-specific motor skills instead of a performance-determining quality.^17–19,50 A considerably larger proportion of studies found significant differences between athletes of different performance levels on the subtests moving sideways and jumping sideways compared to the balancing backwards subtest. A possible explanation for these results might be that the subtests moving sideways and jumping sideways assess the dynamic interplay between both the lower and upper segment of the body, which is important to successfully complete the task demands of many sports.^51–53 Moreover, the findings may be attributable to the time constraints which play a role in both subtests, but do not apply to the balancing backwards subtest, while time limitations in performing movements in the sport-specific context are common.⁵⁴ For example, the server in volleyball must hit the ball within eight seconds after the first referee whistles for service, gymnasts require to perform their beam routine within a time span of 90 s, and football players desire to score a goal before the final whistle. Lastly, differences between talented athletes and their lower performing peers on the subtest moving sideways could be attributable to the subtest allowing room for variation in the way the actions within the subtest are performed. Therefore, this test might measure general motor skills in combination with several psychological aspects of talent which have shown to be important to excel in sports, such as mental rehearsal and decision-making.^2,55

In addition to studies conducting separate analyses for the subtests balancing backwards, moving sideways and jumping sideways, four studies performed analyses using a composite score (i.e., the MQ) derived from three or four subtests of the KTK to identify talent. The MQ was able to discriminate talented athletes from their peers in 2 cross-sectional studies (66% of all cross-sectional studies) and 1 longitudinal study (the only one conducted). These results could be explained by the discriminative value of the individual subtests which compile the MQ. The higher percentage of studies detecting differences between talented athletes and their less proficient peers based on the MQ compared to the scores of the individual subtests could thereby be attributed to the greater amount of information available about the athletes. This enables a more accurate estimation of performance levels. Therefore, the MQ might provide a better understanding of the various general motor skills that are necessary to perform successfully across a range of sports.

The results of the current systematic review show that the discriminatory and predictive value of the subtests balancing backwards, moving sideways and jumping sideways, and the composite score of the subtests of the KTK (i.e., the MQ), is promising. However, the level of evidence supporting the notion that general motor skills can effectively identify talented athletes is still insufficient. This emphasized the need for future high-quality studies. It is recommended that these studies conduct age- and sex-specific analyses as previous research has shown that the predictive value of talent identification test batteries can vary depending on specific sex and age groups.^1,56 These results were supported by the studies of Mostaert et al.³⁸ and Callewaert et al.³³ where differences in general motor skills among athletes of different performance levels were only evident respectively within the females and the younger subgroups of athletes. In addition, given that nearly half of the studies within the current systematic review included football players, it is recommended for future studies to incorporate athletes from a diverse range of sports. This approach aims to address the current gap in the literature and provides practitioners with a more comprehensive understanding of the role of general motor skills in the talent identification process across sports. Moreover, it gives the opportunity to analyse whether the discriminative value of the subtests differ per type of sport (e.g., ball sports, combat sports and gymnastics) and helps prevent potential underestimation of the value of general motor skills in the talent identification pathway when aggregating these results. Lastly, future studies are encouraged to present the outcomes of both the individual subtests of the KTK as well as the composite score of these subtests (i.e., MQ). This approach will offer a comprehensive overview of the value of the KTK in talent identification research.

Remarkably, the vast majority of studies assessed general motor skills by using the subtests of the KTK. However, incorporating subtests from other general motor skill test batteries into talent identification research, such as subtests from the Hirtz's battery⁵⁷ and the TGMD-2²¹ which were each represented in only one of the included studies, could offer interesting insights. These test batteries evaluate different aspects of movement, potentially broadening the understanding of general motor skills relevant to talent identification. Firstly, both the Hirtz's battery and the TGMD-2 measure manipulative general motor skills, such as throwing or catching a ball. Since many sports, like football, volleyball or hockey, require the athlete to possess adequate manipulative skills, assessing these skills might be a valuable addition to the measurement of locomotor skills as done in the KTK. Secondly, the TGMD-2 captures the quality of the performed movements, whereas the scores on the subtests of the KTK are based on quantitative outcomes. Incorporating a qualitative approach could be valuable since it might minimize the effects of maturation as higher absolute outcomes do not necessarily result in a better score on the test. Moreover, a better movement quality might reduce the likelihood of developing injuries which, in turn, increases the number of training hours the athlete can make, facilitating the realization of an athlete's full-potential.⁵⁸ Hence, future studies should focus on clarifying whether assessing manipulative skills and capturing the quality of movement could be valuable in identifying athletic talent complementary to assessing locomotor skills and using a quantitative approach.

Several strengths of this systematic review could be reported. To start, this systematic review is the first to give insight into the role of general motor skills in the talent identification pathway by including studies incorporating multiple general motor skill test batteries which are commonly used in practice. Secondly, only studies of moderate or high quality were included which ensures the quality of the results. This underscores the importance of coaches, clubs, and researchers tailoring their talent identification programs based on high-quality research. Furthermore, the quality of the included studies was assessed using the QuADS enabling comparisons across study designs using the same criteria. Lastly, the broad variety of study designs and samples underscores the extensive applicability of the included general motor skill test batteries in talent identification programs. This allows for the generalizability of the results. This systematic review is not without limitations. Firstly, more than half of the included studies were of cross-sectional design and identified athletes who outperform their peers on general motor skills prior to reaching the age of peak performance in that sport.²⁰ Hence, these studies lack in providing an insight into future success while talent identification programs are designed to identify athletes capable of reaching podium placements in the future.³ Therefore, it is highly recommended that future studies incorporate a longitudinal study design. Secondly, the definition of performance level varied within the included studies. Ideally, the level of expertise of the athletes of the studies included in this systematic review were classified according to objective guidelines such as those developed by Swann et al.⁵⁹ Unfortunately, these guidelines do not apply to define the performance level of children and adolescents. Hence, future research could focus on performing such an evaluation of the current literature regarding the definition of performance level in children and adolescents in order to propose unequivocal classifications of performance level. These classifications could benefit from taking into account the difference between the age of testing and the age of peak performance in the sport. Thirdly, many of the included studies did not provide information on the background of the study population (e.g., biological age, training history, training volume) or did not adjust for these variables in the statistical analyses. It is recommended that future studies gather and conduct analyses using this information in order to facilitate interpretation and comparison of the results within and between studies. Lastly, to our knowledge no extensive validation studies are available on the QuADS tool to allow for the interpretation of the level of evidence of studies assessed using this tool. However, guidelines were established in the current study based on the studies of van der Fels et al.²⁵ and de Croon et al.²⁶ These guidelines have not yet been validated. Future research is recommended to develop validated guidelines to determine the level of evidence of studies assessed using the QuADS tool.

Conclusion

This systematic review is the first to give insight into the role of general motor skills in the talent identification pathway by including studies incorporating different general motor skill test batteries. The results showed that the majority of studies found either differences in general motor skills in favour of the talented athletes or no differences between talented athletes and their peers. Therefore, assessing general motor skills could contribute to talent identification programs by distinguishing higher from lower performing athletes in childhood and adolescence as well as identifying those with the potential to reach a higher performance level in the future. However, caution should be paid prior to the implementation of these general motor skill test batteries in talent identification programs due to the inconclusive nature of the findings. Hence, there is a need for future high-quality studies in order to provide professionals in the field with clear guidelines about the practical use of general motor skill test batteries in talent identification programs. It is recommended that these studies incorporate a longitudinal study design, conduct sex- and age-specific analyses, address the existing gap in the literature by including athletes from diverse sports beyond football, and investigate whether assessing manipulative skills and capturing movement quality could be a valuable addition to assessing locomotor skills in order to identify athletic talent.

Supplemental Material

sj-docx-1-spo-10.1177_17479541241287176 - Supplemental material for The role of general motor skills in talent identification: A systematic review

Supplemental material, sj-docx-1-spo-10.1177_17479541241287176 for The role of general motor skills in talent identification: A systematic review by Froukje Sliedrecht, Suzan Schoof and Esther Hartman in International Journal of Sports Science & Coaching

Supplemental Material

sj-docx-2-spo-10.1177_17479541241287176 - Supplemental material for The role of general motor skills in talent identification: A systematic review

Supplemental material, sj-docx-2-spo-10.1177_17479541241287176 for The role of general motor skills in talent identification: A systematic review by Froukje Sliedrecht, Suzan Schoof and Esther Hartman in International Journal of Sports Science & Coaching

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Froukje Sliedrecht

Suzan Schoof

Supplemental material

Supplemental material for this article is available online.

Notes

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