Abstract
the form of sprinting is one of the most important abilities that can significantly define performance success in many sports. From the perspective of genetically inherited motor functions, running speed can be classified as a primary phylogenetic human movement, manifested in the form of a “three- segment model” consisting of speed, power, and coordination. By comprehensively analyzing the general and partial predictive contributions of dynamic-kinematic parameters of running, speed-power abilities, and morphological characteristics, on a sample of 80 boys aged 10-12 years, it can be concluded that regardless of the choice of criteria, achieved maximal speeds (KVMAX) or results in children’s athletic sprint over 50 meters (KT50m), the same or related predictor variables contributed to the explanation. The variable running time for 20m from a flying start (KTLS20m) has the greatest predictive contribution (β=0.83, p<0.001) to explaining both criteria, which may indicate the importance of conducting this test in the identification and selection for athletic sprint. Additionally, the selection of tests to assess speed-power abilities is extremely important for the identification and selection for athletic sprint. It can be concluded that tests of horizontal and vertical jumps are significant for identification, as well as tests for assessing neuro-muscular excitation. Tests for assessing continuous horizontal jump are also important, although there is an impression that, in boys aged 10-12 years, coordinatively simpler tests should be used. In the analysis of morphological characteristics, variables that significantly contributed to the explanation of criteria at a partial level were body height, back skinfold, and ankle diameter, indicating that in the identification of talented individuals, it should be considered that elite sprinters are characterized by light bones, optimal muscle mass, and low levels of subcutaneous
simpler tests should be used. In the analysis of morphological characteristics, variables that significantly contributed to the explanation of criteria at a partial level were body height, back skinfold, and ankle diameter, indicating that in the identification of talented individuals, it should be considered that elite sprinters are characterized by light bones, optimal muscle mass, and low levels of subcutaneous fat tissue. Keywords: athletics, talent ID, speed, power, maximal velocity Correspondence: N. Covic Faculty of Sport and Physical Education, University of Sarajevo, Sarajevo, Bosnia and Herzegovina E-mail: nedim.covic@fasto.unsa.ba ORIGINAL SCIENTIFIC PAPER
4 J. Anthr. Sport Phys. Educ. 8 (2024) 3ACCESS TO TEST SELECTION IN CHILDREN’S ATHLETICS | S. LIKIC ET AL. Introduction Athletics is a complex multidisciplinary sport. The foun- dation of athletics, as well as various athletic disciplines, con- sists of fundamental locomotor movements, namely walking, running, jumping, and throwing. Besides walking, running represents the most natural form of human locomotion. De - spite the simplicity of the elementary form of running, the technical structure of athletic sprinting is extremely complex. The investigation of running speed and its impact on athletic performance represents a multifaceted and dynamic research area. Scholars have explored various dimensions of running speed, encompassing its biomechanical underpinnings, phys - iological determinants, and training methodologies. From a biomechanical standpoint, running speed is influenced by factors such as stride length, stride frequency, ground contact time, and flight time (Weyand et al., 2000). Athletes often aim to optimize these biomechanical variables to achieve maximal speed while minimizing energy expenditure and the risk of in - jury. Physiologically, running speed is intricately linked to the cardiovascular and musculoskeletal systems’ ability to deliver oxygen and nutrients to working muscles and remove meta - bolic byproducts (Joyner & Coyle, 2008). Interventions target- ing these physiological systems can result in enhancements in running speed and endurance. Regarding training practices, athletes employ a variety of techniques to improve their run - ning speed, including sprint-specific drills, resistance train- ing, plyometrics, and interval training (McMahon & Wenger, 1998). These training modalities are designed to enhance mus - cle strength, power, coordination, and neuromuscular efficien- cy, all of which are critical for sprint performance. Further- more, the study of running speed transcends individual per- formance to encompass external factors such as environmental conditions, footwear selection, and track surfaces, all of which can influence an athlete’s speed (Hausswirth et al., 2014). Re - searchers are actively exploring novel training methodologies and technological advancements, such as wearable sensors and biomechanical modelling, to deepen our comprehension of running speed and enhance athletic performance. Additionally, maximal running speed can depend on vari - ous factors related to morphological and physiological
track surfaces, all of which can influence an athlete’s speed (Hausswirth et al., 2014). Re - searchers are actively exploring novel training methodologies and technological advancements, such as wearable sensors and biomechanical modelling, to deepen our comprehension of running speed and enhance athletic performance. Additionally, maximal running speed can depend on vari - ous factors related to morphological and physiological charac- teristics, energy mechanisms, age, genetic inheritance, motor abilities, intermuscular and intramuscular coordination, as well as optimal biomechanical movement technique. Running speed is one of the motor abilities that is very difficult to devel - op. Furthermore, locomotor speed in the form of sprinting is one of the most important abilities that can significantly define performance success in many other sports. From the perspec - tive of genetically inherited motor functions, running speed can be classified as a primary phylogenetic human movement and is manifested in a “three-segment model,” consisting of speed, power, and coordination (Babić, V., & Dizdar, D., 2010; Čoh, Bračić, & Smajlović, 2009; Kampmiller, T., M. Vanderka, P. Šelinger, M. Šelingerová, D. Čierna, 2011). One study (Čović et al., 2015) explained the running structure in boys similar age explaining the similarity in race phases between boys and elite sprinters. Since the purpose of this scientific study is to select tests that are accessible for talent identification in chil - dren’s athletics, it is necessary to consider the structure of dy- namic-kinematic parameters of running in lower school age, speed-power abilities in terms of natural forms of horizontal and vertical jumps, as well as the speed of neuro-muscular ex - citation, and morphological characteristics of children in this age group. The aim of the study is to select accessible tests for talent identification in children’s athletics by examining the dynam - ic-kinematic parameters of running, speed-power abilities through natural forms of horizontal and vertical jumps, the speed of neuro-muscular excitation, and morphological char - acteristics in lower school-aged children. Methods Participants The research was conducted on a sample of 80 respon - dents, boys aged 10-12, who were selected from the population of pupils of the fourth grade
the dynam - ic-kinematic parameters of running, speed-power abilities through natural forms of horizontal and vertical jumps, the speed of neuro-muscular excitation, and morphological char - acteristics in lower school-aged children. Methods Participants The research was conducted on a sample of 80 respon - dents, boys aged 10-12, who were selected from the population of pupils of the fourth grade of elementary school (Sarajevo, Bosnia and Herzegovina). Subjects were advised to wear sport equipment and non-slippery shoes suitable for sports activi - ties. Legal guardians were asked to sign a written contest de- claring allowance to participate in research and confirming ab- sence of injuries and medical condition that may compromise health. Participants were allowed to forfeit at any time during the testing procedure. All procedures were conducted accord - ing to Helsinki declaration with permission of local Ethical Committee. Procedures Testing was performed in the morning hours indoors on artificial surface suitable for athletic competitions. Overall, 12 experienced sport scientists were included in the testing pro - cedure. Body mass and stature were measured using a scale with a stadiometer (Seca, Hamburg, Germany) to the nearest 0.1 kg and 0.1 cm, respectively. Body mass index was calcu - lated as body mass (kg)/squared stature (m2). Body measures were measured by a level 3 anthropometrist following the pro - cedures established by the ISAK featuring variables: longitudi- nal dimensionality of the skeleton – Body height (ALVT), Leg length (ALDN), Foot length (ALDST); transversal dimension - ality of the skeleton – Width of the pelvis (ATŠZ), Diameter of the ankle (ATDSZ), Diameter of the knee (ATDKZ); volume and mass of the body – Scope of the upper leg (AVONAT), Scope of the lower leg (AVOPOT), body mass (AVMT). Running dynamic and kinematic parameters were esti - mated using 50 meters running test. Running area from 20 to 40 meters was merged with Microgate (Bolzano, Italy) surface sensors while photocells were placed after each 5 meters from start to finish. Subjects were running from standing start 3 m from starting line (flaying start) to avoid any possible mis - takes. Subjects started
kinematic parameters were esti - mated using 50 meters running test. Running area from 20 to 40 meters was merged with Microgate (Bolzano, Italy) surface sensors while photocells were placed after each 5 meters from start to finish. Subjects were running from standing start 3 m from starting line (flaying start) to avoid any possible mis - takes. Subjects started running on their own signal. Sample of variables for estimating running dynamic and kinematic pa - rameters included a set of seven variables: maximum running speed (KVMAX (m/s)), 50m running time (KT50m (s)), 20m running time from flying start (KTLS20m (s)), stride frequen - cy (KFK (Hz)), stride length (KDK (cm)), duration of contact (KTK (ms)) and duration of the flight (KTL (ms)). By selecting one of the two criteria variables (KVMAX or KT50m), the un - selected variable was automatically placed in the role of pre- dictor. Kinematic parameters were registered on tensiometric car - pet (Ergo Tester Bosco), while sample of variables estimating speed-strength motor abilities included a set of 12 variables: Standing long jump (MSDM (cm)), Vertical jump – Abalak test (MABL (cm)), Counter movement jump (MCMJ (cm)), Counter movement jump with free hands (MCMJH (cm)), Repetitive jumps over the right foot on the 20m - stride num - ber (MSD20B), Repetitive jumps over the left foot on the 20m - stride number (MSL20B), Repetitive jumps over the right foot on the 20m – time (MSL20V), Repetitive jumps over the left foot on the 20m – time (MSL20B), Hand tapping on 15 seconds (MTAPR), Leg tapping on 15 seconds (MTAPN), Medicine-ball throw backwards (weight 1 kg) from standing
ACCESS TO TEST SELECTION IN CHILDREN’S ATHLETICS | S. LIKIC ET AL. J. Anthr. Sport Phys. Educ. 8 (2024) 3 5 position over head (MSMEDS), Medicine-ball throw forward (weight 1kg) from lying on back over head (MSMEDL). Statistical analysis For all the data, measures of central tendency and disper - sion (mean ± SD) were calculated, and the normality of dis- tribution was checked using the Kolmogorov-Smirnov test. The predictive general and partial contributions of variables from different anthropological areas to the achieved maximum running speed in boys aged 10-12 years were estimated using multiple regression analysis - Stepwise method, which is based on a successive procedure of variable introduction into the dis - criminant equation according to the criterion F ≤ 1.00. This procedure introduces or discards a variable from the discrimi - nant function if another variable more satisfactorily meets the entry criterion. The analysis was conducted using the SPSS software package (v 21.0) (IBM, Chicago), with statistical sig - nificance set at the conventional 95% level (p > 0.05). Results The predictive values of general and partial contributions of treated sets of variables of dynamic and kinematic run - ning parameters, speed-strength abilities, and morphological characteristics (table 1) in explaining the criteria of achieving maximum running speed (KVMAX) and results in children’s athletic sprinting over 50 meters (KT50m) were determined. Based on the obtained coefficients of determination (R²), which reflected the general predictive contribution of three predictor sets of variables in relation to the criterion variables KVMAX and KT50m, the research results indicated the fol - lowing: the complete set of predictor variables of kinematic running parameters explained 91% of the shared variance of the criterion of achieved maximum running speed - KVMAX (Table 2), and 96% of the shared variance of the criterion vari - able of 50m sprint running results - KT50m (Table 3); the complete set of predictor variables of speed-strength abilities explained 68% of the shared variance of the criterion variable KVMAX (Table 4), and 69% of the shared variance of the cri - terion variable KT50m (Table 5); also, based on the
of the shared variance of the criterion vari - able of 50m sprint running results - KT50m (Table 3); the complete set of predictor variables of speed-strength abilities explained 68% of the shared variance of the criterion variable KVMAX (Table 4), and 69% of the shared variance of the cri - terion variable KT50m (Table 5); also, based on the obtained results, it was determined that the complete set of morpholog - ical characteristics variables explained 21% of the shared vari- ance of the criterion variable KVMAX (Table 6), and 27% of Tabel 1. Morphology, running dynamic and kinematic and speed-strength features in young school age (n=80) male participants. Morphology (n=80) Mean±SD Body height (ALVT) (cm) 145.3±6.6 Body mass (AVMT) (kg) 39.73±8.88 Leg length (ALDN) (cm) 83.04±5.02 Foot length (ALDST) (cm) 22.89±1.32 Width of the pelvis (ATŠZ) (cm) 20.8±2.68 Diameter of the ankle (ATDSZ) (cm) 6.54±0.435 Diameter of the knee (ATDKZ) (cm) 9.04±0.846 Scope of the upper leg (AVONAT) (cm) 45.22±6.18 Scope of the lower leg (AVOPOT) (cm) 30.79±3.34 Running dynamic and kinematic parameters (n=80) 50m running time (KT50m) (s) 9.91±0.67 Maximum running speed (KVMAX) (m/s) 6.02±0.433 20m running time from flying start (KTLS20m) (s) 3.48±0.261 Stride frequency (KFK) (Hz) 3.96±0.255 Stride length (KDK) (cm) 145.51±10.72 Duration of contact (KTK) (ms) 0.15±0.015 Duration of the flight (KTL) (ms) 0.1±0.012 Dynamic parameters of speed-strength motor abilities (n=80) Standing long jump (MSDM) (cm) 145.54±19.09 Vertical jump – Abalak test (MABL) (cm) 27.13±5.01 Counter movement jump (MCMJ) (cm) 19.87±4.28 Counter movement free arms (MCMJH) (cm) 23.72±4.62 Repetitive jumps over the right foot on the 20m (MSD20V) (s) 12.24±3.12 Repetitive jumps over the right foot on the 20m (MSD20B) (n) 28.52±6.72 Repetitive jumps over the left foot on the 20m (MSL20V) (s) 12.37±2.83 Repetitive jumps over the left foot on the 20m (MSL20B) (n) 28.58±6.42 Leg tapping on 15” (MTAPN) (n) 18.54±1.91 Hand tapping on 15” (MTAPR) (n) 25.77±2.74 Backwards overhead medicine-ball throw (1 kg) from standing position (MSMEDS) (m)4.95±0.965 Forward overhead medicine-ball throw (1kg) from lying on back (MSMEDL) (m) 6.95±1.34
jumps over the left foot on the 20m (MSL20B) (n) 28.58±6.42 Leg tapping on 15” (MTAPN) (n) 18.54±1.91 Hand tapping on 15” (MTAPR) (n) 25.77±2.74 Backwards overhead medicine-ball throw (1 kg) from standing position (MSMEDS) (m)4.95±0.965 Forward overhead medicine-ball throw (1kg) from lying on back (MSMEDL) (m) 6.95±1.34
6 J. Anthr. Sport Phys. Educ. 8 (2024) 3ACCESS TO TEST SELECTION IN CHILDREN’S ATHLETICS | S. LIKIC ET AL. Table 3. Predictive contribution of dynamic-kinematic parameters to 50 meters time (KT50) Model summary for criterion variable KT50 R= 0.979, R 2 = 0.96, SE= 0.136, F (2,78) = 918.93, P<0.001 Variables in the Equation Variable B SE of B Beta T P KTLS20m 2.105 .189 .826 11.129 <.001 KT50m -.244 .114 -.158 -2.139 .035 Variables not in the Equation Variable Beta In Partial Min. T P KFK .005 .022 .094 .199 .842 KDK -.009 -.038 .090 -.338 .736 KTK -.015 -.075 .094 -.662 .509 KTL -.0172 -.082 .092 -.722 .472 SE – Standard Error; P statistical significance; DF – degrees of freedom; SS – sum of squares; MS – Mean square Table 4. Predictive contribution of power-speed parameters to maximum running speed (KVMAX) Model summary for criterion variable KVMAX R= 0.824, R 2 = 0.68, SE= 0.251, F (4,76) = 40.361, P<0.001 Variables in the Equation Variable B SE of B Beta T P MSD20B -.025 .005 -.394 -4.506 <.001 MABL .023 .007 .270 3.116 .002 MTAPR .034 .010 .215 3.209 .002 MSDM .004 .001 .207 2.375 .020 Variables not in the Equation Variable Beta In Partial Min. T P MCMJ .086 .108 .441 .945 .347 MCMJH -.004 -.005 .430 -.048 .962 MSD20V -.142 -.141 .248 -1.241 .218 MSL20V -.142 -.168 .428 -1.482 .142 MSL20B -.069 -.074 .363 -.643 .522 MTAPN .035 .046 .505 .402 .688 MSMEDL .103 .166 .543 1.466 .146 MSMEDS .092 .145 .536 1.270 .208 SE – Standard Error; P statistical significance; DF – degrees of freedom; SS – sum of squares; MS – Mean square Table 2. Predictive contribution of dynamic-kinematic parameters to maximum running speed (KVMAX) Model summary for criterion variable KVMAX R= 0.954, R 2 = 0.91, SE= 0.131, F (2,78) = 397.78, P<0.001 Variables in the Equation Variable B SE of B Beta T P KTLS20m -1.010 .269 -.610 -3.746 <.001 KT50m -.226 .105 -.348 -2.139 .035 Variables not in the Equation Variable Beta In Partial Min. T P KFK .023 .071
speed (KVMAX) Model summary for criterion variable KVMAX R= 0.954, R 2 = 0.91, SE= 0.131, F (2,78) = 397.78, P<0.001 Variables in the Equation Variable B SE of B Beta T P KTLS20m -1.010 .269 -.610 -3.746 <.001 KT50m -.226 .105 -.348 -2.139 .035 Variables not in the Equation Variable Beta In Partial Min. T P KFK .023 .071 .042 .631 .529 KDK 4.515 .001 .042 .011 .991 KTK -.003 -.011 .042 -.103 .918 KTL -.030 -.097 .042 -.863 .391 SE – Standard Error; P statistical significance; DF – degrees of freedom; SS – sum of squares; MS – Mean square
ACCESS TO TEST SELECTION IN CHILDREN’S ATHLETICS | S. LIKIC ET AL. J. Anthr. Sport Phys. Educ. 8 (2024) 3 7 Table 5. Predictive contribution of power-speed parameters to 50 meters time (KT50) Model summary for criterion variable KT50 R= 0.832, R 2 = 0.69, SE= 0.378, F (4,76) = 42.853, P<0.001 Variables in the Equation Variable B SE of B Beta T P MSD20B .034 .009 .344 3.597 <.001 MABL -.040 .010 -.308 -3.795 <.001 MSL20V .060 .021 .255 2.826 .006 MTAPR -.040 .015 -.165 -2.526 .013 Variables not in the Equation Variable Beta In Partial Min. T P MSDM -.137 -.175 .428 -1.544 .126 MCMJ -.168 -.214 .436 -1.902 .061 MCMJH -.149 -.180 .422 -1.587 .116 MSD20V .116 .118 .225 1.032 .305 MSL20B .071 .059 .210 .515 .608 MTAPN -.101 -.143 .408 -1.255 .213 MSMEDL -.092 -.149 .424 -1.308 .195 MSMEDS .092 .145 .536 1.270 .208 SE – Standard Error; P statistical significance; DF – degrees of freedom; SS – sum of squares; MS – Mean square Table 6. Predictive contribution of morphological characteristics to maximum running speed (KVMAX) Model summary for criterion variable KVMAX R= 0.459, R2= 0.21, SE= 0.389, F(2,78) = 10.417, P<0.001 Variables in the Equation Variable B SE of B Beta T P ANL -.002 6.022 -.422 -4.07 <.001 ALVT .020 .006 .311 3.005 .003 Variables not in the Equation Variable Beta In Partial Min. T P ALDN .029 .018 .308 .161 .872 ALDST -.054 -.034 .313 -.299 .765 ATŠZ .066 .060 .647 .532 .596 ATDSZ .181 .144 .498 1.282 .203 ATDKZ -.088 -.071 .518 -.631 .529 AVONAT .262 .170 .334 1.522 .132 AVOPOT .171 .105 .298 .933 .353 AVMT .172 .073 .143 .647 .519 ANS .338 .130 .117 1.159 .250 ANPOT -.101 -.072 .399 -.638 .525 SE – Standard Error; P statistical significance; DF – degrees of freedom; SS – sum of squares; MS – Mean square Table 7. Predictive contribution of morphological characteristics to 50 meters time (KT50) Model summary for criterion variable KT50 R= 0.525, R 2 = 0.28, SE= 0.573, F (2,78) = 14.897, P<0.001 Variables in the Equation Variable