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The standing long jump (SLJ) is an easy way to assess lower-body power [1] and findings suggest that SLJ performance might also be related to measures of total body strength [2].
Performance in SLJ is assessed by measuring the shortest distance between a bipedal take-off point of the toes and the landing point of the heel to the nearest centimeter; usually, the best result of three attempts is included in the overall assessment [3].
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There are numerous studies on the kinematics and biomechanics of the SLJ that split the distance achieved in the SLJ (Djump) into three parts: the horizontal distance between the take-off point and the position of the center of gravity (Dtake-off), the horizontal distance between the landing point and the position of the center of gravity (Dlanding), and the flight distance, the distance between these two points (Dflight) ([4, 5]; see Fig. 1).
Fig. 1
Graphical visualization (biomechanics) of the jumping distances in the standing long jump (own illustration based on Wakai and Linthorne [4])
×
Figure 1 shows that two of these flight distances (Dtake-off and Dlanding) are directly related to the body height of the jumper (HB) and the take-off angle (α), as well as the landing angle (β). In contrast, the flight distance (Dflight) is affected by the factors take-off speed (v), take-off angle (θ), gravity (g), and the vertical height difference (hCOM) between the position of the body’s center of mass (COM) at the time of take-off and landing. Furthermore, the take-off speed (v) is determined by the body weight (m), the force of gravity (g), the take-off angle (θ), the ground reaction force (FG), and the damping factor of the jump (l). All these factors, except for body height, can be optimized by physical and technical-tactical training [4].
Model Calculation
In a model calculation based on algorithms by Wakai and Linthorne [4], a ceteris paribus analysis is performed. All factors that can be optimized by physical training (v, m, FG) and technical-tactical training (α, θ, β, hCOM), as well as gravity (g), are assumed to be constant and only different body height (HB) is taken into account as a variable. In addition, it is assumed that the COM is constant and located at 60% of hB.
However, it must be mentioned that a larger HB is mostly associated with a relatively larger body weight, thus reducing the Dflight for the same v. Furthermore, the increased body weight can be due to a larger muscle mass as well as bone or fat mass. Higher muscle mass could increase v, thereby achieving the same Dflight; in the other case, the opposite could result in a decrease in v and the associated Dflight.
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According to our model calculation, we assume identical fixed parameters except for HB, which remains the only variable.
The fixed parameters are: α = 54°, COM = 60%HB, v = 3.0 m/s, g = 9.81 m/s2, hflight = 0.200 m, θ = 40°, β = 60°.
A German study has shown that the height of children of the same age in primary school can vary by an average of about 20 cm, whereas in secondary school and high school the range in height can be more than 30 cm [6].
These results are remarkable in the context of our model calculation: with a body height difference of 20 cm, the jump distance changes by 12.7 cm, whereas with a height difference of 30 cm it changes by 19.0 cm (Table 1).
Table 1
Model calculation—Effects of body height on athletic performance in the standing long jump
Variable
HB [m]
Dtake-off [m]
Dtake-off [m]
Hlanding [m]
Dlanding [m]
Dflight [m]
Djump [m]
Dtake-off [m/(m*hB)]
Djump [m/(m*hB)]
A
1.200
0.423
0.582
0.382
0.221
1.099
1.743
0.353
1.453
B
1.250
0.441
0.607
0.407
0.235
1.775
1.420
C
1.300
0.458
0.631
0.431
0.249
1.806
1.389
D
1.350
0.476
0.655
0.455
0.263
1.838
1.361
E
1.400
0.494
0.680
0.480
0.277
1.870
1.335
F
1.450
0.511
0.704
0.504
0.291
1.901
1.311
G
1.500
0.529
0.728
0.528
0.305
1.933
1.289
H
1.550
0.547
0.752
0.552
0.319
1.965
1.267
I
1.600
0.564
0.777
0.577
0.333
1.996
1.248
Model variant 1
1.627
0.574
0.790
0.590
0.340
2.013
1.237
J
1.650
0.582
0.801
0.601
0.347
2.028
1.229
K
1.700
0.600
0.825
0.625
0.361
2.059
1.211
L
1.750
0.617
0.849
0.649
0.375
2.091
1.195
M
1.800
0.635
0.874
0.674
0.389
2.123
1.179
N
1.850
0.652
0.898
0.698
0.403
2.154
1.165
Model variant 2
1.897
0.669
0.921
0.721
0.416
2.184
1.151
O
1.900
0.670
0.922
0.722
0.417
2.186
1.151
P
1.950
0.688
0.947
0.747
0.431
2.218
1.137
Numbers in italics do not have 5 cm steps in body height
Using renowned German reference values from the German Motor Test [3], such a body height-related difference in the jump distance can lead to lower performance ratings (by up to two levels in a classification with five levels) when classifying performance.
Taking the example of a 16-year-old boy in Germany being between 1.627 and 1.897 m (see [6]) in body height (HB), and by using our fixed parameters, his jumping distance calculated in our model calculation would be between 2.013 and 2.184 m. For a SLJ distance of 2.013 m, his performance would be classified as average (category 3 of 5 performance categories), whereas an SLJ distance of 2.184 m would be classified as very good (category 1) [3]. Thus, the same physical and technical-tactical performance in the SLJ would be categorized completely differently based simply on body height (HB).
In children and adolescents, the SLJ is used in many different fitness test batteries or talent selections, and therefore, alternative assessment criteria should be developed to improve the aspects of fairness and equal opportunities and to receive more differentiated results.
Assessing the achieved jump distances in our model calculation in relation to body height results in a Dtake-off of 0.353 m/(m*HB) for all body heights, which shows that such an assessment significantly increases fairness and equals the chance of good performance. If Djump is assessed using this method, smaller HB leads to a better performance assessment. In other words, Dflight with the same jump distance and different HB means a better performance with a smaller HB than with a larger HB (Table 1).
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Talent selection and fitness and health monitoring in children’s and youth sports is becoming more and more professionalized. However, new research shows that missing consideration of anthropometric parameters can lead to a kind of misclassification. For example, children with a greater weight and overall lower fitness may achieve better results in medicine ball throwing than children of normal weight [7]. Therefore, consideration of anthropometrics in evaluation and classification seems to be a must in modern fitness and physical health assessment systems.
Declarations
Conflict of interest
G. Jarnig, M.N.M. van Poppel and R. Kerbl declare that they have no competing interests.
For this article no studies with human participants or animals were performed by any of the authors. All studies mentioned were in accordance with the ethical standards indicated in each case.
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