Biomechanics and Medicine in Swimming XI

BiomechanicsandmedicineinswimmingXi
Regression Analysis Model Applied to Age-Group
Swimmers: Study of Stroke Rate, Stroke Length and
Stroke Index
Morales, e., Arellano, r., Femia, P., Mercade, J.
University of Granada, Spain
This investigation aimed to develop a regression model of the Kinematics
Characteristics (KC) evolution in a large sample of regional
age-group Spanish swimmers. Subjects were 280 regional swimmers
selected from different clubs. The 50 m time, Stroke rate (SR), Stroke
length (SL) and Stroke Index (SI) were used for analysis. Inverse function
approximation of the race times by age (AGE) and gender (GEN)
was carried out. Quadratic function approximation of the SL and SI
by aging was carried out. Lineal function by aging was defined for ST.
Furthermore, the analysis regression of KC for age and genders were calculated
respectively. 50 m times were different between genders. There
is a tendency to improve the parameters SL and SI with age in both
genders. SR does not show a clear trend and has an irregular behaviour.
Key words: stroke rate, stroke length, stroke index, regression analysis,
age-group.
IntroductIon
The swimmer´s time obtained after performing a competitive event can
be considered as important information to help the coaching process
that follows the competitive performance. The dynamic process of training
needs as much information as possible from that performance. This
information will help the coach to monitor the training program.
The Race Component (RC) Time to be include in the analysis of
swimming performance during international swimming competition
(Hay,Guimaraes, & Grimston, 1983) and it is very important to now
the follow of race. In order to improve the swimmer´s efficiency stroke
rate, stroke length and stroke index to be include in the analysis of competition.
Technical performance in cyclic activities and, more specifically,
swimming performance (Hay, 2002) has traditionally been assessed
by analysis the changes in and management of velocity, stroke rate and
stroke length (Graig, & Perdergast, 1979; Pai, Hay & Wilson, 1984;
Kenndy, Brown, Chegarlur & Nelson, 1990; Chegarlur & Brown, 1992;
Chollet, Pelayo, Tourny, & Sidney, 1996). Several groups of researchers
have analysed the technical and kinematics characteristics (KC), stroke
rate (SR), stroke lengh (SL) and stroke index (SI), during international
competitions to determine their relationship with performance.
Some studies have been published where regression equations were
applied in the analysis of RC obtained in different competitions (Absaliamov
& Timakovoy, 1090; Arellano, Brown, Cappaert & Nelson,
1996; Nomura, 2006). The study aim was to develop a regression model
of the KC evolution in a large sample of regional age-group Spanish
swimmers.
Method
The subjects were 280 swimmers (162 males and 118 females) regional
swimmers. The age of these subjects ranged from 9 to 22 years.
The procedures that have been used to record the 50 m time and kinematics
characteristics obtained by swimmers during the performance
test of 50 m freestyle were: a) references were put on the swimming pool
at the distances selected (5, 10, 15 and 20 m) to know when the head
crossed this line; b) the 50m trials were recorded by five video cameras
connected to a mini DV video recorder through a video-timer and video
selector; c) the images from the first two video cameras were mixed to
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see the over- and under- water phases of the start in the same frame
(until 5m); d) third and fourth cameras were used to measure the 10
and 15 m time; the fifth camera was placed at the end of the swimming
pool for video recording the turning phase (20 and 25 m) and; e) all the
images from the cameras were recorded at a distance of 8 m from the
perpendicular plane of the swimmer’s displacement (see figure 1).
Figure 1. Picture with the references and video cameras set-up on the
swimming pool.
KC obtained by swimmers during the performance test of 50 m freestyle
was calculated in all lap. The results showed the average of laps. The
number of cycles utilized for to do the calculation was three. The equations
defining SR, SL and SI were as follows:
nº cycles ( c)
SR
cycles time ( s)
SL
= (1)
espace ( m)
nº cicles
= (2)
SI = speed • SL (3)
The regression analysis was developed using the SPSS 17.0 statistical
software (SPSS Inc., Chicago, Ill., USA). The Kolmogorov-Smirnov test
showed the normal distribution of the sample. The regression analysis
was used to discover the tendency and model of the 50 m time and KC.
Inverse function approximation of the race times by age (AGE) and
gender (GEN) was carried out. Also, quadratic function approximation
of the SL, and SI by age and GEN, and lineal function of the SR by
AGE and GEN was carried out.
results
The T-test for independent samples explains the difference between
genders for each KC (Table 1).
Table 1. T-test for independent samples according to gender in SR, SL
and SI.
Var. Means Difference E.T T (gl) P
Fc Mas.
Fem.
Lc Mas.
Fem.
Ic Mas.
Fem
53.018
51.259
1.427
1.530
1.846
2.026
*P