This study aimed to determine the relative contribution of selected biomechanical, energetic, coordinative, and muscular factors for the 200 m front crawl and each of its four laps. Ten swimmers performed a 200 m front crawl swim, as well as 50, 100, and 150 m at the 200 m pace. Biomechanical, energetic, coordinative, and muscular factors were assessed during the 200 m swim. Multiple linear regression analysis was used to identify the weight of the factors to the performance. For each lap, the contributions to the 200 m performance were 17.6, 21.1, 18.4, and 7.6% for stroke length, 16.1, 18.7, 32.1, and 3.2% for stroke rate, 11.2, 13.2, 6.8, and 5.7% for intracycle velocity variation in
The goal of competitive swimming is to perform the race distance as fast as possible, for that swimmers must achieve their highest average velocity for that distance. Swimming velocity (
As described above, theoretical models have been developed that attempt to explain the influence of various factors on performance. In spite of the fact that velocity is common to the theoretical approaches, they cannot be combined due to incompatibility of terms and units. This has led to attempts at practical approaches, relating swimming performance to different anthropometrical, physiological, and biomechanical parameters [
Ten welltrained swimmers (
All tests were conducted in a 25 m indoor pool and each subject swam alone in the middle lane, avoiding pacing or drafting effects. Following a warmup that consisted of a selfselected swim of about 1000 m, including some swimming with the snorkel, swimmers performed a 200 m maximum effort front crawl swim after a push start and using open turns without a glide. They were instructed to replicate their pacing and strategy used in competition. After 90 min of active rest, swimmers performed a 50 m front crawl test and twentyfour hours later a 150 m and a 100 m tests, with 90 min active rest interval between them. Together 50, 100, and 150 m tests were at the same swimming speed as in the previous 200 m paced by a visual light pacing system placed in the bottom of the pool. The pacing lights led the swimmers as the lights progressed down the pool with a flash every 5 m (TAR 1.1, GBKElectronics, Aveiro, Portugal).
Each swimmer’s performance was recorded with a total of six stationary and synchronized video cameras (Sony, DCRHC42E, Tokyo, Japan), four below and two above the water. The calibration setup, accuracy, and reliability procedures have been previously described in detail [
One complete stroke cycle (defined as the period between the instant of entry of one hand to the next instant of entry of the same hand) for each of the 50 m laps of the 200 m front crawl was analyzed. From these data, the center of mass position as a function of time was computed. The mean velocity (
To determine and analyze the whole body centre of mass’ IVV in the
Propelling efficiency
Oxygen uptake (
Since the 200 m front crawl energy contribution is supplied from the three energy sources [
The calculation of the index of coordination (IdC) requires the identification of key points in the stroke cycle [
The IdC was calculated as the time gap between the propulsion (pull and push phases) of the two arms and expressed as a percentage of the duration of the complete armstroke cycle (sum of the propulsive and nonpropulsive phases (catch and exit phases)) [
The EMG signals of eight muscles (flexor carpi radialis, biceps brachii, triceps brachii, pectoralis major, upper trapezius, rectus femoris, biceps femoris, and tibialis anterior), which have been shown to have high activity during front crawl swimming [
Raw EMG signals were bandpassed (8–500 Hz), rectified to obtain the full wave signals, and smoothed with a 4th order Butterworth filter (10 Hz) for the linear envelope. The integration of the rectified EMG was calculated, per unit of time, to eliminate the stoke cycle duration effect (iEMG/T) and normalized to the maximum iEMG observed (signal was partitioned in 40 ms windows to identify the maximal iEMG) [
For the frequency analysis (Freq), spectral indices were calculated [
Mean (SD) computations for descriptive analysis were obtained for all variables (normal Gaussian distribution of the data was verified by the ShapiroWilk’s test). A oneway repeated measures ANOVA was used to compare each factor along the 200 m. When a significant
As described in the Introduction, absence of a theoretical model to combine the factors that contribute to swimming performance, a multiple linear regression was used to identify the relative contributions of factors that are associated with swimming performance. These, among the previous defined, factors are biomechanical (SL, SR,
Mean velocity for the total 200 m front crawl was 1.41 (±0.04) m·s^{−1}. Figure
Mean (SE) values expressed as a percentage of the mean value for the 200 m front crawl for velocity (
Figure
Mean (±SE) values for the percentage of the 200 m front crawl mean value for the (i) biomechanical factors: IVV for
The beta coefficients for all factors are presented in Table
The beta coefficients (
SL  SR  IVV 
IVV 


IdC  iEMG  Freq  Constant  

200 m performance  Lap 1  −1.10 
−0.04 
4.04  −1.40 
11.55 
0.01 
0.05 
−0.32 
0.01 
0.89 
Lap 2  5.90 
0.26 
−14.15  −3.52 
−28.08 
0.04 
−0.08 
−0.64 
−0.04 
−2.12 

Lap 3  0.20  0.02  0.25  −0.02  −0.16  0.002  −0.006  0.03  0.001  0.05  
Lap 4  −0.13  −0.002  0.21  0.12  −0.97  0.005  −0.02  −0.04  0.002  1.04  
 
Each 50 m performance  Lap 1  −6.52  −0.25  19.87  −8.02  62.06  0.03  0.26  −1.44  0.02  4.29 
Lap 2  1.32  0.07  −1.65  −0.52  −2.72  0.004  −0.01  −0.08  −0.01  −1.75  
Lap 3  0.63  0.05  0.35  −0.18  −0.49  −0.002  −0.01  0.05  −0.001  −1.59  
Lap 4  0.50  0.03  −0.15  −0.03  −0.12  0.001  −0.004  −0.01  −0.0001  −0.92 
The biomechanical factors showed a great importance, manly the SL and SR (Figure
The percentage of the contributions of each factor in each lap for the 200 m swim performance (a) and mean percentages for all laps (b).
In Figure
The relative contributions of the factors for the 50 m laps performances (a) and mean percentages for all laps (b) of the 200 m front crawl.
Although previous studies have evaluated the role of biomechanical [
Stability in the IVV (
The assessed muscular factors revealed in spite of swimming at maximum effort that the observed muscles were involved at a submaximum level, as amplitude increased and frequency decreased (i.e., increase in the spectral indices), as previously reported for amplitude [
As velocity and the SLSR ratio changed, interarm coordination adapted, with an increase in IdC in the final stages of the 200 m event. This observation is consistent with the development of fatigue as reported previously [
A theoretical framework for the interaction of the biomechanical, energetic, coordinative, and muscular factors is presented in Figure
The relationship between biomechanical, energetic, coordinative, and muscular factors to performance in competitive swimming.
The biomechanical factors had the highest contribution to the 200 m front crawl and also to each 50 m lap mean velocities, where together they accounted for up to 33.7% and 61.0%, respectively. These contributions are understandable, as the product of two of these factors (SL and SR) determines swimming velocity [
Changes in SL and SR are associated with
As the biomechanical factors show a decreased contribution to the variance of the 200 m in each 50 m swim performance between the first and the last laps, other factor’s contributions must increase (see Figure
The reduction in
The increased
The increase in
In the first lap, the contribution of the SL is higher than the SR, but in the last lap SR is greater suggesting fatigue in the last lap, which is supported by the EMG data (see Figure
In spite of these associations described above, the relationship between iEMG and force is not linear and the diagnostic value of the time domain analysis (iEMG) in muscle fatigue evaluation is considered to be more limited than that of the frequency domain analysis (Freq) [
For the mean velocity in each lap, both iEMG and Freq present a similar mean contribution; however their pattern of change over the laps is different. The iEMG has its highest contribution on the first lap, whereas Freq has a small contribution. However, Freq is higher, and iEMG lower, in the last lap. This can suggest that at the beginning of the effort higher muscular activation is needed to recruit more fasttwitch muscle fibers and achieve the higher SR at this stage. In the second lapes, the contribution of Freq surpasses that of iEMG, and after this, it decreases constantly until the end of the 200 m effort. The decreased contribution of iEMG is contrary to the increase in absolute values relative to the mean value for 200 m. This pattern of changes is similar to the decrease in spectral parameters that indicate the evolvement of fatigue. As higher
Notwithstanding the results and discussion, as well as the combined interactive effects of performance influencing factors on several research fields in welltrained swimmers, the approach used has some limitations that have to be acknowledged. The regression analysis was not intended to predict performance, only to determine the contribution of the factors, and the variables used represent discrete and extremely important outcomes, each of them for the understanding of the swimming performance and aquatic human locomotion. The relation between the number of variables and subjects evaluated was poor, which may influence the results of the analysis performed, over or underestimating the contribution of the factors.
The swimmers in this study had the highest velocity in the first lap of the 200 m swim. The factors contributing to this were a balance of SL, SR,
This investigation was supported by Grants of the Portuguese Science and Technology Foundation (SFRH/BD/38462/2007) (PTDC/DES/101224/2008—FCOMP010124FEDER009577).