SUMMARY:

The purpose of this study is to identify the solutions that high-level athletes have chosen in the 100m freestyle swimming competition. 40 athletes have been reviewed and evaluated in the specific circumstances of each race. Of these, 16 athletes were considered in the National Championship, the remaining 24 athletes in the International Championship. The speed, the length of the cycle, the frequency of the cycles, and the other swim indexes recorded from the last 50m to 50m. When analyzing the baseline data, we find that there is a great difference in the application of the individual solutions of each athlete. Can be divided into 3 different groups: Special group I is high frequency, group II is the distance of the cycle and large amplitude, group III is the intermediate group of the two groups. The relationship between velocity values, The frequency and length of cycles of the first 50m and 50m are also studied. Not all 40 athletes have the same speed regulation. Conversely, when they have established a relationship between the length and frequency of the particular swim, they will remain intact until the end of the race. Of course, some of the best athletes we study , they have adopted solutions beyond the above standards. This analysis allows us to better understand how to adjust the technical elements of race races by the athletes and their adaptation to the cyclical conventions of this activity – Swimming / freehand / speed / frequency / length of the swim. Conversely, when they have established a relationship between the length and frequency of the particular swim, they will remain intact until the end of the race. Of course, some of the best athletes we study , they have adopted solutions beyond the above standards. This analysis allows us to better understand how to adjust the technical elements of race races by the athletes and their adaptation to the cyclical conventions of this activity – Swimming / freehand / speed / frequency / length of the swim. Conversely, when they have established a relationship between the length and frequency of the particular swim, they will remain intact until the end of the race. Of course, some of the best athletes we study , they have adopted solutions beyond the above standards. This analysis allows us to better understand how to adjust the technical elements of race races by the athletes and their adaptation to the cyclical conventions of this activity – Swimming / freehand / speed / frequency / length of the swim.

In swimming history, free swimming is considered to be the fastest moving swimmer from the early twentieth century. Later on, the development of both the number and the quality of training has improved significantly. The tireless, creative creation of coaches and athletes on the career path are factors that can explain the latest advances in swimming. Today’s workout tests are conducted through energy sources (assessing oxygen consumption, plasma [6,15], psychology (stress tolerance) [13], biomechanics and (the development of endurance, thrust, swimming cycle frequency, length of swimming cycle) [1,7,14,27]. But to test the validity of the solutions that have been applied in the practice and in the competition, it is important to clearly define the conduct of the tests in the high class race. Therefore, there are many groups of researchers who have paid much attention to the choice that athletes have for the establishment of the frequency / length relationship of the swimmer.

In 1970, there was a tendency for this study to be formally conducted, and then American researchers, East German and West German researchers continued to study this issue in earnest. However, up to now, no study has been conducted with a large number of athletes (from 8 to 16 athletes tested) and with long follow-up time for many years as their study. I.

The main purpose of this study is to systematically identify the solutions that national and international high-level athletes have applied in the 100m free races. The uniqueness of this study is the large number of athletes (40 testers tested individually and by gender) as well as the systematic nature of the study (the same event, at the same time in June, meaning 1 to 2 months before the European Championships, or Olympic Games).

Since 1990, all of the international races held at Cannet (one of the world’s best organized races) have been analyzed and evaluated by scientists. Since 1992 the analysis has also been done in all the French championships. These competitions are selected for analysis as they are selective for International competitions of the year. In this study, the 100m freestyle is of particular interest for two reasons: The first reason – a 100m freestyle swim is considered to be the most important swimmer of the swim because it is full of intermediaries. of swimming. Clearly 100m is the ideal distance and free swimming is the fastest swimmer. Second reason – Tactics are very diverse of this type of swimming. To confirm one thing later,

The 100m freestyle pool finals were analyzed in four cases: swimming pool held at Cannet 1990, 1991, 1992 and French championships in 1992.

40 athletes have been monitored and evaluated in a detailed and scientific way. That is the subject matter of our research. Also note: Players known under the “Car” have participated in four races – Car1, Car2, Car3, Car4 show the sequence of the race. We are close to this athlete (European record holder) for handling information and statistics, as he is a very interesting subject.

The race was recorded by four Panasonis S – VHS cameras. All four camcorders have large rotational angles and are located on four sides of the pool and can cover the entire four tracks as much as possible. Each race was repeatedly reviewed to record the different time, space and performance of the eight athletes in each round. During that time, the frequencies at each swimming time were counted from the beginning to the end of the 50m head with a Seiko frequency measurement instrument as well as push motions that were counted from the beginning to the end of the 50m. These data, along with the full time recorded on the electronic timer, were statistically recorded as cyclical, cyclical, cyclical, cyclical, cyclone- [7]

A summary of the detailed calculations after each race will allow us to obtain the key information for each athlete during the race as follows: Average speed – the symbol (V) denoted by ms -1 . Calculation V: Take a 50m gap divided by the official time to 1/100 sec. The speed of the first 50m includes the advantage of time in the start and the time required to turn around until the athlete steps on the timer table. At about 50 m, when the athlete reaches the target just touch the time sheet is. – The average frequency (F) is equal to (cycle.min  -1  ) of 50m. This measure was taken three times within 50m in the uninfected area as well as when athletes rounded off.

– Length (m. Cycle -1 ). The length of each cycle (swimming step) in 50m is calculated as follows: 50m divided by the number of cycles (one cyclical freestyle equals two stroke span). Although this swim length calculation has overestimated the swim length of each cycle. But the analysis by the Oriental scientists [11] suggests that this is an inherent disadvantage of this calculation method, but it does not affect the comparison of different free-swimmers groups.

– Swimming index – Signed in m 2. Cycle -1. Sec -1  was determined by Cotill et al. In 1985 [7] as a product of velocity / length / cycle.

Although the swim index uses the velocity parameter, the velocity itself is affected by the starting point and the spin point, but the index is closely related to the athlete’s performance.

The percentage of the race (%) represents the relationship between the time of each 50m segment and the total time multiplied by 100. Example: 100m swim for 50 seconds. 50m swimhead in 24 seconds equivalent to 48% and 50m later is equivalent to 52%

The mean and standard deviations are calculated on the basis of all data collected and calculated. The analysis of the basic factors allows us to determine the position of the athletes depending on the specific changes of performance. Six variables were recorded: velocities, frequencies, lengths per cycle at 50m head and 50m end. The percentage values ​​of the race calculated from active changes are considered support changes not involved in the establishment of the research axis. Simple regression analysis is applied to analyze the velocity, frequency, length of each cycle and to determine the linear relationship of the variables in the first 50 m and 50 m.

The first analysis : mean values, minimum values, maximum values ​​as well as standard deviations of velocity, frequency, length of cycles and percentage of variable parameters in two sections The 100m freestyle was done with a median velocity of 1.94  ±   0.04 M. S  -1  and a mean time of 51.67 seconds. The average frequency is 51.62  ±   4.57 cycles. minutes  -1 , the average length of each cycle is 2.56 ±  0.20 mx cycle  -1 , the average swimming index is 4.38 ±  0.36 (  M 2.  cycles -1 seconds – 1 )

Table I  (please refer to page 20)

The analysis of the basic elements is not only to describe simply but to get a general overview and optimal for the changes of the athletes. The analysis of the basic factors allows us to draw three main axes with the corresponding proportions as follows: Axis I is 61.3%, Axis II is 25.6%, Axis III is 8.4%. They merged into 95.3% of total information. Both multiplication diagrams formed by axes I and II, II and III are shown in Figures I and II.

Figure I: Location of 40 swimmers in 100m freestyle by I & II when analyzing the basics.

Figure II: Position of 40 swimmers at 100m freestyle by II & III when analyzing the basic factors.

Figure III: Relationship between the speed of the first 50 m (V1) and the last 50 m (V2) of the 100 m freestyle swim of 40 high-level athletes. It seems more reasonable to compare the results of axis I with the results of other axes. Axis I matches athletes with the length of each major cycle with high frequency players (each athlete is represented by his first three letters). On the first and third axes, the athletes differ in how they swim 100m (Figure I).

Group I: Highlighted with swimming frequency is Hac, Ly, Hol, Tay, Bas, Wer, Tit, Lef.

Group II: is the length of each cycle (length of the swim): Hla, Sho, Sta, Gut, Kam, Gru, Pop, Dep, Poi, Def, Bla.

Group III: Standing between the two groups, in this figure we need to pay attention to some of the values ​​that correspond to certain individuals, namely Pap, Hol, Tay and Wer. I & Figure II). The world’s best pop athlete (who has become the Olympic champion) surpasses the large index of a cycle (2.69m) with very low swimming frequency

 (44.75 cycles.min -1 ). Holts, Hands, and Wer have the length of each cycle, but have high pitch frequencies. The contribution of these four athletes to the establishment of the research axis is not large, so it is not necessary to repeat the analysis of the basic factors, but we only consider these athletes as additional factors.

The vertical axis II denotes the velocity corresponding to the level of achievement. The individual who swims as fast as he is at the top of the shaft, and vice versa.

Axis III tells us about the balance in the race as it compares the percentages of the two races. Athletes stand near the “% of clusters”. Some other athletes have constant speed throughout the race. Their characteristic is that there is a very small difference between the percentages at the first 50m and 50m, such as Hla, Sho, Kal, Gil, Wer, Sech, Gut, Poi. These athletes are very different from the athletes who have had a great speed change in the first and second laps of Car2, Gre, Bas, Tit, Dep, Cra, Poi. There is one case to note that the case of a player is present at all competitions. I noticed all four (Car1, Car2, Car3, Car4) related to this athlete – the best French athlete.

Figure 4: Relationship between the frequency of the first 50 m (F1) and the last 50 m (F2) of 40 players.

 This analysis aims to study the linear relationship between change in the first 50 m and 50 m. Figure 3 shows the distribution chart of velocity recorded in the 50m head (V1) and velocity in the last 50m (V2). The R 2  factor is very small (0.2 <0.50) so we can not establish a linear relationship between V1 & V2.

Figure 4 – Relationship between the frequency of the first 50m (F1) and the last 50m (F2). Here we find three special players are Hol, Tay, Wer road outside the main round of points. To make this sample more accurate a large number of athletes and athletes must fill the gap between the main round and three other individual players. However, we think that one of the special things about studying the senior players is the large number of solutions that they apply in the race.

The sum of all points in Figure 4 shows that the correlation coefficient (R 2  = 0.80) is sufficient to establish a linear relationship. The straight line from top to bottom passing through these points is:

F2 = (0.707 F1) + 13.279

Figure 5 shows that four players have different options than the rest. We feel that in this particular case it is necessary to include in this regression line the solutions that athletes have adopted such as the 100 m (2.69 m) average of one cycle). The correlation coefficient R 2 = 0.756 allows us to determine the regression line: DCM2 = (0.692 DCM1) + 0.507

Figure 5: Relationship between the length of each 50m head (DCM1) and the last 50m (DCM2).

This type of research is of a descriptive type and does not directly affect the athletes when they are playing.

Once the data has been collected, they are immediately classified and monitored. It is clear that even if one waits for a result, this method of treatment is not an experimental one. Among the descriptive research methods, specific calculations allow us to quickly identify the characteristics of the subject. The analysis of the basic elements helps us to classify the factors that can explain the different achievements of the athletes. The statistical method explained by the simple regression analysis of the fundamental changes of this study allows us to distinguish the change in velocity, frequency, or length of each cycle in a linear relationship. Between the top 50m and the last 50m of each race. One criticism of this study is the lack of data on the athlete’s body, If there are data that will help us to explain more clearly the results obtained. In fact, the height, the length of the limbs and the height of the athletes are very different factors [12,17,18,26]. The reason for this criticism comes from two main reasons: The first is that research that is concerned with the relationship between athlete performance characteristics and performance often compares athletes with achievement scores different [26]. Or compare two teams of different level. Grimon and other researchers [12] studied 14 prospective athletes by another method. Our research is concerned only with the selected athletes. In these athletes, the factors that affect them less. For example, in high jump, the height of the athlete is a very important factor, But in the 20 best athletes in the world, the difference in height is not important anymore, it does not affect their performance anymore. Second reason – It is possible to make an explanation of the measurements of 100 m freestyle swimmers less important, namely: if the athlete’s measurements are an important factor in swimming In the 100m freestyle, there is little effect. In fact, Pelayo and his colleagues have also conducted the same study as we do, but they did not find in the 100m freestyle swimmers the organic correlation between performance parameters, velocity, the length of each cycle, the frequency and age, the body measurements of athletes. If the measurements of the athlete are an important factor in swimming generally in the 100m freestyle swim almost no effect. In fact, Pelayo and his colleagues have also conducted the same study as we do, but they did not find in the 100m freestyle swimmers the organic correlation between performance parameters, velocity, the length of each cycle, the frequency and age, the body measurements of athletes. If the measurements of the athlete are an important factor in swimming generally in the 100m freestyle swim almost no effect. In fact, Pelayo and his colleagues have also conducted the same study as we do, but they did not find in the 100m freestyle swimmers the organic correlation between performance parameters, velocity, the length of each cycle, the frequency and age, the body measurements of athletes.

More specifically, we took two cases in our study: Car1 – 2.01 m high, weighs 85 kg, has a swim length of 2.26 m. cycle -1  and frequency is 49.5 cycles. min -1 . In contrast Kal athletes 1.76 m high, weighs 85 kg with a swim length of 2.38 m. cycle -1  and swimming pool frequency are 49.5 cycles. min  -1 . The example above shows that a player less than 25 cm at the same speed has a swim length greater than 12 cm. This proves that the decisive answer is that there is a great deal of difficulty in regulating the pitch / pitch relationship  first and foremost regarding the technical and tactical factors of the athletes.

It can be seen that the standard deviation of the velocity in the two-way direction of the swimming pool ( ±  0.04 and 0.04 m. S -1 ) is lower than the difference in length of each cycle ( ± 0 , 23 and 0.18 m, cycle -1 ) and much lower than the standard deviation in frequency ( ± 5.23 and 4.15 cycles x minutes  -1Table 1. Of course, velocity variations are rare when athletes have been specially selected according to this standard (or at least they have these abilities). Apparently one of the first eight athletes of the contest to be featured in the final was included in the team, as he was faster than the ninth athlete despite his frequency and duration. How come? So strategic choices – The relationship between the length of each cycle and the pitch of the swimmer is different from that of other athletes. However, even if we observe the fundamental differences, the length of each great cycle is usually attributed to the great athlete. Although there are many differences between individuals, this trait is present in all of the subjects we studied. Furthermore, these values ​​were much higher than those recorded in other normal athletes [2,21,23]. The results of this study will be a guideline for training in the case of assessing the length of each cycle combined with speed estimation to achieve high performance in training and competition. In contrast, the value of frequencies of athletes is very close to the frequency of normal athletes [2,21,23]. This observation is perfectly consistent with Costill and colleagues [7]. They pointed out that the best predictor of achievement in a player during training was the length of each run (R = 0.88). The variety of frequencies and lengths of each cycle can be explained by the recorded data at the Cannet mass races of 1992. The 1992 event was rather special, There were two winners at the Olympic Games in 1992: a 100m freestyle for Pap. This is the most famous athlete in the world, he has the most swimming way. 200m freestyle silver medal for the famous athlete Hol, he has the highest swimming frequency in the world. In addition, the competition is also preparing for the Swedish team to participate in the 1992 Olympic Games. This is the team with the highest swimming frequency in the world like their captain Hol. Even so, the competition held at Cannet 1992 was not a high-flying 100m freestyle competition. This limitation was corrected by integrating the race into all other races held at Cannet. 200m freestyle silver medal for the famous athlete Hol, he has the highest swimming frequency in the world. In addition, the competition is also preparing for the Swedish team to participate in the 1992 Olympic Games. This is the team with the highest swimming frequency in the world like their captain Hol. Even so, the competition held at Cannet 1992 was not a high-flying 100m freestyle competition. This limitation was corrected by integrating the race into all other races held at Cannet. 200m freestyle silver medal for the famous athlete Hol, he has the highest swimming frequency in the world. In addition, the competition is also preparing for the Swedish team to participate in the 1992 Olympic Games. This is the team with the highest swimming frequency in the world like their captain Hol. Even so, the competition held at Cannet 1992 was not a high-flying 100m freestyle competition. This limitation was corrected by integrating the race into all other races held at Cannet. Even so, the competition held at Cannet 1992 was not a high-flying 100m freestyle competition. This limitation was corrected by integrating the race into all other races held at Cannet. Even so, the competition held at Cannet 1992 was not a high-flying 100m freestyle competition. This limitation was corrected by integrating the race into all other races held at Cannet.

As we have shown in Figure 1 and Figure 2, the athletes have a very different set of swimming techniques and have been mapped together in the form of the basic elements analysis table. It is clear in Figure 1 that the position of Pop is completely isolated as he is both the fastest player and the longest-running player. In contrast, in the first axis we see three athletes, although their speed is quite high, but still have high swimming frequency. Thus, we can compare the positions of high velocity athletes and the mean swimming length / average frequency (Car, Kal) for low speed but high frequency athletes (Tit, Hac ) or have a large cycle length (Gru), Wer athletes are distinguished from other athletes because of the frequency, velocity and length of each cycle at an average level.

Three athletes in our study (Pap, Hol, Car) all three athletes won Olympic medals and have different basic characteristics. Each person belongs to one group as shown. (Figure 1) .Pap has the advantage of the length of the cycle, the Hol has the advantage of swimming frequency and the Car stands in between these two players. In our opinion, if this explanation is not reasonable, it should be emphasized that the field of talent of these three players are completely different. Pap won the championship at the Olympic Games 50m freestyle, 100m. Car won two Olympic medals 100m freestyle. Hol, though quite perfect in the 100m freestyle, won the gold medal in the free-kick at 200m, 400m. So maybe the frequency rating is not only used in the 100m swim test, but also in other swimming ranges. The issue of measuring the length of the cycle, too, Can be used for swimming courses that are larger than 100m. The structure of the 100 m freestyle swimming technique is how to have the optimal pitch and frequency relationship.

In the special case of the athlete, four times of monitoring and evaluation, each time the athlete has a different velocity and the swimming index that we observe is always changing. Naturally, we will not make any formal conclusions about the training regimen, the tactics of the athletes, but we provide only the following explanations:

At Cannet in 1990, Car1 won the race in a clear manner. In 1991, Car 2 was in active preparation for physical training, but he also won a silver medal. In 1992, Dunkerque landed in the shortest time. He then joined the Cannet massacre in 1992, a month before the Games to try out the athletes, and at this he reached the third goal. This is not related to the change in the relationship between the length of the cycle and the frequency. So we can assume that the athlete retains the “swimming mechanism” during the exercise, but has different levels of training.

Among these results, the faint relationship between the velocity of the first 50m and 50m seems to be quite significant. We found that the difference in time between the two oscillations was 1.60  ±  0.12y. Obviously, if the race is structured to distribute strength, the relationship between the two speeds of the two races (the first 50m and the last 50m) will be clear. In other words, if each of the athletes we studied had the optimum way to structure the technical elements for the competition, the velocity values ​​of the two segments would have a significant relationship. Maybe the speed at 50m is not related to the speed at the last 50m because the speed at 50m depends on the advantage at the starting point when the athlete dives into the water. This shows that each athlete uses this advantage differently, on the other hand, this allows the assessment of the ability of the individual to dive and swim further. This can also be explained by the strategic situation of each athlete. For example, some athletes just need to get involved in the final, some other athletes strive to stand on the podium, Try to create the best personal records and only in such cases will the structure of the swimmer elements reach the optimal level. For veteran athletes, fixing the frequencies they have chosen is a decisive factor for their performance. It is clear that at the same velocity, any oscillation or change in the frequency of swimming leads to increased energy consumption [8]. So all frequency choices are unchanged until the end of the race. It is not surprising that the best athletes in the 100m freestyle tend to regress. About the length of each cycle, the relationship between the first 50m and 50m is also significant. As we have seen above, this factor is critical to high achievement. From this point of view, stabilizing the length of the cycle is a prerequisite.

The results of our research have some influence on the attitude of the athlete. The systematic high value of each cycle (2.26  ±  0.20 mx cycle  -1 ) shows the excellent performance of the thrust. Actually the length of each cycle when considered independent of velocity is the best indication for swim quality. Even very strong thrust can not produce large lengths at each cycle if the resistance to the resistance is reduced due to the front or lateral contact with water that is not suitable for the hydrodynamic principle. . Qualified athletes have chosen the most appropriate way of receiving water because even with great resistance due to high velocity (resistance to velocity is proportional to velocity squared) and thus they are still reachable. The swim length is great.

Although there are differences in the choice of the swim length / frequency relationship for each athlete, this setting is fixed until the end of the race. All variations in the parameters of the engine, Push is the cause of increased energy consumption. Despite the fatigue, maintaining the relationship between swim length / frequency is a striking feature for high-level athletes, and this is something to be gained in training.

In addition to the information considered as the characteristics of the level athlete, it should be understood that not only a path to success. Various logical facts also clarify the characteristics of high-level athletes. Before taking this champion or champion as a model to follow, first analyze the individual characteristics of the champion and then ask yourself: are his achievements Would not it be better to have a choice of other sensible swimming solutions? A high-level athlete in his swimming style not only converges all personal characteristics and motifs, but also a part of his ability to create, but the light itself. This has left a huge gap for other athletes to overcome,

We observed that the structure of 100m freestyle swimmers was very specific to this study. It should be recalled that the accomplishments of the study participants allowed us to consider this subject to be a high-level subject. Not all 40 athletes use the same speed adjustment method. In contrast to the superiority at the starting point and after they have determined the relationship between their specific swim length and frequency, they maintain that relationship until the end of the race. However, some of the best athletes we have studied have adopted solutions beyond those standards.

Athletes of different nationalities have different training and preparation. This analysis allows us to better understand the patterns of pooling techniques used and the adaptation of high-level athletes to the rules regarding the cyclical nature of the activity. .

Our research can also be a help, a guide for coaches and athletes in the preparation phase of the strategy. In other words, the solutions of the athletes of the level are often full of creativity and surprise. So being a champion is not just about copying the stereotypes that demand the very creativity of the coaches and players.

 

POOLSTORE (SPORTS INSTITUTE OF SCIENCE)