Comparison of Maximal Aerobic Speeds of Team-sport Athletes and Investigation of Optimal Training Loads

To investigate maximal aerobic speed (MAS), participants of team sports in terms of certain variables and to determine relationship team sports. In this study, it was used from quantitative research approach, screening research. 44 athletes voluntarily participated in study. Current average; age was 17.20±1.0 years, height was 178.6±6.6 cm, and weight was 73.1±11.2 kg. 20-meter shuttle run test (20MSRT) was used as a data collection tool. It was applied descriptive statistics, inferential one-way analysis of variance (ANOVA), Pearson product-moment correlation and sources of meaningful differences were examined by least significant difference (LSD) test. There was a positive relationship between age, VO 2max and speed scores (p < 0.05). Besides, significant difference between VO 2max , distance and speed also VO 2max , distance and speed were found to be significantly different according to types of sports (p < 0.05). When distance and speed scores of athletes were examined, it was determined that mean scores of football players were higher compared to basketball and handball. Heart rate and MAS scores of participants were not significantly different according to type of sport played. This study will contribute to strength and strength coaches, trainers and physiotherapists in terms of training programs that they will apply to athletes of various sports.


INTRODUCTION
Many studies are carried out to identify characteristic qualities of competitors in different sports.Thanks to the developing technology, sports science renews itself day by day and tries to discover training techniques that increase success.In this context, contemporary training methods consider effects of high-intensity aerobic running speed training on physiological and performance values in team sports.Moreover, research is conducted on individual training applications related to different types of sports(J.Baker et al., 2003).MAS is defined in the literature as the speed of movement produced by an athlete at maximal aerobic power or 100% of VO2max (Bosquet et al., 2002;Rampinini et al., 2009).MAS measurements are made in km/h.It is more important to know the MAS, which is mandatory to adjust the running speed, which in turn facilitates physiological development, than to know VO2max (D. Baker and Heaney, 2005).It is thought that being able to adjust running speed of the athletes according to needs of the sports that they play will have an important role in their performances.On the other hand, it is thought that these running speeds may differ between sports, players' positions, and even genders.It is known that MAS are determined optimally according to type of sport and comparisons can be made accordingly.In this way, it becomes easier and more efficient to follow the physiological development of athletes (D. Baker and Heaney, 2005).This process is attracting more interest day by day from sports scientists.Furthermore, looking at the current literature on MAS, it is seen that it is next to this (D. Baker, 2011;D. Baker and Heaney, 2005;Bellenger et al., 2015;Berthoin et al., 1994;Mülazımoğlu, 2012).On the other hand, when examining studies conducted outside of Turkey, it is seen that there is slightly more research available in the literature (D. Baker, 2015;D. Baker and Heaney, 2005;Dellal et al., 2008;González-Badillo et al., 2015).As a result, this study will contribute to the existing literature in terms of relationships between types of sports and age of athletes and maximal aerobic speed.Therefore, the purpose of this research is a comparison of maximal aerobic speed (MAS) of young athletes and investigation of optimal training loads.

Research Design
The aim of this study is to compare the MAS of young athletes participating in team sports and to determine the optimal training loads.In this study, a quantitative research approach was used.As a methodological approach, the screening method was preferred in order to determine the most obvious characteristics of the participants, such as their skills and attitudes (Büyüköztürk et al., 2017).The 20-meter shuttle run test was applied as a data collection technique by the researchers to the athletes forming the working group after obtaining the necessary permissions.Athletes voluntarily participated in the implementation of the data collection tool, and informed consent forms were obtained from them or their families.

Statistical Analysis
Before proceeding to the analysis stage, the data of the research were tested to determine whether they were suitable for normal distribution with the Shapiro-Wilk W test and kurtosis and skewness values.Parametric techniques were used because the distributions were observed to be normal.The data were analysed with the SPSS 23 package program.In this context, information about the research group and various research variables were evaluated using descriptive statistics techniques.As data analysis techniques, one-way analysis of variance (ANOVA) and Pearson product-moment correlation coefficients were used.In the analysis of the data, significance levels were taken as 0.05.

20-Meter Shuttle Run Test
Within the scope of this research, the Trabzonspor Kadir Özcan Youth Development Centre's synthetic field was used for the 20-meter shuttle run test.Active male athletes from football, basketball, and handball voluntarily participated in the study.Six running tracks, consisting of a flat area of 20 meters, were used for the test.The starting and ending points of the created areas were determined by marking them with training funnels.The command signals necessary for the test were transferred from a computer environment to the athletes via a sound system.Before starting the test, the athletes were allowed to acclimate to low-intensity shuttle running exercises.In addition, the athletes were encouraged to run at the maximum level during the test and to complete the test at the maximum level."The running speed at the start of the test is 8.5 km and the running speed is gradually increased by 0.5 km per minute.The test ended with two faults occurring repeatedly or when athletes reached their burnout levels" (Köklü et al., 2011).

Heart Rate Measurement Equipment
A heart rate monitor (Polar RS 800, Finland), which can measure heart rate instantly, was used to determine the heart rate and save it to the computer.

Heart Rate Measurement Equipment
A heart rate monitor (Polar RS 800, Finland), which can measure heart rate instantly, was used to determine the heart rate and save it to the computer.

Heart Rate Measurement Equipment
A heart rate monitor (Polar RS 800, Finland), which can measure heart rate instantly, was used to determine the heart rate and save it to the computer.

Calculation of Maximal Aerobic Speed
There are many different formulas and test models to calculate MAS directly and indirectly (D. Baker, 2015).Baker and Heaney obtained some normative aerobic fitness data for MAS scores for athletes competing in field sports.In this sense, they used the following tests to determine MAS: laboratory tests, Multistage Montreal Beep, VAMEVAL, YoYoIR1, Carminatti's test, Multistage Shuttle Beep, Set Time Trial, Set Distance Trial, and 1200m Shuttle.The test model applied in the current study is the Multistage Shuttle Beep (20-m shuttle run test).The formula for calculating MAS in this test is as follows: (MAS=Latest speed (km/h)×1.34-2.86)[13].The result of this formula gives us MAS in km/h.It should then be converted to m/s so that training running distances can be more easily calculated.For example, the MAS of an athlete whose test is completed at the 13th shuttle level is calculated as follows: 13th shuttle speed=14.5km/h.We need to put it into the formula and convert it to m/s as follows: MAS= 14.5×1.34-2.86=16.5 (km/h)×1000/3600=4.6 m/s.There is also a general correction formula for calculating MAS with estimated VO2max (MAS=Estimated VO2max/3.5),which gives us the result in kilometres per hour (Léger and Abdullah Cetindemir, et al.: Comparison of Maximal Aerobic Speeds of Team-sport Athletes and Investigation of Optimal Training Loads Mercier, 1984).

RESULT
In this section, the appropriateness of the variables for normal distribution is examined with skewness and kurtosis values, and demographic information and descriptive values related to the research variables are shown both on a general basis and according to the type of sport played.Afterwards, information about the test results is included.The arithmetic averages of test performance parameters (HR, VO2max, distance, speed, and MAS) of the football, basketball and handball players are presented in Table 1.The relationships between some parameters and the MAS values of participants of different sports were tested with ANOVA.The results are given in Table 3.As a result of this analysis, VO2max, distance, and speed were found to differ according to type of sport.In the LSD test performed to find source of difference, VO2max scores favour football, basketball and handball.In favour of football and handball scores showed a significant difference in favour of basketball.Among the distance values of the athletes, the average of football players was highest (X ̅ = 2176.25,SD = 487.83)compared to basketball (X ̅ = 1548.33,SD = 412.92)and handball (X ̅ = 1192.50,SD = 435.72).The average distance score of the basketball players was higher than that of handball players.In terms of speed values, basketball players had the highest average among the three types of sports.There were no significant changes in HR or MAS scores of the participants according to type of sport.In the MAS scores of the athletes, a significant difference was found in favour of football between football and handball players.While there was no significant difference in the ANOVA test, the significant difference seen in the LSD test may be due to the precise measurement of the LSD test.According to this relationship, MAS scores increase as the age, VO2max, distance, and speed of the athletes increase.It can be said that the MAS score will increase as the age variable increases.This can be described as a developmental process and it shows parallelism with other studies performed (Baquet et al., 1999).However, no study investigating the relationship between VO2max, distance, and speed variables and MAS scores was found.In this sense, when the relationships of these variables are interpreted, according to the formula MAS is calculated as (MAS = Latest speed (km/h) × 1.34 -2.86).The higher the speed variable, the higher the MAS value will be indirectly.
According to the protocol of the 20-meter shuttle run test, when the relationship of MAS with distance is interpreted, distance covered must be increased in order to obtain the speed value of participants or to obtain next speed level.
According to the VO2max formulas used in the calculations in our study, for the VO2max value to be high, the speed score should also be high (D. Baker, 2015).The relationship between athletes' HR, VO2max, distance, speed and MAS values and the type of sport was tested with ANOVA.As a result of this analysis, it was found that VO2max, distance and speed differ according to type of sport.
In the LSD test conducted to find the source of the difference, there was a significant difference in VO2max.Scores of football players were highest in comparisons of football, basketball and handball, while basketball scores were higher than those for handball.In this sense, when studies on footballers are examined, had similar findings for VO2max values (Crisp et al., 2013;Helgerud et al., 2001).In studies of basketball players, similar VO2max findings (Crisp et al., 2013).Finally, when studies of handball players are examined, lower VO2max values were calculated in a previous study (Zapartidis et al., 2011).For this reason, the training and conditioning of athletes can be predicted.The average distance of those who played football was higher compared to basketball and handball.The average distance score of basketball players was higher than that of handball players.When similar previous studies are examined, which examines the distance between 8619 -10,335m, the distance travelled about basketball, the average distance of athletes is 5587m, and the distance covered in handball found distances covered in their study as 3627m (Crisp et al., 2013;Helgerud et al., 2001;McInnes et al., 1995;Oba and Okuda, 2008).In this sense, it is thought that reason for the difference in distances between different types of sports is due to structural differences.In this sense, what separates games from each other, that is area measures or the playing time of the games.Based on these differences, it can be said that when the data in our study are compared, the same parallelism is revealed.When looking at the speed values, a difference was observed in favour of football when comparing the scores for all three studied sports and in favour of basketball when comparing handball and basketball.When studies on football are examined, performance values related to the shuttle run test applied to football players in his study (Gastin et al., 2017;Spinks et al., 2002;Vitale et al., 2018).
In that study, speed reached by young football players in the shuttle run test was found as 13.7 km/h, which is very close to speed obtained in our study (13.8 km/h).When we look at studies about basketball, results of shuttle tests to determine maximal oxygen consumption among basketball players.
The study stated that basketball players were able to run an average of 2152 m in the 20-meter shuttle run test.This Abdullah Cetindemir, et al.: Comparison of Maximal Aerobic Speeds of Team-sport Athletes and Investigation of Optimal Training Loads result corresponds to a speed of approximately 14 km/h in the test protocol.When this result is compared with current research (12.45 km/h), it is seen that previous speed score was higher.It is thought that such a difference may be due to athlete age, training, and conditioning levels.Finally, looking at work on handball, reported that handball players had an average speed of 13.25 km/h in the 20-meter shuttle run test.In this study, it was found that handball players had an average speed of 11.65 km/h.This speed is lower.Such a difference may be due to athlete age, training, and conditioning levels, as mentioned above (Paradisis et al., 2014;Suna et al., 2016).No significant changes were observed in the HR and MAS scores of participants according to types of sports.However, in the LSD test, a significant difference was observed in the HR scores of the football and handball players in favour of handball.When we examine maximal HR results in studies on basketball, reported that HR of basketball players in 20meter shuttle run test as 198.46 beats/min (Moran et al., 2019).In the current study, it was found to be 196.58beats/min.When we examine other studies, found that average heart rate during basketball competitions to be 169 ± 9 beats/min (McInnes et al., 1995).
When we examine studies about football players, found that maximal heart rate to be 196.92beats/min in a shuttle run test applied to young footballers (Nassis et al., 2010).Analysed HR of footballers and reported an average of 164 beats/min (Bangsbo et al., 1991).Danish players and different study reported that 171 beats/min for professional players (Ali and Farrally, 1991;Journal, 2014).As a result of the study, it was found to be 193.81beats/min.When we examine works on handball, reported that HR of 180 beats/min for handball players in 20-meter shuttle run test.
In the current study, it was found to be 199.87beats/min.In addition, in a study testing physiological and physical capacities of elite male handball players, found maximal HR of handball players in the Yo-Yo test to be 191 beats/min.(Michalsik et al., 2015;Suna et al., 2016).
For the MAS scores of athletes, a significant difference was found between football and handball players in favour of football.While there was no significant difference in ANOVA test, significant difference in LSD test may be due to precise measurement of LSD test.As a result of our current study, MAS of football players was 3.92 m/s, while that of basketball players was 3.84 m/s and that of handball players was 3.54 m/s.When we examine studies in literature, it can be seen that there is very limited research on MAS.The value for Italy Series A footballers was reported as 4.91 m/s with rampinini test (Rosenblatt, 2014).

CONCLUSIONS
1.It was found that as age, VO2max, and distance and speed scores of athletes increased, the MAS also increased.2. A positive correlation was found between age and VO2max and speed scores.3. A positive correlation was found between VO2max and distance and speed.4. A negative relationship was found between Bmi and VO2max and speed.It was found that VO2max, distance, and speed differed according to types of sports.In the LSD test conducted to find the source of difference, there was a significant difference in VO2max in favour of football compared to basketball and handball scores, and in favour of basketball compared to handball scores.For the distance values of the athletes, it was observed that average of football players was higher compared to basketball and handball.Similarly, the average score of basketball players was higher than that of handball players. 5.When speed values for different types of sports were analysed, a difference was found in favour of football compared to basketball and handball, and scores for basketball were higher than those for handball.6.No significant changes were observed in HR and MAS scores of the participants according to types of sports.However, in LSD test, a significant difference was found between football and handball in favour of football in MAS scores of the athletes.

MAS
10 minutes is preferred, 1-2 set method can be used.2-4 minutes rest time should be given between sets.Accordingly, the grid training model for football players, basketball players, and handball players is presented visually in Figure1.(D. Baker, 2011).

Figure 1 .
Figure 1.MAS program with grid method for football, basketball, and handball players

Figure 2 .
Figure 2. MAS running distances with Eurofit method for football, basketball, and handball players

Figure 3 .
Figure 3. Mas running distances with tabata method for football, basketball and handball branches

Table 1 .
Descriptive statistics for performance variables

Table 2 .
Relationships between height, weight, age, and Bmi and HR, distance, speed, and MAS values

Table 3 .
HR, VO2max, distance, speed, and MAS values of athletes according to type of sport DISCUSSIONIn this research, relationships between athletes' height, weight, age, and Bmi and HR, VO2max, distance, speed, and MAS scores were examined with Pearson correlations.A positive correlation was found between age, VO2max, and speed and MAS values.

Table 4 .
Table 4. MAS program with long interval method for football, basketball, and handball players Long edge, KK; Short edge, MAS; Maksimal aerobic speed

MAS program with grid method for football, basketball, and handball
1:1 Running/Rest-Active (15 s: 15 s).Long edge run with 100% MAS.Short edge run with 70% MAS, work starts with 6 minutes, 2-4 sets if 8 minutes run time is preferred.If