However, these same studies pointed that the players who act on by the sides of the field cover greater high intensity distances. The full-backs have as function to participate in the transition from the defense to the offense, involving high intensity running through the sides of the field, which helps to explain the result obtained in our study. Indeed, Aquino et al. Biochemical, physical and tactical analysis of a simulated game in young soccer players.
In addition, Osiecki et al. J Exerc Physiol. However, the perceived recovery of the full-backs was 4. These variables, added to the external load, indicate the physical distress suffered on the game. In addition, the internal load was not different between positions variation of Our results proved that there was no difference on recovery, internal and external load variables between wins, losses, and draws.
However, in a practical point of view, it could be explained by the fact that the actions performed on defense and offense aim to take the lead. This behavior makes the internal and external load and the recovery very similar regardless the team is losing, drawing or winning the game. In the present study, no biochemical indicators of muscle damage were used. Another point was that the analysis related to the match outcome was not detailed by playing position, however, it was necessary due to the sample, that would have insufficient subjects for each position, which would limit the power of the analysis, once the considered period had five wins, two losses, and two draws.
However, the methodology and the instruments used in the study significantly contribute to the literature and to the soccer clubs. Additionally, there was no difference on recovery, external and internal load variables according to the match outcome wins, losses, and draws. Abrir menu Brasil. Abrir menu. Juan H. Abstract AIMS To compare the internal and external load and the recovery by playing position and the match outcome wins, losses or draws in professional soccer.
Introduction The high physical demand required on high-level soccer has been previously demonstrated 1 1. Methods Design It was analyzed nine official matches of the first division of the local soccer championship ranking stage. Participants Twenty-three male professional soccer athletes from a team of the first division of the Brazilian Championship took part into the study age Table 1 Comparison of external and internal load and recovery by playing position.
Table 2 Comparison of external and internal load and recovery by the result. However, the former study [ 26 ] only analyzed one single sub-elite game and, therefore, caution is warranted when directly comparing the results. For this reason, future research is needed in this area.
Taken together, the distance and speed data extracted from the literature hint that higher level basketball players seem to cover less distance but achieve greater top speeds during competition, which is in line with what has been reported in other team sports [ 52 , 50 ]. Time motion analysis has been widely used to track frequency and duration of movements during competition [ 4 , 18 , 26 , 22 , 14 , 9 , 32 ].
Running was defined as sagittal plane movement at a greater intensity than jogging and with a moderate degree of urgency at 3. Ferioli et al. Upon review, Ferioli et al. Scanlan et al. Again, these results would suggest that top-level basketball players spend more time at high-intensity activities compared to their sub-elite counterparts.
In addition, elite players tend to display greater control over the most appropriate time and situations to express high-intensity actions relative to the total distance covered whilst on the court. Both studies showed that guards spend more time running compared to forwards and centers.
This information, seen in Table 3 , is useful and may have important implications when prescribing high-intensity running relative to each position in basketball. Based on these results, individual conditioning programs should be adapted to the specific physical requirements of guards, forwards, and centers, keeping in mind that the latter have been found to have a lower proportion of high-intensity running, acceleration, decelerations, and COD.
Heart rate in training was used to quantify the cardiovascular demands imposed on the athletes [ 3 , 12 , 35 , 20 , 23 , 24 ]. Torres-Ronda et al.
Gocentas et al. More investigation is needed in the future as it relates to the HR demands of varying training programs. In basketball, this method has been widely used to assess Training Load [ 35 , 37 , 41 ] and has been shown to provide good insight on the energy cost of different movement patterns, particularly when coupled with external load data [ 2 , 10 , 39 ].
Briefly, it involves players reporting their RPE score using the Borg point scale thirty minutes after the completion of each training session, multiplying the value by the number of minutes of the session [ 41 ] and then calculating the sum of the values of each training session during the week. As noted in Table 4 , the Total Weekly Training Loads in the studies analyzed ranged from to AU in elite level teams [ 35 , 37 , 41 ].
The large range observed is likely due to the high variability on the number of training sessions or practice duration based on the loads provided by the technical staff. Since sRPE is obtained by multiplying RPE by session duration, the accumulative amount of weekly training load is dependent on the duration of each training session, which can vary based on style of play, level of competition, or moment of the season [ 36 , 42 , 44 ].
In addition, Svilar et al. According to the authors, the rapid eccentric actions involved in decelerations, cuts, and COD may explain the abovementioned relationship [ 1 , 2 ]. Nevertheless, the mechanical stress imposed on the athletes during these movements, as well as the effects of eccentric training in basketball athletes, are areas that need additional investigation in upcoming studies. Therefore, when designing appropriate training sessions, a combination of internal and external load variables is recommended [ 2 , 10 , 39 ].
In elite level basketball, ACC T in training varied from The DEC T in elite basketball training ranged from The total volume of ACC in competition was 81 per match on average, as opposed to a mean of 38 accelerations per training session [ 36 , 40 , 43 , 47 ]. This was also the case with DEC. DEC T in competition was The present data supports the notion that training, and match demands seem to be considerably different, at least considering the number of ACC and DEC [ 15 ].
Matching the volume and intensity of competition via training is important during certain times of the preparatory and competitive season to adequately prepare the athletes for competition. As a consequence, the data reported herein may be extremely pertinent for practitioners in regard to training reflecting the demands of match-playing, as well as modulating training load based on outputs of these variables during competition.
In this context, to try and achieve similar or even greater ACC demands in training with respect to match-play, manipulating constraints such as the number of players, the duration of drills or court dimension may be a potential strategy [ 12 , 15 , 47 ]. Within this framework, Schelling and Torres [ 47 ] found that ACC load in 3vs3 and 5vs5 full court scrimmage drills was greater than 2vs2 and 4vs4 full court scrimmage drills, indeed suggesting that manipulating training variables may greatly affect the total load imposed to the players.
A study by Svilar et al. Interestingly, the authors examined load parameters according to positional on-court roles and found that centers had a higher volume of ACC T Also, noteworthy, forwards were shown to have a high volume of DEC T It appears that the profiles of activity are quite different amongst positions and further research is necessary to better understand each individual profile.
Still, the amount of exposures to cuts, COD, or screening actions, as well as the typical movement area of each positional role may conceivably explain such findings [ 6 , 10 , 12 , 16 , 27 , 53 ].
Despite the aforementioned, one must consider the limitations of accelerometry when measuring external load. Even though such technology is extremely useful, accelerometers fail to measure the metabolic demands of isometric muscle contractions during player-on-player contact due to the low velocity outputs.
While these actions have very low acceleration, they potentially have very high energy demands [ 1 , 19 , 54 ]. Therefore, the physical cost of player-on-player contact loading is a component of basketball that must be examined more thoroughly in future research to more accurately quantify training and competition load.
Some limitations should be addressed when considering the present research on training load and competition demands among different levels of basketball. Firstly, several elite leagues e. Secondly, when trying to investigate these variables, most sub-elite and youth teams do not have the financial means to invest in equipment to accurately quantify load during training.
Finally, the limited number and sample size of youth and sub-elite studies made it difficult to conclude the precise demands of training and competition at these levels. As such, more resources need to be invested in these areas.
Basketball is a highly competitive team-sport that requires a cascade and flow of various movement patterns relative to the technical and tactical aspects of the sport.
Examining the internal and external loads imposed on the players from both training and competition provides context for the practitioner to create an optimal training environment. From the results of the present systematic review, it appears that higher-level players seem to be more efficient while moving on-court.
Elite level players cover less distance, at lower average velocities, and with lower HR max and HR ave during competition. However, they seem to have greater capacities to move at higher speed. This is likely due to a heightened sense of awareness based on the schematics of the game.
Examining this holistic approach creates an ideal training environment that facilitates both technical and tactical development as it relates to the game of basketball. Future research must be dedicated to this area to provide more precise insight into the physical and interpositional demands of the sport. Kinesiology is non-profit journal and all costs of publishing and peer review process are covered by the publisher itself or other funding sources like Ministry of Science and Education of the Republic of Croatia.
There are no restrictions on self archiving of any form of paper preprint, postprint and publisher's version. In relation to acc counts and dec counts WM presented higher values Furthermore, all positions, except CB, performed less acc counts than dec counts during the entire match Table 1. CB had the lowest values of all positions in both variables but especially pronounced in Sprint wr 0. Regarding HIR dist , CF presented higher values in 26—30 m than all the other positions, while distances of 36—40 and 46—50 m were covered more times by FB 1.
Table 3. Furthermore, there was a pattern of covariance in the work-rates analysed acc, dec, HIR and sprint across playing positions Fig 1. Mean work-rate in sprints, HIR, acc and dec.
The main outcome was that CB performed less turns per match The present study shows that the physical demands in official match-play, in elite football, vary greatly across playing positions. As previously mentioned, a novel finding from this study was that the work-rates in HIR, sprints, accelerations and decelerations change in the same pattern across playing positions.
These findings are in line with the research literature regarding FB covering greater high-intensity and sprinting distances during matches compared to CB. Previous studies have reported greater distances in HIR and sprint covered by wide players FB and WM compared with more central positions CB, CM and CF [ 13 , 20 , 24 , 31 ], however the present study shows significant higher work-rate for wide positions only in acc, dec and sprints but not in HIR, even though the values for wide positions are slightly, though insignificantly, higher than for central positions excluding CF.
No significant differences were observed between CF and WM in HIR wr which is in line with previous research [ 18 ], but in opposition to others [ 11 , 20 , 31 ]. Furthermore, our data show that CF is the most physical demanding position with longer distances covered in HIR, sprints, accelerating and decelerating than the other positions. It has been speculated within the research literature that these differences between wide and more central positions are due to a lack of space for reaching sprinting velocity and the playing style different roles for different positions [ 24 , 25 , 32 ].
Table 2 illustrates that player position had a significant influence on the different distances covered in HIR. An aspect to consider is that we also observed some HIR longer than the ones presented in Table 2 but with no significant differences between positions. Another important finding is that CF and WM accelerated more often compared with players in the other positions, which differs from a previous study with another Norwegian professional football club [ 24 ].
However, some similar trends were observed between these studies, with CB being the players who decelerated the least times compared with other playing positions. Furthermore, when comparing our data with results from previous research [ 4 , 24 , 25 ] we observed slightly lower values of acc counts in almost all the positions CB, FB, CM and WM. The inverse trend was observed in dec counts with all positions presenting higher values in our study, probably due to style of play.
A main finding of the present study refers to the number of turns observed across playing positions. They observed that midfielders performed significantly fewer turns during a match than defenders and strikers.
Our data show that CM did not perform significantly different compared to the other positions while WM performed more turns than CB. These differences may be caused by the different sampling technology used. Both turns, acceleration and deceleration activities add substantial load in addition to high-intensity running and must be taken into consideration when analysing physical demands of match-play.
It should be noted that different measurement technologies could cause the discrepancy in results between the present study and previous research [ 5 ]. Also, different playing styles, cultural and competitive contexts may account for differences observed. In summary, our data show that speed and distance measures only to some extent predict the physical demands of a football player and that these demands vary greatly across playing positions.
Taking into consideration the law of training specificity [ 33 ] and the idea that the physical loading of the training session should be individually designed to improve performance and avoid excess of fatigue and overtraining [ 34 ] the coaches need a clear view how different playing positions achieve load. The present results may provide useful and novel insight regarding positional differences in physical profiles of elite football players during match-play.
The positional differences in workload and work pattern need to be taken into consideration when designing and implementing training program cycles, according to the team's style of play.
Performing sprints in addition to small sided games must be taken into consideration when planning the trainings since small and medium sided games do not provide enough space to elicit these actions.
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