|
|
|
ABSTRACT |
The main aim of this study was to determine the physical demands of different small-sided ball possession games (SSBPGs) according to player field position and compare these demands in relation to the most demanding passages of play (MDP) in competitive matches. Global positioning system data were obtained from 25 football players (20.4 ± 2.1 yrs, 1.78 ± 0.66 m, 69.7 ± 6.1 kg) belonging to the reserve squad of a Spanish La Liga Club. Players were categorized according to positional groups; full back (FB), central defender (CD), midfielder (MF), wide midfielder (WMF) and forwards (FW). The variables analyzed were relativized to metres per minute (m·min-1): total distance covered (TD), TD at high speed (HSR; >19.8 km·h-1), TD at sprint (SPR; >25.2 km·h-1), the number of accelerations (ACC) and decelerations (DEC) at high intensity (> +/-3 m·s-2), the average metabolic power (AMP; W·kg-1) and the high metabolic load distance (HMLD; >25.5 W·kg-1). The MDP were analyzed using a rolling average method, where maximal values were calculated for 3 and 5 minutes to compare with SSBPGs using AMP as a criterion variable. The results were obtained from the SSBPGs relative to the MDP (expressed in %) for each player position. FB showed the greatest magnitude of overload in ACC/DEC according to the MDP in the two smaller SSBPGs formats (201-217%), whereas MF showed lower values (105-140%). The load expressed in relation to the MDP can be different depending on the format of the SSBPGs and the characteristics of playing position. These factors should be considered by the coaches when planning training. |
Key words:
Small-sided games, GPS, peak intensity, football
|
Key
Points
- It is necessary to plan specific intervention strategies (e.g., increase the relative dimensions per player while maintaining a high number of players per team) or use complementary exercises to balance the load in relation to the demands of the game.
- The values relative to minutes of practice showed differences between the positions, increasing when the SSBPGs were larger (7v7+3 and 8v8+3 formats).
- The playing positions reported different demands depending on the type of ball possession game.
|
Small-sided games (SSGs) are extensively used in football training with the aim of concurrently simulating a variety of technical and physical aspects of the sport (Hill-Haas et al., 2009). In this regard, the implementation of SSGs has been shown to be effective in developing aerobic and anaerobic endurance, agility and strength in players at different standards of play (Los Arcos et al., 2015; Owen et al., 2012). Among the vast array of football-specific tasks (e.g., SSGs, modified games, conditioned games, etc.) currently available, small-sided ball possession games (SSBPGs) are extensively used to develop combinative playing skills. In these drills, the generic aim is to conserve ball possession with no goals or goalkeepers involved, while the four moments of the game (i.e., offensive organization, defensive organization and both offensive and defensive transitions) are present (Winter and Pfeiffer, 2016). Moreover, the spatial structure of the team and tactical tasks associated with the different playing positions, although simplified in comparison to an 11 vs. 11 game, can be maintained. The idea that the physical demands of competition present large inter-player and intra-player variability is not new (Carling 2013; Di Salvo et al., 2007). One of the variables that can greatly influence a player's physical activity during a competitive match is the position they occupy on the pitch (Castellano et al., 2014; Di Salvo et al., 2007). Thus, it would appear desirable that training drills aiming to improve game-related physical performance effectively address these positional-specific demands observed during matches. In overall terms, SSGs typically present lower demands relating to high-speed running (HSR) and sprint actions, and greater acceleration-deceleration demands than competitive matches (Beenham et al., 2017; Casamichana et al., 2012; Dellal et al., 2012; Giménez et al., 2018). The magnitude of these differences increases when the number of players and/or pitch dimensions are reduced (Casamichana and Castellano, 2010; Hill-Haas et al., 2009). Recently, Lacome et al. (2017) compared competitive match demands with those imposed by different SSGs and modified games, considering the playing position of players in the competition. The main findings revealed that, when compared with the most demanding passages (MDP) of the competitive matches, there were substantial differences depending on positional role, with central defenders and midfielders being the most over-stimulated and under-stimulated during the SSGs compared to competition respectively. Despite the study by Lacome et al. (2017), the possible differences that SSGs might impose on the different playing positions remain largely unexplored. To date no comprehensive evaluation of the physical demands of SSBPGs in comparison with game demands and specific to each playing position has been conducted. Therefore, the aim of this study was to quantify the external training load that the different positions are exposed to during different SSBPGs when compared with the MDP of competitive matches.
Study designGlobal Positioning System (GPS) data were collected during the 2015-2016 competitive season to establish the position-specific demands of the competitive matches and the different SSBPGs. Demands were expressed in values relative to practice time (m·min-1 for example) and values relative to the most demanding passages of play (% of the MDP) in competitive football matches over a similar duration (3 or 5 minutes).
ParticipantsData were collected from 25 football players (20.4 ± 2.1 yrs, 1.78 ± 0.66 m, 69.7 ± 6.1 kg) belonging to the reserve squad of a Spanish La Liga Club. At the time of writing, the first team squad has been ranked among the top six in the last 10 seasons and ranked as the top team in the last three seasons according to official UEFA rankings. Players were grouped according to their playing position as central defenders (CD, n = 4), full backs (FB, n = 6), midfielders (MF, n = 3), wide midfielders (WMF, n = 5) and forwards (FW, n = 7). Data arose as a condition of the players’ employment whereby they were assessed daily and thus no authorization was required from an institutional ethics committee (Carling et al., 2016; Lacome et al., 2017). Nevertheless, this study conformed to the Declaration of Helsinki and players provided informed consent before participating.
Competitive matchesThirty-seven competitive matches in the 2015-2016 season were included in the analysis (13 wins, 15 losses, 9 draws, final league position 11th). The team systematically played in a 1-4-3-3 formation with a goalkeeper, four defenders (two FBs and two CDs), three midfielders (a MF and two WMFs) and three FWs. Goalkeepers and players with fewer than six records were not included in the analysis. Only data from players who completed the full match were analyzed. A total of 227 individual GPS files from match data on reserve team players belonging to a professional male football team were collected, with this distribution per position: CD = 42, FB = 60, MF= 40, WMF = 34, and FW = 51 GPS files.
Small-sided ball possession gamesThe SSBPGs were structured according to the position of the player in the game system (wide players occupied the positions closest to the narrow side line and MF and WMF occupied the inner positions). The main offensive objective of the positional games was to maintain possession of the ball in superiority with three jokers (Jk). Quick pressure after losing ball possession was the main defensive tactical concept. The characteristics of each of the SSBPGs analyzed in the current study were as follows (Figure 1):
- 4v4+3: four against four players plus three Jks. Duration: 02:48±00:37 min. Dimensions: 13 x 17 m, surface area per player: 21.0 m2; one of the Jks is located inside and the other two Jks on the sides of the playing area, which creates an overload of 7 vs. 4 in the possession phase.
- 5v5+3: five against five plus three Jks. Duration: 03:48±00:43 min. Dimensions: 25 x 20 m, surface area per player: 38.5 m2; one of the Jks is located inside and the other two Jks on the sides of the playing area, which creates an overload of 8 vs. 5 in the possession phase.
- 7v7+3: seven against seven plus three Jks. Duration: 05:18±00:40 min. Dimensions: 29 x 36 m, surface area per player: 61.4 m2; one of the Jks (always a MF) is located inside and the other two Jks (always a CD and FW) on the sides of the playing area, which creates an overload of 10 vs. 7 in the possession phase.
- 8v8+3: it is eight against eight plus three Jks. Duration: 05:23±00:37 min. Dimensions: 40 x 35 m, surface area per player: 73.7 m2; one of the Jks is located inside and the other two Jks on the sides of the playing area, which creates an overload of 11 vs. 8 in the possession phase.
Variables and MDP of the gamesThe variables recorded were relativized to metres per minute (m·min-1): the distance covered (TD), distance covered at high speed running (HSR: >19.8 km·h-1, m·min-1), distance covered in sprinting (SPR: >25.2 km·h-1, m·min-1), the number of high intensity accelerations and decelerations (ACC/DEC: >3 m·s-2, n·min-1), the high metabolic load distance (HMLD; >25.5 W·kg-1, m·min-1), and the average metabolic power (AMP: W·kg-1). The intensity thresholds used were the same as those employed in previous studies (Osgnach et al., 2010; Owen et al., 2017; Stevens et al., 2017; Tierney et al., 2016). ACC/DEC in the STATSports software was calculated from the differentiated GPS Doppler speed; for an ACC/DEC to register it had to have a minimum duration of 0.5 seconds and a minimum magnitude of 0.5 m·s-2 (Varley et al., 2017). The AMP variable was used as a variable criterion to estimate the MDP of the four training game formats and competitive matches. AMP is calculated from an estimation of the energy expenditure by players associated with constant and intermittent activity (di Pampero et al., 2005; Osgnach et al., 2010). Although there are some deficiencies when there is no activity after a player’s effort, the inclusion of both dimensions, velocities and ACC/DEC, is considered a valid reference to estimate the load for a player over a given period. The moving average duration method was used for the AMP variable using two different durations, 3 and 5 min., only in competitive matches. As a result, for each individual match the period with the highest AMP values was selected and analyzed together with the rest of the variables. After that, the intensity of the SSBPGs was expressed both in absolute values (m·min-1 for example) and in relative values (%) according to the MDP of the competitive football matches. The 4v4+3 and 5v5+3 were relativized to the values obtained in the MDP of the competitive matches with the 3-min. time window, while the 7v7+3 and 8v8+3 were relativized through comparison with the 5-min. time window.
ProcedureThe activity profile of players was monitored during each training game format and competitive match using 10 Hz GPS units (Viper Pod, 50 g, 88 x 33 mm, STATSports Viper, Northern Ireland) that have been employed in previous studies (Bowen et al. 2017; Fox et al., 2017). The accuracy of these devices has been investigated, with a 2.53 ± 6.03% estimation error in distance covered and accuracy (%) improving as the distance covered increases and the speed of movement decreases (Beato et al., 2016). The GPS model used in this study was worn in a vest designed for this purpose inside a mini pocket positioned in the centre of the upper back, just above the shoulder blades, thus not affecting the mobility of the upper limbs and torso. Upon completion of each training session and competitive match, the GPS data were extracted using the appropriate proprietary software (Viper, STATSports, Northern Ireland). This type of system has previously been shown to provide valid and reliable estimates of instantaneous and constant velocity movements during linear, multidirectional and football-specific activities (Anderson et al., 2016). The number of records for each SSBPG and position is shown in Table 1. The SSPBGs were performed on a natural grass surface and the ball was always available by prompt replacement when kicked out with the aim of maximizing effective playing time (Casamichana and Castellano, 2010). The demands of the SSBPGs were studied according to the position of the players during competition. Data from Jk and Gk were not included in the analysis. In the SSBPG analysis, the pauses between repetitions were excluded in order to compare these with the more intense periods of the match (MDP). STATSports software (version 1.2) was then used for the computation of a moving average over the AMP variable for competitive matches using two different time windows of 3 and 5 min. As a result, for each competitive match maximum values using the AMP variable were calculated for each of the two moving average durations. These two different durations were analyzed because they correspond to the usual duration of the SSBPGs in the team studied. Descriptive statistics and analysis were then calculated based on positions of play. These data were then averaged across all observations per position for between-group analysis.
Statistical analysisThe data are presented as means and standard deviations (mean ± SD). The homogeneity of variances was examined by means of Levene’s test. The presence of significant differences was determined by means of a 2-tailed repeated-measures analysis of variance applied to each of the dependent variables in relation to player position (CD, FB, MF, WMF and FW). Whenever a significant difference was found, a post hoc Bonferroni’s test was used, whereas a Dunnett’s T3 post hoc test was applied when the variances were not homogeneous. All the statistical analysis was performed using SPSS 16.0 (SPSS Inc., Illinois, USA) for Windows, with significance being set at p<0.05. Effect sizes (ES) were also calculated to determine meaningful differences with magnitudes classified as (Batterham and Hopkins, 2006): trivial (<0.2), small (>0.2-0.6), moderate (>0.6-1.2), large (>1.2-2.0) and very large (>2.0-4.0).
Figure 2 shows the average (all positions pooled) SSBPG intensity relative values per minute. As the SSBPGs dimensions increased, TD (ES: 0.0—1.6), HMLD (ES: 0.1—1.0) and AMP (ES: 0.1—1.2) increased significantly while ACC (ES: 0.1—1.1) and DEC (ES: 0.1—0.9) were significantly reduced. Table 2 displays the relative values per minute obtained for the four SSBPGs, differentiating the player positions on the field (CD, FW, MF, WMF, and FW). Figure 3 shows the average (all positions pooled) SSBPG intensity relative to the MDP of the match-play expressed as a percentage (%). Table 3 displays the results of the SSBPGs relative to the MDP (expressed as a %) for each player position. The variables ACC and DEC showed significantly greater values (i.e., >100% of MDP) in the SSBPGs format 4v4+3 (AVG: 172/168%) and 8v8+3 (AVG: 145/138%). Among the different playing positions, FBs showed the greatest magnitude of overload according to the MDP in the two smaller SSBPGs formats in the ACC variable during 4v4+3 (201.6 %), 5v5+3 (217.5%) and the DEC variable during 4v4+3 (213.5%) and 5v5+3 (208.2%), while MF presented the lowest overload in the mechanical variables during 4v4+3 (115.2 %), 5v5+3 (138.3%) and the DEC variable during 4v4+3 (105.3%) and 5v5+3 (140.4%). HSR and SPR showed the lowest demand in comparison with the MDP during 5v5+3 (4.1%) and 7v7+3 (11.6%).
The aim of this study was to quantify the external training load according to the playing positions of players belonging to an elite soccer team during different SSBPGs. To our knowledge this is the first study to analyze the locomotor (e.g., TD, HSR and SPR) and mechanical (e.g., ACC and DEC) intensity of SSPBGs, considering positional player demands and comparing them in relation to the MDP. The main findings were: 1) irrespective of game format (i.e., size and number of players) and time-window (3 or 5 min.), the density of ACC and DEC variables showed the greatest degree of overload (>100% of the MDP); 2) in contrast, HSR metrics showed the lowest demand (<12% of the MDP), with practically no SPR demand in any SSBPG; 3) despite an overload in the mechanical variables and an underload in the locomotor dimensions in relation to match demands, player position dependent differences were observed; and, 4) all player positions showed intensity and global load metrics (e.g., AMP and HMLD) largely superior to the game demands. In contrast, the MF position showed the least demanding compared to other field positions. In competition, playing position has been shown to impact the overall physical demands (Di Salvo et al., 2007) and also the MDP in match-play (Delaney et al., 2017). In this study, every game format resulted in marked between-position differences in relative overload in most locomotor performance with the exception of HSR and SPR (see Table 3 and Figure 3). It is worth mentioning that sprint distance in these drills was almost non-existent for all the playing positions and all the formats studied. Similar to previous studies investigating non-position dependent training responses to SSG (Castellano and Casamichana, 2013; Hill-Haas et al., 2009; Lacome et al., 2017), there was an increase in TD and HSR as the size of the playing area of the SSPBGs drills increased in both relative (m2 per player) and absolute (e.g., pitch dimensions) values, and this impacted HMLD and AMP. In this regard, it seems obvious that players require sufficient pitch dimensions and acceleration time to reach high-speed (>19.8 km·h-1) and / or sprint (>25.2 km·h-1) speed thresholds (Delaney et al., 2017). In contrast, the number of accelerations and decelerations were greater in the smaller game formats compared with the drills including more players (7v7+3 and 8v8+3). Regarding the comparison across player positions, significant differences were observed; in particular FW was the position with lowest load in this type of game format in relation to WMF and FB. As the playing space became larger and included more players, these differences increased. Demands were highest in WMF in this type of playing situation overall with respect to CD and FW positions. Furthermore, training drills that take into account playing position should, in theory, better mimic individual match demands and therefore result in more specific training stimuli. Comparing training drill demands with the MDP of competitive matches, in addition to average values, can be useful in understanding the magnitude of the overload at the near-maximal intensities a player is subjected to during football-specific training drills. That is, when drill data is expressed as a % of the MDP during the match and values obtained exceed 100%, it means that match demands have been exceeded (overload). This training aspect (i.e., magnitude of the overload) is pivotal to the management of training load since systematic repetition over time could lead to an over- or under-stimulation with implications for performance (Jaspers et al., 2017) and for player health, where both situations might increase the risk of injury (Malone et al., 2017). In this study, the activity demands expressed as a % of the MDP were position-dependent (see Table 3). When the demands of the different SSPBGs are examined according to the % of the MDP, results indicate that there is an under-solicitation in TD, AMP, HMLD and especially in HSR and SPR. As mentioned above, in this study, the results showed that all the variables approached 100% of the MDP as the SSBPGs increased in size and number of players. Thus, the differences below in TD, HSD and SPR and above in ACC and DEC are lower in the larger formats (7v7+3 and 8v8+3) while the differences increase in the smaller formats (4v4+3 and 5v5+3). Lacome et al. (2017) also reported that as the reduced game format increased, demands were more similar to the MDP demands in the game. Although the ACC and DEC values exceed those obtained in the MDP of the matches, one needs to keep in mind that the criterion variable selected for determining the MDP of the matches was AMP. Therefore, the values obtained for ACC and DEC in the MDP of the matches would be higher if these variables had been used directly as criteria to establish the MDP. CDs and FBs reported significantly higher values for ACC and FBs also in DEC in small SSPBGs (4v4+3 and 5v5+3) compared to in the other two game formats (7v7+3 and 8v8+3). The MDP for CDs were significantly lower compared to other positions which means that although they did not cover greater distances (in metres), they were subjected to greater loads than other playing positions, such as for example FWs. MFs presented a significantly lower value for HMLD than CDs in all the SSPBGs studied. Furthermore, they reported low values for AMP, especially in the SSPBGs with fewer players. Regarding ACCand DEC it should be noted that full backs reported significantly higher values than MFs and FWs in the small SSPBGs. As described by Lacome et al. (2017), the results suggested the need to incorporate training drills that replicate and perhaps exceed the demands of the MDP in match-play. Based on the results obtained, the high-speed and sprint displacement actions are the most under stimulated with the studied SSPBGs. Therefore, other drills should be included in training dynamics to stimulate the HSR and SPR of players’ actions. Perhaps including some type of work such as HIIT might be useful to exceed the values obtained in the MDP in match-play in variables referring to TD or especially HSR (Lacome et al., 2017), since in our study SSPBGs do not manage to replicate these demands. Limitations in the present study included the unability to confirm the number of satellites per each data collection which may have led to small errors in the positional data. Furthermore, only physical and external load demands were recorded via GPS. Inclusion of internal load variables (i.e., heart rate-based variables) could give additional information about player responses. In future studies it would be useful to use the same SSPBGs but with larger playing surfaces for the same number of players, enforce game rules that favour or limit the number of contacts with the ball or use a different game space other than a rectangular pitch in order to confirm the results of this report.
Implications for football trainingThe small SSBPGs, 4v4+3 and 5v5+3, can be used to moderately overload mechanical variables (ACC and DEC), while 7v7+3 and 8v8+3 formats can be used to increase the values in the TD and HMLD variables. In addition, all of the SSBPGs that were designed with relative dimensions per player of less than 75 m2 failed to stimulate HSR and SPR variables. It is necessary to plan specific intervention strategies (e.g., increase the relative dimensions per player while maintaining a high number of players per team) or complementary exercises to balance the load in relation to the demands of the game. In the majority of the variables the values relative to minutes of practice showed differences between the positions, increasing when the SSBPGs were larger. However, when values were considered in relative terms to the % of the MDP, these differences decreased, especially in the larger formats. Analysis acrossplaying positions reported different demands depending on the type of game format. For MFs these types of tasks were less demanding than for the rest of the positions. In addition, in the 4v4+3 and 5v5+3 game formats, FB was the position reporting the highest demands compared to the MDP in the mechanical variables (>200%), while MFs did not exceed 50% in mechanical load compared to its MDP.
This study provides useful information for coaching staff on the impact of SSBPGs on physical load, considering positional differences in relation to the MDP of competitive match play. Based on these results, it may be necessary to include varied training situations to overload the player during the training process. Distance, distance covered at high speed and distance covered when sprinting are the variables that have the lowest MDP percentage while performing the SSBPGs studied. Hence it may be necessary to design other types of tasks where these variables can be stimulated or complemented with other activities where they can be performed.
ACKNOWLEDGEMENTS |
The experiments comply with the current laws of the country in which they were performed. The authors have no conflict of interest to declare. |
|
AUTHOR BIOGRAPHY |
![Journal of Sports Science and Medicine](volume19/iss1/images/jssm-19-1-g004.jpg) |
Andrés Martín-García |
Employment: Fitness Coach FC Barcelona, FC Barcelona Sports Performance Department. |
Degree: PhD student |
Research interests: Training Load, Team Sports, Prevention Injury, Strength & Conditioning |
E-mail: andres.martin@fcbarcelona.cat |
|
![Journal of Sports Science and Medicine](volume19/iss1/images/jssm-19-1-g005.jpg) |
Julen Castellano |
Employment: Professor at Basque Country University (UPV-EHU), Spain |
Degree: PhD in Sport Science |
Research interests: Performance analysis in team sports; Methodology in Behavioural Sciences. |
E-mail: julen.castellano@ehu.es |
|
![Journal of Sports Science and Medicine](volume19/iss1/images/jssm-19-1-g006.jpg) |
Alberto Méndez Villanueva |
Employment: Head of Fitness. Qatar Football Association |
Degree: PhD in Sport Science |
Research interests: Intermittent sports physiology, physical fitness testing, strength and conditioning in football |
E-mail: amendezvillanueva@yahoo.com |
|
![Journal of Sports Science and Medicine](volume19/iss1/images/jssm-19-1-g007.jpg) |
Antonio Gómez-Díaz |
Employment: Fitness Coach FC Barcelona (1st team Football). Professor in Sport Science Murcia University. FC Barcelona Sports Performance Department. |
Degree: PhD, BSc |
Research interests: Training Load, Team Sports, Prevention Injury, Strength & Conditioning |
E-mail: antonio.gomez@fcbarcelona.cat |
|
![Journal of Sports Science and Medicine](volume19/iss1/images/jssm-19-1-g008.jpg) |
Francesc Cos |
Employment: High Performance Director New York City Football Club. Lecturer at Barcelona University |
Degree: PhD, Ms, Bs, PT |
Research interests: Strength & Conditioning, rehabilitation and return to play |
E-mail: fcos@gencat.cat |
|
![Journal of Sports Science and Medicine](volume19/iss1/images/jssm-19-1-g009.jpg) |
David Casamichana |
Employment: Professor in Faculty of Education and Food. Universidad Europea del Atlántico. Santander, Spain. Fitness Coach Real Sociedad. |
Degree: PhD in Sport Science |
Research interests: Soccer; Team analysis; Training load; Physiological development |
E-mail: davidcasamichana@gmail.com |
|
|
|
REFERENCES |
![Journal of Sports Science and Medicine](image/si.png) Akenhead R., Harley J.A., Tweddle S.P. (2016) Examining the external training load of an English Premier League football team with special reference to acceleration. The Journal of Strength & Conditioning Research 30, 2424-2432.
|
![Journal of Sports Science and Medicine](image/si.png) Anderson L., Orme P., Di Michele R., Close G., Morgans R., Drust B., Morton J.P. (2016) Quantification of training load during one-, two- and three-game week schedules in professional soccer players from the English Premier League: implications for carbohydrate periodization. Journal of Sports Science 34, 1250-1259.
|
![Journal of Sports Science and Medicine](image/si.png) Batterham A.M., Hopkins W.G. (2006) Making meaningful inferences about magnitudes. International Journal of Sports Physiology and Performance 1, 50-57.
|
![Journal of Sports Science and Medicine](image/si.png) Beato M., Bartolini D., Ghia G., Zamparo P. (2016) Accuracy of a 10 Hz GPS Unit in Measuring Shuttle Velocity Performed at Different Speeds and Distances (5–20 M). The Journal of Human Kinetics 54, 15-22.
|
![Journal of Sports Science and Medicine](image/si.png) Beenham M., Barron D.J., Fry J., Hurst H.H., Figueirdo A., Atkins S. (2017) A Comparison of GPS Workload Demands in Match Play and Small-Sided Games by the Positional Role in Youth Soccer. The Journal of Human Kinetics 22, 129-137.
|
![Journal of Sports Science and Medicine](image/si.png) Bowen L., Gross A.S., Gimpel M., Li F.X. (2017) Accumulated workloads and the acute: chronic workload ratio relate to injury risk in elite youth football players. British Journal of Sports Medicine 51, 452-459.
|
![Journal of Sports Science and Medicine](image/si.png) Bradley P.S., Noakes T.D. (2013) Match running performance fluctuations in elite soccer: indicative of fatigue, pacing or situational influences?. Journal of Sports Sciences 31, 1627-1638.
|
![Journal of Sports Science and Medicine](image/si.png) Brandes M., Heitmann A., Muller L. (2012) Physical responses of different small-sided games formats in elite youth soccer players. The Journal of Strength & Conditioning Research 26, 1353-1363.
|
![Journal of Sports Science and Medicine](image/si.png) Brown D.M., Dwyer D.B., Robertson S.J., Gastin P.B. (2016) Metabolic power method: Underestimation of energy expenditure in field-sport movements using a global positioning system tracking system. International Journal of Sports Physiology and Performance 11, 1067-1073.
|
![Journal of Sports Science and Medicine](image/si.png) Buchheit M., Manouvrier C., Cassirame J., Morin J.B. (2015) Monitoring locomotor load in soccer: is metabolic power, powerful. International Journal of Sports Medicine 36, 1149-1155.
|
![Journal of Sports Science and Medicine](image/si.png) Carling C (2013) Interpreting physical performance in professional soccer match-play: should we be more pragmatic in our approach?. Sports Medicine 43, 655-663.
|
![Journal of Sports Science and Medicine](image/si.png) Carling C., Bradley P., McCall A., Dupont G. (2016) Match-to-match variability in high-speed running activity in a professional soccer team. Journal of Sports Sciences 34, 2215-2223.
|
![Journal of Sports Science and Medicine](image/si.png) Casamichana D., Castellano J. (2010) Time-motion, heart rate, perceptual and motor behaviour demands in small-sides soccer games: Effects of pitch size. Journal of Sports Sciences 28, 1615-1623.
|
![Journal of Sports Science and Medicine](image/si.png) Casamichana D., Castellano J., Castagna C. (2012) Comparing the physical demands of friendly matches and small-sided games in semiprofessional soccer players. The Journal of Strength & Conditioning Research 26, 837-843.
|
![Journal of Sports Science and Medicine](image/si.png) Castellano J., Alvarez-Pastor D., Bradley P.S. (2014) Evaluation of research using computerised tracking systems (Amisco® and Prozone®) to analyse physical performance in elite soccer: A systematic review. Sports Medicine 44, 701-712.
|
![Journal of Sports Science and Medicine](image/si.png) Castellano J., Casamichana D. (2013) Differences in the number of accelerations between small-sided games and friendly matches in soccer. Journal of Sports Science & Medicine 12, 209-210.
|
![Journal of Sports Science and Medicine](image/si.png) Delaney J.A., Cummins C.J., Thornton H.R., Duthie G.M. (2018) Importance, Reliability, and Usefulness of Acceleration Measures in Team Sports. The Journal of Strength & Conditioning Research 32, 3485-3493.
|
![Journal of Sports Science and Medicine](image/si.png) Delaney J.A., Thornton H.R., Rowell A.E., Dascombe B.J., Aughey R.J., Duthie G.M. (2017) Modelling the decrement in running intensity within professional soccer players. Science and Medicine in Football 2, 86-92.
|
![Journal of Sports Science and Medicine](image/si.png) Dellal A., Owen A., Wong D.P., Krustrup P., van Exsel M., Mallo J. (2012) Technical and physical demands of small vs. large sided games in relation to playing position in elite soccer. Human Movement Science 31, 957-969.
|
![Journal of Sports Science and Medicine](image/si.png) di Prampero P.E., Fusi S., Sepulcri L., Morin J.B., Belli A., Antonutto G. (2005) Sprint running: a new energetic approach. Journal of Experimental Biology 208, 2809-2816.
|
![Journal of Sports Science and Medicine](image/si.png) Di Salvo V., Baron R., Tschan H., Montero F.C., Bachl N., Pigozzi F. (2007) Performance characteristics according to playing position in elite soccer. International Journal of Sports Medicine 28, 222-227.
|
![Journal of Sports Science and Medicine](image/si.png) Fox R., Patterson S.D., Waldron M. (2017) The relationship between heart rate recovery and temporary fatigue of kinematic and energetic indices among soccer players. Science and Medicine in Football 1, 132-138.
|
![Journal of Sports Science and Medicine](image/si.png) Giménez J.V., Del-Coso J., Leicht A.S., Gomez M.A. (2018) Comparison of the movement patterns between small-and large-side games training and competition in professional soccer players. The Journal of Sports Medicine and Physical Fitness 58, 1383-1389.
|
![Journal of Sports Science and Medicine](image/si.png) Hader K., Mendez-Villanueva A., Palazzi D., Ahmaidi S., Buchheit M. (2016) Metabolic power requirement of change of direction speed in young soccer players: not all is what it seems. PloS one 11, e0149839.
|
![Journal of Sports Science and Medicine](image/si.png) Halouani J., Chtourou H., Gabbett T., Chaouachi A., Chamari K. (2014) Small-sided games in team sports training: A brief review. The Journal of Strength & Conditioning Research 28, 3594-3618.
|
![Journal of Sports Science and Medicine](image/si.png) Hill-Haas S., Dawson B., Coutts A., Rowsell G. (2009) Physiological responses and time-motion characteristics of various small-sided soccer games in youth players. Journal of Sports Sciences 27, 1-8.
|
![Journal of Sports Science and Medicine](image/si.png) Hill-Haas S.V., Coutts A.J., Rowsell G.J., Dawson B. T. (2009) Generic versus small-sided game training in soccer. International Journal of Sports Medicine 30, 636-642.
|
![Journal of Sports Science and Medicine](image/si.png) Jaspers A., Brink M.S., Probst S.G., Frencken W.G., Helsen W.F. (2017) Relationships between training load indicators and training outcomes in professional soccer. Sports Medicine 47, 533-544.
|
![Journal of Sports Science and Medicine](image/si.png) Lacome M., Simpson B.M., Cholley Y., Lambert P., Buchheit M. (2017) Small-Sided Games in Elite Soccer: Does One Size Fits All?. International Journal of Sports Physiology and Performance 13, 1-24.
|
![Journal of Sports Science and Medicine](image/si.png) Los Arcos A., Vázquez J. S., Martín J., Lerga J., Sánchez F., Villagra F., Zulueta J. J. (2015) Effects of small-sided games vs. interval training in aerobic fitness and physical enjoyment in young elite soccer players. PloS one 10, e0137224.
|
![Journal of Sports Science and Medicine](image/si.png) Malone J.J., Lovell R., Varley M.C., Coutts A.J. (2017) Unpacking the Black Box: Applications and Considerations for Using GPS Devices in Sport. International Journal of Sports Physiology and Performance 12, S218-S226.
|
![Journal of Sports Science and Medicine](image/si.png) Malone S., Roe M., Doran D.A., Gabbett T.J., Collins K. (2017) High chronic training loads and exposure to bouts of maximal velocity running reduce injury risk in elite Gaelic football. Journal of Science and Medicine in Sports 20, 250-254.
|
![Journal of Sports Science and Medicine](image/si.png) Martín-García A., Díaz A.G., Bradley P.S., Morera F., Casamichana D. (2018) Quantification of a Professional Football Team's External Load Using a Microcycle Structure. The Journal of Strength & Conditioning Research 32, 3511-3518.
|
![Journal of Sports Science and Medicine](image/si.png) Osgnach C., Poser S., Bernardini R., Rinaldo R., Di Prampero P.E. (2010) Energy cost and metabolic power in elite soccer: a new match analysis approach. Medicine and Science in Sports and Exercise 42, 170-178.
|
![Journal of Sports Science and Medicine](image/si.png) Owen A.L., Djaoui L., Newton M., Malone S., Mendes B. (2017) A contemporary multi-modal mechanical approach to training monitoring in elite professional soccer. Science and Medicine in Football 1, 216-221.
|
![Journal of Sports Science and Medicine](image/si.png) Owen A.L., Wong D.P., Paul D., Dellal A. (2012) Effects of a periodized small-sided game training intervention on physical performance in elite professional soccer. The Journal of Strength & Conditioning Research 26, 2748-2754.
|
![Journal of Sports Science and Medicine](image/si.png) Stevens T.G., de Ruiter C.J., Twisk J.W., Savelsbergh G.J., Beek P.J. (2017) Quantification of in-season training load relative to match load in professional Dutch Eredivisie football players. Science and Medicine in Football 1, 117-125.
|
![Journal of Sports Science and Medicine](image/si.png) Tierney P.J., Young A., Clarke N.D., Duncan M.J. (2016) Match play demands of 11 versus 11 professional football using Global Positioning System tracking: Variations across common playing formations. Human Movement Science 49, 1-8.
|
![Journal of Sports Science and Medicine](image/si.png) Varley M.C., Jaspers A., Helsen W.F., Malone J.J. (2017) Methodological considerations when quantifying high-intensity efforts in team sport using global positioning system technology. International Journal of Sports Physiology and Performance 12, 1059-1068.
|
![Journal of Sports Science and Medicine](image/si.png) Winter C., Pfeiffer M. (2016) Tactical metrics that discriminate winning, drawing and losing teams in UEFA Euro 2012®. Journal of Sports Sciences 34, 486-492.
|
![Journal of Sports Science and Medicine](image/si.png) Winter E.M., Maughan RJ (2009) Requirements for ethics approvals. Journal of Sports Sciences 27, 985.
|
|
|
|
|
|
|