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Planning Training Workload in Football Using Small-Sided Games' Density

Authors:
  • Association sportive saint etienne
  • AS Saint Étienne

Abstract

Sangnier, S, Cotte, T, Brachet, O, Coquart, J, and Tourny, C. Planning training workload in football using small-sided games density. J Strength Cond Res XX(X): 000-000, 2018-To develop the physical qualities, the small-sided games' (SSGs) density may be essential in soccer. Small-sided games are games in which the pitch size, players' number, and rules are different to those for traditional soccer matches. The purpose was to assess the relation between training workload and SSGs' density. The 33 densities data (41 practice games and 3 full games) were analyzed through global positioning system (GPS) data collected from 25 professional soccer players (80.7 ± 7.0 kg; 1.83 ± 0.05 m; 26.4 ± 4.9 years). From total distance, distance metabolic power, sprint distance, and acceleration distance, the data GPS were divided into 4 categories: endurance, power, speed, and strength. Statistical analysis compared the relation between GPS values and SSGs' densities, and 3 methods were applied to assess models (R-squared, root-mean-square error, and Akaike information criterion). The results suggest that all the GPS data match the player's essential athletic skills. They were all correlated with the game's density. Acceleration distance, deceleration distance, metabolic power, and total distance followed a logarithmic regression model, whereas distance and number of sprints follow a linear regression model. The research reveals options to monitor the training workload. Coaches could anticipate the load resulting from the SSGs and adjust the field size to the players' number. Taking into account the field size during SSGs enables coaches to target the most favorable density for developing expected physical qualities. Calibrating intensity during SSGs would allow coaches to assess each athletic skill in the same conditions of intensity as in the competition.
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... Soccer is a predominantly tactical sport (Ade et al., 2016;Bradley and Ade, 2018) and the execution of actions related to information processing and perceptual-cognitive skills are particularly important when the objective is to resolve complex conflicts generated by the confrontation between two teams (Lex et al., 2015;Vestberg et al., 2012;Williams et al., 2012). At present, specific training has become the most utilized strategy by coaches to improve performance of athletes (Sangnier et al., 2019). Soccer-specific drills can maximize the most relevant adaptations (Casamichana and Castellano, 2010;Casamichana et al., 2012;Impellizzeri et al., 2004), while minimizing the cumulative effects of fatigue (Hill-Haas et al., 2010), monotony and training stress (Issurin, 2010). ...
... Modifications of the variables of space, game rules, and players' density have been widely used in soccer match simulations in recent years to achieve specific adaptations of soccer players (Asian- Clemente et al., 2021;Casamichana and Castellano, 2010;Köklü et al., 2020;Sangnier et al., 2019). Coaches have designed many training drills to improve the tactical behaviours of soccer players, approaching the conditional demands of the match. ...
... Modifications of playing space, game rules, and the number of players have been widely used in soccer match simulations in recent years to achieve adaptations of player-specific conditional capabilities (Asian- Clemente et al., 2021;Casamichana and Castellano, 2010;Köklü et al., 2020;Sangnier et al., 2019). In this sense, coaches have designed training drills to improve the tactical behaviours of players and, at the same time, have tried to make these exercises as similar as possible to the conditional requirements of soccer matches. ...
... Within a tactical periodization model, each training week looks to incorporate the four dimensions of the game (i.e., technical, tactical, physical, and psychological) in relation to the game model implemented. From a physical standpoint, the "strength days" within a tactical periodization model look to overload the acceleration and deceleration components within the training session using small-sided games of various player densities [51]. The coaches can design training sessions that create a smaller relative pitch area in relation to the number of players in any given space, to allow for short sharp movements to occur in relation to match demands [52]. ...
... The coaches can design training sessions that create a smaller relative pitch area in relation to the number of players in any given space, to allow for short sharp movements to occur in relation to match demands [52]. By further manipulating the work to rest ratios, and the duration of training exercises, coaches can create scenarios where the specific metrics highlighted in this research can be overloaded in relation to the specific phases of play and intensity [51]. This can provide a potential solution to mitigate the drop-off in the specified metrics within the first and second halves, however, further investigation is warranted. ...
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The aim of the study was to determine the between-match and between-halves match variability of various Global Positioning System (GPS) variables and metabolic power average (MPA) in competitions, based on the match results obtained by professional soccer players over a full season. Observations on individual match performance measures were undertaken on thirteen outfield players competing in the Iranian Premier League. The measures selected for analysis included total duration, accelerations in zones (AccZ1, 2, and 3), decelerations in zones (DecZ1, 2, and 3), and MPA collected by the Wearable Inertial Measurement Unit (WIMU). The GPS manufacturer set the thresholds for the variables analyzed as follows: AccZ1 (<2 m.s −2); AccZ2 (2 to 4 m.s −2); AccZ3 (>4 m.s −2); DecZ1 (<−2 m.s −2); DecZ2 (−2 to −4 m.s −2); DecZ3 (>−4 m.s −2). The results revealed significant differences between wins and draws for the duration of the match and draws compared to wins for the first-half duration (p ≤ 0.05; ES = 0.36 [−0.43,1.12]), (p ≤ 0.05; ES = −7.0 [−8.78, −4.78], respectively. There were significant differences on AccZ1 during the first-half between draws and defeats (p ≤ 0.05; ES = −0.43 [−1.32,0.46]), for AccZ3 in the second-half between draws and defeats (p ≤ 0.05; ES = 1.37 [0.48,2.25]). In addition, there were significant differences between wins and draws (p ≤ 0.05; ES = 0.22 [−0.62,1.10]), and wins and defeats for MPA in the first-half (p ≤ 0.05; ES = 0.34 [−0.65,1.22]). MPA showed further differences between draws and defeats in the second-half (p ≤ 0.05; ES = 0.57 [−0.22,1.35]). Descriptive analysis revealed differences between the first and second half for wins in AccZ2 (p = 0.005), DecZ2 (p = 0.029), and MPA (p = 0.048). In addition, draws showed significant differences between the first and second half in duration, AccZ1, AccZ2, and DecZ2 (p = 0.008), (p = 0.017), (p = 0.040), and (p = 0.037) respectively. Defeats showed differences between the first and second half in AccZ1, AccZ3, and MPA (p = 0.001), (p = 0.018), and (p = 0.003) respectively. In summary, the study reveals large variations between the match duration, accelerometer variables, and MPA both within and between matches. Regardless of the match outcome, the first half seems to produce greater outputs. The results should be considered when performing a half-time re-warm-up, as this may be an additional factor influencing the drop in the intensity markers in the second half in conjunction with factors such as fatigue, pacing strategies, and other contextual variables that may influence the results. Citation: Nobari, H.; Banoocy, N.K.; Oliveira, R.; Pérez-Gómez, J. Win, Draw, or Lose? Global Positioning System-Based Variables' Effect on the Match Outcome: A Full-Season Study on an Iranian Professional Soccer Team. Sensors 2021, 21, 5695.
... Such multidimensional effects of SSGs on players' acute responses make these games highly popular and frequently used by coaches for players of different age categories, experience, and competitive levels [10,11]. By changing task constraints during SSGs, coaches may directly amplify or inhibit the range of players' action possibilities within the context of practice [12], where manipulation of the playing area represents the variable which most influence players' external workload and technical performance, and consequently, decision making [13]. For this reason, how the body responds to the physical demands of the game-e.g., sprinting, running at different intensities-are of great interest for the literature [14]. ...
... It was previously observed that playing area dimensions influence the intensity of the game, the actions of the players, and the energy systems [13]. Large playing areas are associated with an increase in the intensity of exercise [41], while small playing areas appear to foster technical development [42]. ...
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This study sought to evaluate the training load in different age category soccer players associated with distinct pitch size small-sided games (SSGs). Twenty-four soccer players (eight in each age category: U-12, U-15, and U-23) performed three consecutive 4 vs. 4 ball possession SSGs (SSG1: 16 × 24 m; SSG2: 20 × 30 m; and SSG3: 24 × 36 m) all with 3 min duration and 3 min rest. Subjects carried ultra-wideband-based position-tracking system devices (WIMU PRO, RealTrack System). Total distance covered increased from SSG1 to SSG3 in all age categories and predominantly in running speeds below 12 km∙h−1. Moreover, distance covered in 12–18 km∙h−1 running speed was different in all performed SSGs and age categories. Residual or null values were observed at 18–21 km∙h−1 or above running speed, namely in U-12, the only age category where metabolic power and high metabolic load distance differences occurred throughout the performed SSGs. Edwards’ TRIMP differences between age categories was only observed in SSG2 (U-12 < U-15). The design of SSGs must consider that the training load of the players differs according to their age category and metabolic assessment should be considered in parallel to external load evaluation in SSGs. Wearable technology represents a fundamental support in soccer.
... The manipulation of playing area dimensions affects the intensity of the game, players' actions and the energy sources used (Sangnier et al., 2019): large playing areas are associated with greater distance covered (Silva et al., 2014) and an increase in the intensity of exercise (Halouani et al., 2014;Sarmento et al., 2018) in comparison with small ones. Small playing areas appear to foster technical development (Clemente et al., 2019;Sgrò et al., 2018). ...
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Small-sided games have been adopted as an integral part of soccer training, however, the use of task constraints by the coach and the action capabilities of both players and teams require further investigation. The aim of this investigation was to explore the age-category effects (under-11: U11, under-15: U15 and under-23: U23) on external training workloads (total distance covered, distance covered while walking, running and sprinting, number of sprints and maximum sprint speed), internal training load metrics (rate of perceived exertion, RPE) and tactical individual actions (passing number with dominant and non-dominant foot, and max passing speed) during 4 vs. 4 ball possession small-sided game constrained within three different playing areas (small: 20 x 15 m, medium: 25 x 20 m, and large: 30 x 25 m). Results revealed substantial differences (all p < .001) for each specific playing area observed across many of the external workload measures. For every area analysed, U23 players covered more distance walking, whereas U11 and U15 players covered more distances at higher intensities. Additionally, significant differences were found for the RPE (small playing area: p = .001; large playing area: p < .001) with U23 and U15 players showing higher scores compared with U11 ones. It can be concluded that a 4 vs. 4 ball possession small-sided game can provide different performance related stimuli to players, depending on age category and the playing surface area. Therefore, coaches and individuals involved with training and development of soccer players across all age groups should be aware of the key variables highlighted in this study before planning training drills.
... Only one study had a high risk of bias, with a score ≤4 (see Table S1). There were 88 observational studies (i.e., 94%), with 82 prospective cohort studies [41,[43][44][45][46][47][48][49]51,52,[54][55][56][59][60][61][86][87][88]90,[92][93][94][95][96][97][98][99][100][101][102][103][104][105][106][107][108][109][111][112][113][114][116][117][118][119][120][121][122][123][125][126][127][128][129][130][131][132][133][134], 3 retrospective cohort studies [85,110,115], 2 cross-sectional studies [50,62], and one diagnostic accuracy study [124]. There were six experimental studies (i.e., 6%), with three pre-post interventional studies [42,58,89], two cross-over randomized controlled trials [53,91], and one non-randomized trial [57] (see Table S2). ...
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Big Data has real value when the veracity of the collected data has been previously identified. However, data veracity for load monitoring in professional soccer players has not been analyzed yet. This systematic review aims to evaluate the current evidence from the scientific literature related to data veracity for load monitoring in professional soccer. Systematic searches through the PubMed, Scopus, and Web of Science databases were conducted for reports onthe data veracity of diverse load monitoring tools and the associated parameters used in professional soccer. Ninety-four studies were finally included in the review, with 39 different tools used and 578 associated parameters identified. The pooled sample consisted of 2066 footballers (95% male: 24 ± 3 years and 5% female: 24 ± 1 years). Seventy-three percent of these studies did not report veracity metrics for anyof the parameters from these tools. Thus, data veracity was found for 54% of tools and 23% of parameters. The current information will assist in the selection of the most appropriate tools and parameters to be used for load monitoring with traditional and Big Data approaches while identifying those still requiring the analysis of their veracity metrics or their improvement to acceptable veracity levels.
... The continuous manipulation of task constraints, such as the adaptation of space and number of players, according to a specific age and individuals' capabilities, allow for more effective development of individual and collective tactical, physical and technical skills (Gonçalves et al., 2017;Sampaio et al., 2014;Silva et al., 2015). For example, Sangnier et al. (2019) showed that the manipulation of playing dimensions in balanced game formats constrain the intensity of the game, players' actions and energy sources. Similarly, Olthof et al. (2018) demonstrated that different age groups deal differently with space available, revealing that the distance between players tend to increase as older the player becomes (Olthof et al., 2018). ...
Article
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This study aimed to examine the effects of age group (under-11, under-15, and under-23) on the external, internal workloads, and tactical individual actions when playing 4v2, 4v4, and 4v6 ball possession small-sided soccer games. Data were analysed separately under the opponent perspective (4vX) and by the cooperation perspective, according to teammates (4v2+X). For all opponent formats, statistical differences were found for walking, with older age groups covering longer distances. Higher running distances were found in 4v4 game format for U11s, while U23s reported higher RPE scores in 4v4 and 4v6 formats. More passes were performed in 4v2 and 4v4 game formats for U11s and a higher maximum passing speed in 4v6 format for U15s and U23s. In the cooperation perspective, statistical differences were found for all external workload variables: U11s covered more distances while sprinting, whereas U23s walked more, perceiving the task as more intense. Similarly, U11s performed a higher amount of tactical individual actions also in every format. Younger players seem to benefit from a lower level of opposition to mature tactical individual actions, while older players can develop fast ball circulation in numerical inferiority. ARTICLE HISTORY
... 31 Therefore, evaluating the effort by means of metabolic power, could better inform the coach of the true "load" imposed by a given training session. 32 considering at the same time the effects accounted for acceleration and movement velocity, metabolic power may constitute an integrated measure of the aerobic and anaerobic game demands. The metabolic power is closely associated to acceleration and deceleration 5 but needs a minimum speed between 8-12 km·h -1 to reach high values. ...
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The aim of this study was to compare kinematics parameters among official matches and SSGs of an italian premier league soccer team. Eighteen elite professional male soccer players (4 central defenders, 4 wide defenders, 3 central midfielders, 3 box-to-box midfielders, 2 wingers and 2 strikers) took part in the study. Players were monitored during four months of full training (including pre-season and in-season) and over 26 matches (14 Serie A matches, 9 Europa League matches, and 3 friendly matches), from July 2017 until November 2017. The kinematic parameters during official matches and SSGs were evaluated through Video Match Analysis. The kinematic data analysis shows that the metabolic power, that constitutes an integrated measure of acceleration and velocity, fails to reflect at all what occurs during actual match-play. An increased attention should be place in planning SSGs during training to better reproduce actual match situations.
... 31 Therefore, evaluating the effort by means of metabolic power, could better inform the coach of the true "load" imposed by a given training session. 32 considering at the same time the effects accounted for acceleration and movement velocity, metabolic power may constitute an integrated measure of the aerobic and anaerobic game demands. The metabolic power is closely associated to acceleration and deceleration 5 but needs a minimum speed between 8-12 km·h -1 to reach high values. ...
Article
Background: The aim of this study was to compare kinematics parameters among official matches and SSGs of an Italian premier league soccer team. Methods: Eighteen elite professional male soccer players (4 central defenders, 4 wide defenders, 3 central midfielders, 3 box-to-box midfielders, 2 wingers and 2 strikers) took part in the study. Players were monitored during four months of full training (including pre-season and in-season) and over 26 matches (14 Serie A matches, 9 Europa League matches, and 3 friendly matches), from July 2017 until November 2017. The kinematic parameters during official matches and SSGs were evaluated through Video Match Analysis. Results: The kinematic data analysis shows that the metabolic power, that constitutes an integrated measure of acceleration and velocity, fails to reflect what occurs during actual matchplay. Conclusions: An increased attention should be place in planning SSGs during training to better reproduce actual match situations.
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Background Wearable tracking devices are commonly utilised to quantify the external acceleration load of team sport athletes during training and competition. The ability to accelerate is an important attribute for athletes in many team sports. However, there are many different acceleration metrics that exist in team sport research. This review aimed to provide researchers and practitioners with a clear reporting framework on acceleration variables by outlining the different metrics and calculation processes that have been adopted to quantify acceleration loads in team sport research. Methods A systematic review of three electronic databases (CINAHL, MEDLINE, SPORTDiscus), was performed to identify peer-reviewed studies that published external acceleration load in elite team sports during training and/or competition. Articles published between January 2010 and April 2020 were identified using Boolean search phrases in relation to team sports (population), acceleration/deceleration (comparators), and competition and/or training (outcome). The included studies were required to present external acceleration and/or deceleration load (of any magnitude) from able-bodied athletes (mean age ≥ 18 years) via wearable technologies. Results A total of 124 research articles qualified for inclusion. In total, 113/124 studies utilised GPS/GNSS technology to outline the external acceleration load of athletes. Count-based metrics of acceleration were predominant of all metrics in this review (72%). There was a lack of information surrounding the calculation process of acceleration with 13% of studies specifying the filter used in the processing of athlete data, whilst 32% outlined the minimum effort duration (MED). Markers of GPS/GNSS data quality, including horizontal dilution of precision (HDOP) and the average number of satellites connected, were outlined in 24% and 27% of studies respectively. Conclusions Team sport research has predominantly quantified external acceleration load in training and competition with count-based metrics. Despite the influence of data filtering processes and MEDs upon acceleration, this information is largely omitted from team sport research. Future research that outlines acceleration load should present filtering processes, MEDs, HDOP, and the number of connected satellites. For GPS/GNSS systems, satellite planning tools should document evidence of available satellites for data collection to analyse tracking device performance. The development of a consistent acceleration filtering method should be established to promote consistency in the research of external athlete acceleration loads.
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