A mini-review of youth soccer match-play simulations

Mohammad Nor Aliff Bin Nordin; Muhamad Hamdan; Hosni Hasan; Mashidee Sulaiman; Sapto Adi; Raja Mohammed Firhad Raja Azidin

doi:10.4103/mohe.mohe_34_22

REVIEW ARTICLE

Year : 2023 | Volume : 12 | Issue : 1 | Page : 1-7

A mini-review of youth soccer match-play simulations

Mohammad Nor Aliff Bin Nordin¹, Muhamad Hamdan¹, Hosni Hasan², Mashidee Sulaiman³, Sapto Adi⁴, Raja Mohammed Firhad Raja Azidin⁵
¹ Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia
² Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia; Fakultas Ilmu Keolahragaan, Universitas Negeri Malang, Malang, Java, Indonesia; Sports Engineering and Artificial Intelligence Center, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia
³ Selangor Football Club, Red Giant Sdn Bhd, Shah Alam, Selangor, Malaysia
⁴ Fakultas Ilmu Keolahragaan, Universitas Negeri Malang, Malang, Java, Indonesia
⁵ Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia; Fakultas Ilmu Keolahragaan, Universitas Negeri Malang, Malang, Java, Indonesia; Sports Engineering and Artificial Intelligence Center, Universiti Teknologi MARA; Selangor Football Club, Red Giant Sdn Bhd, Shah Alam, Selangor, Malaysia

Date of Submission	04-Dec-2022
Date of Decision	12-Apr-2023
Date of Acceptance	19-Apr-2023
Date of Web Publication	27-Jun-2023

Correspondence Address:
Raja Mohammed Firhad Raja Azidin
Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia; Fakultas Ilmu Keolahragaan, Universitas Negeri Malang, Malang, Java, Indonesia; Sports Engineering and Artificial Intelligence Center, Universiti Teknologi MARA; Selangor Football Club, Red Giant Sdn Bhd, Shah Alam, Selangor, Malaysia

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/mohe.mohe_34_22

Abstract

The physical demands of football during match play have been observed, investigated and mimicked in a more controlled laboratory setting through a number of studies meant to resemble the activity of an actual soccer match. However, there have been variations in the simulation's design across studies. This mini-review aims to assemble and align various protocols in simulating youth soccer match play in order to identify and assess the viability of combining numerous simulations into various research in the sport. This article is the first narrative review to discuss numerous protocols used in research towards reproducing youth soccer match-play demands in a laboratory-controlled environment.

Keywords: Match play, soccer, youth

How to cite this article:
Nordin MN, Hamdan M, Hasan H, Sulaiman M, Adi S, Raja Azidin RM. A mini-review of youth soccer match-play simulations. Malays J Mov Health Exerc 2023;12:1-7

How to cite this URL:
Nordin MN, Hamdan M, Hasan H, Sulaiman M, Adi S, Raja Azidin RM. A mini-review of youth soccer match-play simulations. Malays J Mov Health Exerc [serial online] 2023 [cited 2023 Sep 25];12:1-7. Available from: http://www.mohejournal.org/text.asp?2023/12/1/1/379848

Introduction

Soccer simulation protocols aim to replicate movement patterns and physiological demands of match play (Russell et al., 2011; Thatcher and Batterham, 2004). Free-running intermittent exercise simulation protocols are designed to simulate the activity pattern characteristics of soccer; however, several factors, such as the omission of game-specific skills (Russell et al., 2011), and the use of a non-grass surface, might reduce the ecological validity of these protocols (Russell et al., 2011). As such, modified versions of protocols have been implemented to investigate soccer-specific skills (Foskett et al., 2009).

The motion demands of competitive soccer match play have been published extensively. The recent development of semi-automated systems has enabled researchers and practitioners to collect and manage large volumes of data, which has furthered our understanding of physical requirements. It is increasingly acknowledged that players perform within their physical capabilities (Drust et al., 2007) and that extrinsic factors, such as tactical approach, quality of opposition, match status and crowd support, create a large degree of inter-match variability in the physical data (Gregson et al., 2010). The myriad of factors that affect physical match performances makes it difficult for researchers to adopt these outcome measures to determine the efficacy of a given physical training intervention or ergogenic aid.

Consequently, researchers have developed laboratory- and field-based match-play simulations to enable them to examine the efficacy of nutritional, training and thermoregulatory interventions. Motorised treadmill (Drust et al., 2000), shuttle running (Nicholas et al., 2000) and field-based (Raja Azidin et al., 2015) simulations have generally required the participants to cover more total and high-speed running distances than those typically observed in match play (Williams et al., 2010). This can be attributed to their linear nature, which precludes non-uniform locomotor patterns, changes in direction and utility movements, all of which significantly increase the energetic cost (Drust et al., 2007). In addition, motorised treadmill protocols (Drust et al., 2000) have not always mimicked the high frequency of activity changes in match play (~1400); hence, changes in velocity from acceleration and deceleration movements are not inherent features of many simulations. This is a particularly important omission since players engage in these movements frequently and they are also more energetically demanding than constant velocity running (Osgnach et al., 2010). Non-motorised treadmill simulations (Thatcher and Batterham, 2004) have been more successful as players are required to perform acceleration and deceleration actions.

However, the resistance of the treadmill belt allows only 80% of the player's peak velocity to be achieved during sprint efforts, and the utility movements are absent in non-motorised treadmill simulation; hence, the mechanical demands are not indicative of match play. In order to determine and assess the feasibility of incorporating various simulations into various studies in the sport, this review intends to assemble and align numerous soccer match-play simulations specifically for youth players.

Physical Demand in Youth Soccer

Youth male football players reach approximately 6.3 km (range: 4.4–8.1 km) distance per game, with 12% of the distance deriving from high-intensity activities (Rebelo et al., 2014). Previous research suggesting elite under-14 football players covered more total distance and high-intensity movements compared to sub-elite players (Waldron and Murphy, 2013). Research regarding physical match output and its correlation with selection or deselection in youth soccer is minimal. Running performance, including maximal sprints and high-intensity efforts, increases with age (Zhou et al., 2020). Accelerations are a key component of physical and sprint performance, but previous research reported that maximal accelerations are not always associated with a number of sprints. Varley et al. (2012) found that a number of accelerations were approximately eight times more than the number of sprints per game and that 85% of maximal accelerations do not reach high-intensity running thresholds. Acceleration and deceleration involve greater energetic cost compared to maintaining constant speed (Vanrenterghem et al., 2017), with accelerations contributing to 7%–10% of player load, and decelerations contributing 5%–7% (Dalen et al., 2016). According to Vigh-Larsen et al. (2018), under-19 youth players accelerated and decelerated significantly more than senior players, indicating that senior professionals are more selective about how often they use this parameter.

Reproducing The Demands of Youth Soccer Match Play in a Laboratory Setting

Limited simulations specifically designed for youth soccer have reproduced the mechanical and physiological responses to such intermittent activity (Harper et al., 2016; Thatcher and Batterham, 2004). These simulations, also known as fatigue protocols, were designed to replicate the activity patterns seen in actual matches. They have the advantage of enabling controlled experimental evaluations of the player's performance as well as precise control over speed and distance covered. Thatcher and Batterham (2004) demonstrated the comparability of physiological responses between individuals participating in actual match play and a non-motorised treadmill protocol. However, the lack of lateral and backward movements performed in unidirectional treadmill protocols limits the validity of this protocol. The Loughborough Intermittent Shuttle Test (LIST) was an intermittent exercise simulation that has been used to examine the effects of various ergogenic aids on exercise performance (Erith et al., 2006). The LIST consisted of 75 min of intermittent activity that was followed by a shuttle run to exhaustion. This free-running exercise simulation replicated the movement demands of soccer and was an improvement over earlier unidirectional treadmill-based protocol (e.g. Nevill et al., 1993). However, the omission of a half-time period and the lack of game-specific skills, some of which have been previously found to have an energy-consuming consequence (e.g. dribbling; Reilly and Ball, 1984), reduce the ecological validity of the LIST and may also compromise the integrity of the physiological strain imposed by this protocol when compared to actual match play. Due to several study inputs, including match-play time, activity profiles, task execution, physiological responses and player loading, fatigue protocols in soccer have altered and evolved.

Activity Profile

Soccer players' running activity profiles have been mostly identified and categorised as consisting of intermittently jogging, walking, sprinting, running or striding and occasionally moving backwards or sideways (Thatcher and Batterham, 2004). The intermittent activities are repeated continuously, stopping for an average of 44 static rest pauses (standing) at average nearly every 2 min (Reilly, 1997). According to Robinson and White (2005), these activities are carried out over the course of a 90-min match while superimposing various ball control actions, which, according to Reilly (1997), may be affected by the actions' irregular volume and density. According to match-play data from studies by Link and Hoernig (2017), players' actions during soccer matches may vary depending on their position on the field (for example, defenders, midfielders and forwards), as well as the teams' playing strategies (i.e. offensive and defensive). More recent simulations have modified earlier iterations of soccer match simulations in order to present a more accurate picture of youth soccer activities throughout the simulations (Nordin et al., 2020).

Protocol Duration

Soccer simulations, as was previously indicated, may enable time-savvy observations and evaluations or offer a temporal portrayal of how soccer match play may contribute to the observed changes. Simulation protocols introduced by Oliver et al. (2014) are conveniently needed to cause localised fatigue for physical performance evaluations. However, the focus of this review is on laboratory simulations that mimic the demands of youth soccer match play, with fatigue as a side consequence. For a single evaluation, these simulations typically take longer to complete. A normal soccer match lasts for 90 min total, divided into two 45-min halves and a 15-min halftime break. After 90 min of play, if the score is still tied, another 30 min is played before penalty shootouts are used to decide the winner. Researchers have seen this format to create simulations of at least one-half of a soccer match (Raja Azidin et al., 2015), while extra time procedures were added to the simulation to meet specific research goals, as demonstrated by Harper et al. (2016). The majority of simulations use a 15–20-min activity profile that is repeated several times to finish the 90-min simulated match play in order to account for these match-play lengths.

Important Parameters

In order to measure the demands placed on an athlete during match play in relation to the actual demands of the game, Reilly (2005) proposed that physiological responses to the activity (heart rate [HR], rating of perceived exertion, blood lactate and oxygen consumption (VO₂) may be used for insightful evaluation. When conducting assessments and fitness interventions, this information is frequently taken into consideration (Reilly and Brooks, 1986). These physiological measurements could be used to describe how intense the soccer match-play simulation was. Therefore, the majority of studies recorded at least two physiological reactions during their particular simulations to compare to actual match-play observations. A mean HR of 158 ± 4 beats per minute (bpm) could be seen amongst players throughout the course of a soccer match, according to a compilation of studies in league and friendly matches by Russell et al. (2011). According to Mohr et al. (2004), after increases in core body temperatures to as high as 38.7°C, players' oxygen consumption during soccer matches may be as high as 70% of their maximum oxygen uptake (VO₂ max), with players' body mass decreasing by about 2% as a result of fluid loss. [Table 1] summarises several selected studies which implemented soccer-specific match simulations on the youth soccer population.

Table 1: Summary of selected youth soccer match simulation protocol characteristics

Click here to view

The Features of Simulated Soccer Match-Play Protocols for Laboratory-Controlled Studies

Youth soccer match-play simulations have undoubtedly been developed to determine the utility movements necessary to replicate the features of soccer match-play activities. These movements are frequently multidirectional and incorporate high accelerations and decelerations throughout the simulation. There are two types of simulation that have been developed to replicate the characteristics of soccer match play. The treadmill-based protocol does not really mimic the ecological demands of soccer due to its linear, unidirectional running with motor-controlled accelerations and decelerations (Raja Azidin et al., 2015). On the other hand, overground requires greater space for various activities incorporated in the simulation to accommodate these demands. In addition, overground simulations have been demonstrated to produce a better representation of youth physiological (Russell et al., 2011) and physical (Harper et al., 2016) demands of actual soccer match play. Nevertheless, not all overground soccer match-play simulations meet certain ecological requirements, especially when it comes to individual ball actions and running distance.

There have been several soccer match simulations found and examined. According to Rebelo et al., 2014, youth male football players reach approximately 6.3 km (range: 4.4–8.1 km) distance per game, with 12% of the distance deriving from high-intensity activities which was identically replicated by Mendez-Villanueva et al. (2013). A lot of simulations included walking, striding and sprinting profiles that had to be finished while either maintaining a predetermined percentage of maximum oxygen uptake (VO₂ max), a constant HR or just covering a predetermined distance for a predetermined amount of time as instructed by audio cues. However, using audio cues to cover a distance creates a circumstance that satisfies the physiological and physical requirements of match play. Accurate physiological replication of the demands made during a soccer match simulation may be possible by tracking match-play simulations using physiological responses such as aerobic capacity and HR measurements (Barreira et al., 2017).

Protocol Selection Consideration

Several overground soccer match-play simulations have been extended to include ball-handling tasks such as passing, shooting, dribbling and heading a ball in order to increase the simulation's ecological validity such as the BOSS (Hamdan et al., 2020). These additions of ball actions were to reproduce movement patterns experienced in actual soccer matches (Stølen et al., 2005). The soccer-specific exercise protocol was designed in a spacious environment, such as a sports arena or an open field. This situation occurred as a result of the simulation course being set up as a series of brief soccer exercises that required the players to travel from station to station. Consequently, a big, open space becomes necessary. The SAFT90 (De Ste Croix et al., 2015), which was created over a 15-m course, does permit administration in smaller spaces or laboratories. This makes the SAFT90 more versatile and a more convenient protocol to be employed. However, despite being able to reproduce the physical and physiological demands of match play, SAFT90 lacked an ecological element of soccer match-play: ball-handling task.

Soccer Match-Play Simulation Ecological Validity

The SAFT90 has then served as the foundation for a number of innovations. Da Silva and Lovell (2020) reported improved external validity of the T-SAFT90 to undertake ecologically valid soccer research with the incorporation of ball-handling tasks such as passes, dribbles and shots on target. However, the total frequency of ball activities reported summed up to less than half of the reported 117–126 times in actual match play (Link and Hoernig, 2017). The youth soccer match simulation (YSMS⁹⁰) (Nordin et al., 2020) was a shorter variant (13 m) of the BOSS by Hamdan et al. (2020) which included ball-handling tasks ranging from running with a ball (dribbling), heading, short passes and shooting (or long passes, interchangeably) tasks. The design of the YSMS⁹⁰ was targeted to replicate the ecology of a youth soccer match play where players interact with the ball up to 120 times, covering a range between 120 and 286 m when in possession of the ball per person (Di Salvo et al., 2007).

Soccer Match-Play Alternative

To our knowledge at the time of the review, the closest youth soccer match simulation for controlled laboratory research may be YSMS⁹⁰. YSMS⁹⁰ may be a more resource-efficient way to mimic the demands of real soccer matches for laboratory studies specifically for the youth population. Several studies tried to simulate the demands of soccer matches by conducting simulated matches (Russell et al., 2012). These simulated matches are played in a way that mimics actual matches, which incorporate two teams of 11 players competing on the field with the full support of coaches and support teams. These scheduled matches would be more challenging in terms of preparation time and resources. Conversely, since data can be collected in groups during simulated matches, these investigations are ideal for examining physiological and metabolic traits. This allows for efficient data collection times.

Conclusion

This article has looked at a few soccer match-play simulations. To the best of our knowledge, this work is the first narrative review to include a range of research protocols used to replicate the demands of soccer match play in a laboratory-controlled environment. There are several important notes from this review: (i) it makes sense that a simulation would replicate the demands of soccer match play while also being safe, feasible and controllable to be used in laboratory-controlled studies given the potential utility of soccer match-play simulations for further understanding of the biological responses of athletes during matches and (ii) practical applications of simulated soccer match play includes using them as fatiguing protocols for soccer-specific technical assessment and return to play assessments.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

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