Does competition standard and player position influence the match-play physical demands of Australian elite youth male soccer players within a single squad?

Abstract

The purpose of this study was to investigate the influence of competition standard and player position on the physical demands of Australian elite youth male soccer players during match-play. Twenty-three elite youth male soccer players from the same Australian U17 National Centre of Excellence program were observed across 8 National Youth League (NYL) and 21 National Premier League (NPL) competition matches. Total (TD/min), low- (< 3.6 m/s), moderate- (3.6–5.0m/s) and high-speed (> 5.0 m/s) running distance, and the accelerations (Acc/min) (≥ 2.0 m/s²) and decelerations (Dec/min) (≤ −2.0 m/s²) were recorded using 15-Hz portable global positioning system tracking devices (GPSports, Canberra, Australia). An interaction was observed between competition standard and player position for TD/min (p = 0.003), HSRD/min (p = 0.007) and Acc/min (p = 0.037) indicating the influence that competition standard had on these variables varied according to player position. Furthermore, we report that Central Defenders (3.1%), External Attackers (4.2%) and Central Attackers (3.8%) performed more TD/min in NYL (professional development level) compared to NPL (semi-professional) match-play. Central Defenders (24.2%) and Central Attackers (17.0%) completed more HSRD/min in NYL (professional development level) compared to NPL (semi-professional) match-play. Central Defenders (47.8%), External Defenders (20.5%), Midfielders (18.5%) and External Attackers (32.3%) all performed more Acc/min in NPL (semi-professional) when compared to NYL (professional development level) match-play. The results of this study provide scientific basis to aid the match-preparation of Australian elite youth male soccer player’s transition to higher standards of soccer.

Keywords

Association football,global positioning system,performance analysis,time-motion analysis

Introduction

Quantifying the physical demands of elite youth male soccer players during match-play provides vital information for coaches and performance staff so that relevant training drills and game simulations can be constructed.¹ The application of wearable Global Positioning System (GPS) devices in soccer has helped characterise the physical demands of match-play while providing insight into the contextual variables that influence running performance.^2,3 The physical demands of match-play in soccer can be influenced by variables such as player age,⁴ competition standard,² team formation (e.g. 4-3-3, 4-4-2, 4-5-1)^2,5, player position,⁶ team rankings (e.g. 1st versus 4th)⁷ and player status (e.g. elite and sub-elite).⁸ As elite youth male soccer players can be subject to varying competition standards, data pertaining to the influence competition standard and player position in the context of elite youth male soccer players should be of interest to coaches and performance staff.^2,9,10

‘Elite’ soccer players are typically defined as team members of professional soccer clubs, competing in top national competition tiers or national representative teams.¹¹ Most research detailing the influence of competition standard on the physical demands of match-play has focused on elite senior male soccer teams,¹² with a recent increased attention in female¹³ and youth male players.⁹ To date, Bradley et al.¹² reported that senior players competing in English Championship (tier 2) and League 1 (tier 3) performed greater total distances and higher-intensity (> 5.5 m/s) running during match-play when compared to Premier League teams (tier 1). Similarly, Di Salvo et al.³ observed the physical demands of players in the English Premier (tier 1) and Championship (tier 2) across four seasons, reporting that Championship players (tier 2) covered a greater total match distance (11,102 ± 916 m) compared to Premier League players (tier 1) (10,746 ± 964 m).³ Championship (tier 2) players also completed more running at high speeds (> 5.5 m/s) (750 ± 222 m) compared to Premier League players (tier 1) (693 ± 214 m). However, despite these reported differences, the comparisons are between different player groups and thus inter-individual differences may substantially impact on any competition standard differences reported.

Other contextual factors investigated previously include the influence of player age, player status (defined as elite and sub-elite) and position during elite youth match-play.^4,9,10 Buchheit et al.⁴ analysed the physical demands of U13 to U18 elite youth male soccer academy players. Total distance, high-intensity running (3.6–4.4m/s) and sprinting (> 5.3 m/s) distances all increased incrementally with age.⁴ However, match durations were reduced for all age groups except the U18 category that competed using official 90-minute match durations.⁴ While this study provides contextual information, the evaluation of results is difficult given that the physical demands were reported in absolute terms rather than relative distance per minute. With longer match durations logically leading to higher running distances, it may be more intuitive to compare the relative distance per minute between age-groups.⁴ Player status (elite and sub-elite) has been found to influence the physical capabilities and physical demands of match-play.¹⁴ In elite and sub-elite U14 youth male soccer players, the elite youth players (115.7 ± 6.6 TD/min) covered greater total distances compared to sub-elite youth players (105.4 ± 7.7 TD/min).¹⁴ U14 elite youth players (14.5 ± 2.3 HIR/min) were also found to cover greater distances at high-intensity (3.6 m/s – 5.2 m/s) compared to their sub-elite (11.5 ± 3.7 HIR/min) compared to sub-elite youth players.¹⁴ Differences in physical demands reported between elite and sub-elite youth male soccer players could be due to variation in the anthropometric characteristics, physical capabilities, technical skills, and decision making ability^8,15 rather than the playing standard per se. Evidence suggests that elite youth male soccer players tend to have greater body mass, height and superior results in Yo-Yo Intermittent Recovery Test Level 2 (YYIR2) performance, plus 5 m and 30 m sprint tests when compared to sub-elite youth male soccer players.⁸ Furthermore, Keller et al.¹⁵ found that Australian elite youth male soccer players demonstrated superior technical and decision-making abilities when compared to sub-elite youth male soccer players.

The physical demands of competition match-play have been shown to vary according to player position.^4,6 For example, Abbot et al.⁶ analysed the physical demands of U23 elite youth male soccer academy players. The results found that Midfielders produced the highest total and acceleration distance when compared to all player positions (p < 0.001)⁶. Furthermore, Wide Defenders and Wide Attackers produced the greatest very-high speed running distances (p < 0.001), whilst Central Defenders produced the lowest.⁶ Although the influence of player position on the physical demands of match-play has been well documented, the influence and interaction of competition standard and player position on the physical demands of match-play is less understood.¹¹

Most elite soccer players begin their careers as professional players between the ages of 17 and 20 years.⁸ By this age it is widely accepted that players have proven capability in several positions and are ready to compete at the elite level.⁸ A unique feature of the Australian soccer player development pathway involves elite youth male soccer players competing in a youth (U21) professional development national competition (National Youth League, NYL) and an adult (senior) semi-professional state competition (National Premier League, NPL). Effectively, this creates a duel, segmented competition structure where elite youth male soccer players compete in the NYL from November to February and NPL from April to August within a 12-month period.¹¹ The teams competing in the NYL are comprised of full-time, elite players forming the basis of the youth (U21) teams of Australia’s top-flight professional club soccer competition (A-league). Alternatively, teams that compete in the NPL competition consist of part-time, sub-elite adult (senior) semi-professional teams from state regions. As such, information regarding the physical demands of a single academy cohort competing in a youth (U21) professional development national competition (e.g. NYL) and adult (senior) semi-professional state competition (e.g. NPL) is underrepresented in the literature. A systematic investigation detailing the influence of competition standard and player position for elite youth male players competing in a youth (U21) professional development (e.g. NYL) and adult (senior) semi-professional (e.g. NPL) competition is required in Australia and could provide scientific basis to develop effective training practices to successfully transition elite youth soccer players to senior elite match-play. Therefore, the purpose of this study was to determine the influence of competition standard and player positions on the physical demands of Australian elite youth male soccer players in match-play.

Methods

Study design

This study used a longitudinal observational design of a single cohort. Elite youth male soccer players from one team were observed across twenty-nine competition matches, consisting of 8 youth (U21) professional development National Youth League (NYL) and 21 adult (senior) semi-professional National Premier League (NPL) matches. Competition standard (NYL and NPL) and player position (Central Defenders, External Defenders, Midfielders, External Attackers and Central Attackers) were used as fixed factors, while repeated measures for each player in different matches were considered as random factors.

Participants

Twenty-three elite youth male soccer players from the same Australian U17 National Centre of Excellence program participated in this study. At the beginning of the study, the mean age of the players was 15.61 ± 0.75 years; height 173.41 ± 5.07 cm; body mass 65.15 ± 6.02 kg and YYIR2 680 ± 64 m. A standard training week consisted of 4–5 soccer sessions, 1–2 strength and conditioning sessions, 1–2 post-match contrast water immersion recovery sessions and 1–2 competition matches per week, in accordance with seasonal fixtures. Prior to the commencement of data collection, all participants, parents and legal guardians were informed of the investigation aims by verbal and written communication in addition to any potential risks before providing their written informed consent to participate. Participants were free to withdraw from the investigation at any time, without any repercussions. This study was conducted according to the requirements stipulated by the Declaration of Helsinki and approved by the relevant Institutional Human Research Ethics Committee.

Procedures

Twenty-nine competition matches, consisting of 8 youth (U21) professional development National Youth League (NYL) and 21 senior (adult) semi-professional National Premier League (NPL) matches were analysed for this study. Data were stratified according to player positions, including Central Defenders (4 players, n = 56 total match files), External Defenders (5 players, n = 56 total match files), Midfielders (6 players, n = 82 total match files), External Attackers (5 players, n = 54 total match files) and Central Attackers (3 players, n = 28 total match files). A total of 276 individual match files were collected. Each player competed in an average of 12 competition matches (range = 3–27 competition matches). Due to player development and availability, players may have featured in more than one playing position across NYL and NPL competitions, and their position was defined for each individual game accordingly. NYL competition matches were played throughout a three-month summer competition calendar (November – January), whilst NPL competition matches were played throughout an eight-month winter competition calendar period (March - October). The reference team utilised the same 4-3-3 formation and tactics in all observed matches. Matches were played on 100×70m field dimensions on a combination of natural and synthetic turf surfaces. Each match was 90 minutes in duration, separated into two 45-minute halves, with the addition of injury time determined by the match referee. All games were played under the same competition rules, limiting each team to three substitutions and a 15-minute break for half time. All competition matches were preceded by a 30-minute standardised warm up, consisting of short and long passing, small-sided games, shooting, short and intermediate length maximal sprint efforts, as well as dynamic stretching. Although GPS units were worn during the standardised warm up data were not analysed.

The physical demands of competition matches were captured using 15 Hz portable global positioning system (GPS) tracking devices (SPI HPU, GPSports, Canberra, Australia), and consisted of the following variables; total distance per minute (TD/min), low-speed (< 3.6 m/s) running distance per minute (LSRD/min), moderate-speed (3.6–5.0m/s) running distance per minute (MSRD/min), high-speed (> 5.0 m/s) running distance per minute (HSRD/min), number of acceleration efforts (≥ 2.0 m/s²) per minute (Acc/min), and deceleration efforts (≤ −2.0 m/s²) per minute (Dec/min). The velocity thresholds were chosen based on recommendations for elite youth male soccer players and are similar to those described in previous investigations.^4,14 Global Positioning devices were turned on 30 minutes before each competition game to ensure satellite connectivity. Devices were fitted inside a specific GPS unit garment positioned on the upper back of each player. To minimise the effect of inter-unit error, each player was allocated the same unit for the duration of the data collection period. During all competition matches 4 to 12 satellites were available for connectivity and signal transmission, satisfying the criteria for ideal positional detection.¹⁶ Horizontal dilution of precision values (HDOP) was not reported by the proprietary software (Team AMS, Canberra, Australia). Upon completion of each competition match, GPS data were extracted using proprietary software (Team AMS, Canberra, Australia). Each match file was processed to include only data captured during the match time, divided into first and second halves. The interunit reliability (expressed as a coefficient of variation) for the GPS devices has been reported as 1.4% for total distance, 3.2% for distance at speeds of 0 m/s to 2.0 m/s (walking), 7.8% for distance at speeds of 2.0 m/s to 5.9 m/s (jogging) and 4.8% for distance covered at speeds > 5.9 m/s (sprinting).¹⁷

Statistical analyses

Statistical analyses were conducted using R version 3.6.2.¹⁸ The lmer function from the lme4 package¹⁹ was used to conduct a General Linear Mixed Model to determine the influence of competition standard and player position (fixed factors) on the physical demands (TD/min, LSRD/min, MSRD/min, HSRD/min, Acc/min, Dec/min) of competition matches (dependent variables). Repeated measures for each player in different matches were considered as a random factor. Type II Wald F tests were conducted using the Anova function from the car package²⁰ to determine the significance of the interaction between competition standard and player position, and the main effects for competition standard (alpha level = 0.05). The assumptions of homoscedasticity and linearity were determined upon visual inspection of plots of the fitted values against the residuals.²¹ The assumption of normality was determined upon visual inspection of histograms and Q-Q plots of the residuals. Effects size statistics for competition standard (between NYL and NPL) for each player position were calculated by Cohen’s d, using the least squares means and the pooled standard deviation of the random effects to account for the structure of the General Linear Mixed Model.²² The effect sizes were interpreted as trivial: |d| = < 0.2, small: |d| = 0.2 – 0.49, moderate: |d| = 0.50 – 0.79 and large: |d| = ≥ 0.8.²² Least-squares means, least-squares mean differences and 95% confidence intervals were calculated using the ls_means function from the lmertest package.¹⁹

Results

The influence of competition standard and player position on the physical demands of match-play are outlined in Figures 1 and 2. Results from the General Linear Mixed Model demonstrated interactions between competition standard and player position for TD/min (p = 0.003), HSRD/min (p = 0.007) and the number of Acc/min (p = 0.037). The least-squares means, mean differences and 95% confidence intervals for the physical demands according to competition standard and player position are presented in Tables 1 to 5. The least-squares means, mean differences and 95% confidence intervals for the physical demands according to competition standard, not accounting for playing position are presented in Table 6.

Figure 1.

Physical demand characteristics for Total (a), Low- (b), Moderate- (c) and High-Speed (d) Distance per minute according to competition standard and playing position.

Figure 2.

Physical demand characteristics for the number of accelerations (a) and decelerations (b) per minute according to competition standard and playing position. CD: central defenders; ED: external defenders; MD: midfielders; EA: external attackers; CA: central attackers. * |d|: 0.2 – 0.49 small difference between NYL and NPL. ** |d| = 0.5 – 0.79 medium difference between NYL and NPL. *** |d| = ≥ 0.8 large difference between NYL and NPL.

Table 6.

Main effects for physical demand characteristics according to competition standard.

	Competition Standard
	NYL	NPL	Difference	Percent difference (%)	Effect size	d
TD/min	121.02 (118.60 – 123.45)	119.31 (117.31 – 121.30)	1.72 (1.28– 2.15)	1.4	Small	0.24
LSRD/min	84.00 (82.10 – 85.90)	85.37 (83.70 – 87.04)	–1.37 (–1.60 – –1.15)	–1.6	Small	0.27
MSRD/min	24.11 (22.61 – 25.62)	22.20 (20.88 – 23.51)	1.92 (1.72 – 2.11)	7.9	Small	0.47
HSRD/min	12.97 (12.09 – 13.85)	11.73 (11.01 – 12.44)	1.24 (1.07 – 1.41)	9.6	Small	0.47
Acc/min	0.63 (0.55 – 0.71)	0.76 (0.68 – 0.84)	–0.13 (–0.14 – –0.12)	–20.7	Medium	0.63
Dec/min	1.00 (0.90 – 1.10)	1.08 (0.98 – 1.18)	–0.08 (–0.08 – –0.07)	–7.6	Small	0.37

Data are presented as least-squares mean (95% CI).

Difference: Difference (95% CI) of the least squares means between NYL and NPL, relative to NYL.

Percent Difference: Percent Difference of the least squares means between NYL and NPL, relative to NYL.

Cohen’s d: trivial effect = < 0.2; small effect = 0.2 – 0.49; medium effect = 0.5 – 0.79; large effect = ≥ 0.8.

Table 1.

Physical demand characteristics of central defenders according to competition standard.

	Competition standard
Central defender	NYL	NPL	Difference	Percent difference (%)	Effect size	d
TD/min	114.70 (109.95 – 119.46)	111.10 (107.44 – 114.75)	3.61 (2.50 – 4.71)	3.1%	Medium	0.51
LSRD/min	81.30 (77.94 – 84.67)	81.98 (79.28 – 84.67)	–0.67 (–1.34– 0.00)	–0.8	Trivial	0.13
MSRD/min	21.96 (19.21 – 24.71)	20.36 (18.18 – 22.54)	1.60 (1.03– 2.17)	7.3	Small	0.39
HSRD/min	11.39 (9.64 – 13.15)	8.63 (7.30 – 9.97)	2.76 (2.34 – 3.18)	24.2	Large	1.05
Acc/min	0.45 (0.32 – 0.57)	0.66 (0.55 – 0.77)	–0.21 (–0.23 – –0.19)	–47.8	Large	1.04
Dec/min	0.86 (0.71 – 1.01)	0.94 (0.81 – 1.06)	–0.07 (–0.10 – 0.05)	–8.7	Small	0.30

Data are presented as least-squares mean (95% CI).

Difference: Difference (95% CI) of the least squares means between NYL and NPL, relative to NYL.

Percent Difference: Percent Difference of the least squares means between NYL and NPL, relative to NYL.

Cohen’s d: trivial effect =< 0.2; small effect = 0.2 – 0.49; medium effect = 0.5 – 0.79; large effect = ≥ 0.8.

Table 5.

Physical demand characteristics of central attackers according to competition standard.

	Competition standard
Central attacker	NYL	NPL	Difference	Percent difference (%)	Effect size	d
TD/min	123.24 (117.30 – 129.17)	118.55 (114.38 – 122.73)	4.68 (2.92 – 6.45)	3.8	Medium	0.66
LSRD/min	84.98 (80.95 – 89.02)	85.43 (82.45 – 88.41)	–0.44 (–1.50 – 0.61)	–0.5	Trivial	0.09
MSRD/min	23.69 (20.35 – 27.02)	20.71 (18.28 – 23.14)	2.98 (2.07– 3.89)	12.6	Medium	0.73
HSRD/min	14.66 (12.45 – 16.87)	12.18 (10.64 – 13.71)	2.49 (1.82– 3.16)	17.0	Large	0.94
Acc/min	0.76 (0.61 – 0.90)	0.74 (0.62 – 0.85)	0.02 (–0.01 – 0.05)	2.7	Trivial	0.10
Dec/min	1.01 (0.85 – 1.18)	0.98 (0.85 – 1.12)	0.03 (0.00 – 0.06)	3.0	Trivial	0.15

Data are presented as least-squares mean (95% CI).

Difference: Difference (95% CI) of the least squares means between NYL and NPL, relative to NYL.

Percent Difference: Percent Difference of the least squares means between NYL and NPL, relative to NYL.

Cohen’s d: trivial effect = < 0.2; small effect = 0.2 – 0.49; medium effect = 0.5 – 0.79; large effect = ≥ 0.8.

There was no interaction between competition standard and player position for LSRD/min (p = 0.082), MSRD/min (p = 0.082) or Dec/min (p = 0.288), however there were significant main effects identified for competition standard for LSRD/min (p = 0.006), MSRD/min (p < 0.001), HSRD/min (p < 0.001), Acc/min (p < 0.001) and Dec/min (p < 0.001) (Table 6).

Discussion

This study sought to investigate the influence of competition standard and player position on the physical demands of Australian elite youth male soccer players during match-play. The results of this study contrast with previous investigations in elite senior male soccer players that reported the influence of competition standard on the physical demands of match-play. For example, Di Salvo et al.³ reported that elite senior male soccer players competing in the top division (Premier League) of the English domestic leagues exhibited lower total distance when compared to teams competing in the second (Championship) and third (League 1) competition divisions. Therefore, despite superior competition standard being previously reported to lessen the physical demands of match-play in top competition divisions,³ the results of this study indicate that higher competition standard may increase the physical demands exhibited by Australian elite youth male soccer players.

Throughout the 21 adult (senior) semi-professional NPL competition, the reference team won 85% of their matches. Conversely, within the youth (U21) professional development NYL competition analysed, the reference team was less successful, winning only 25% of their matches. Previous research has demonstrated that teams who retain the highest percentage of ball possession exhibit lower physical demands and have greater match success rate.²³ Furthermore, Central and External Defenders in elite German soccer were found to cover shorter distances at high speed running (≥ 4.0 m/s) in matches won as opposed to matches lost.²⁴ As such, ball-possession and match success may account for the greater TD/min (Figure 1(a)) and HSRD/min (Figure 1(d)) observed for Central Defenders, External Attackers and Central Attackers in NYL compared to NPL match-play. However, future investigations should incorporate win to loss ratios within their analysis to determine if the variance in the physical demands is attributed to competition standard rather than match outcome (i.e. won, draw, loss).

The greater TD/min (Figure 1(a)) and HSRD/min (Figure 1(d)) observed for Central Defenders, External and Central Attackers in NYL compared to NPL match-play could be attributed to the tactical role of each position. Competition standard encompasses aspects of technical and tactical skill proficiency, plus general player conditioning. Therefore, it seems logical that a more nuanced explanation is warranted. Central Defenders operate as the last line of defence, protecting against invasive runs from opposition attacking players.⁶ As the reference team was less successful in NYL than NPL, it is possible that Central Defenders spent greater periods of NYL compared to NPL match-play defending against opposition attacking players inside their own defensive half. The increased requirement to press against opposition attacking players may have led to an increased TD/min (3.1%) and HSRD/min (24.2%) in NYL match-play.

A similar rationalisation can be made for External and Central Attackers. Tactically, External Attackers compete in widespread, open areas of the field,⁶ whilst Central Attackers operate as the highest line of attack, in central congested areas often outnumbered against two opposing Central Defenders.⁶ As such, the increased TD/min (Figure 1(a)) and HSRD/min (Figure 1(d)), for External and Central Attackers could be attributed to a greater demand and number of pressing runs against opposition players in an attempt to win possession of the ball as a result of decreased ball-possession. A supposition represented by the decreased match-success in NYL match-play.

External Defenders performed more TD/min (4.7%) and HSRD/min (8.8%) in NPL relative to NYL match-play (Table 2). The results for External Defenders are similar to previous findings in elite senior male soccer players.^2,12 The modern tactical role of External Defenders in a 4-3-3 formation is to support both attacking and defensive situations, operating in wide, less congested areas of the field.⁶ As the reference team had increased match success in the NPL competition it is possible that External Defenders had a greater number of opportunities to support attacking situations. Therefore, leading to a greater number of attacking efforts and return efforts to defensive zones with an overall increase in physical demands of NPL relative to NYL match-play for External Defenders.

Table 2.

Physical demand characteristics of external defenders according to competition standard.

	Competition standard
External defender	NYL	NPL	Difference	Percent difference (%)	Effect size	d
TD/min	119.31 (115.06 – 123.56)	124.88 (121.30 – 128.46)	–5.57 (–6.24 – –4.90)	–4.7	Medium	0.78
LSRD/min	82.31 (79.30 – 85.32)	85.90 (83.12 – 88.67)	–3.59 (–3.83 – –3.35)	–4.4	Medium	0.71
MSRD/min	23.75 (21.29 – 26.20)	24.62 (22.40 – 26.84)	–0.87 (–1.10 – 0.64)	–3.7	Small	0.21
HSRD/min	13.42 (11.85 – 14.99)	14.60 (13.31 – 15.90)	–1.18 (–1.46 – –0.91)	–8.8	Small	0.45
Acc/min	0.63 (0.52 – 0.75)	0.76 (0.65 – 0.88)	–0.13 (–0.13 – –0.13)	–20.5	Medium	0.63
Dec/min	1.07 (0.94 – 1.21)	1.14 (1.00 – 1.27)	–0.07 (–0.07 – –0.07)	–6.2	Small	0.32

Data are presented as least-squares mean (95% CI).

Difference: Difference (95% CI) of the least squares means between NYL and NPL, relative to NYL.

Percent Difference: Percent Difference of the least squares means between NYL and NPL, relative to NYL.

Cohen’s d: trivial effect = < 0.2; small effect = 0.2 – 0.49; medium effect = 0.5 – 0.79; large effect = ≥ 0.8.

Table 3.

Physical demand characteristics of midfield players according to competition standard.

	Competition standard
Midfielder	NYL	NPL	Difference	Percent difference (%)	Effect size	d
TD/min	123.42 (119.86 – 126.99)	122.74 (119.82 – 125.65)	0.68 (0.03 – 1.35)	0.6	Trivial	0.10
LSRD/min	86.52 (83.95 – 89.08)	89.50 (87.27 – 91.73)	–2.98 (–3.32 – –2.65)	–3.4	Medium	0.59
MSRD/min	26.11 (24.03 – 28.19)	23.38 (21.60 – 25.16)	2.73 (2.44 – 3.03)	10.5	Medium	0.67
HSRD/min	10.19 (8.88 – 11.51)	9.15 (8.09 – 10.21)	1.04 (0.79– 1.30)	10.2	Small	0.40
Acc/min	0.69 (0.59 – 0.79)	0.82 (0.73 – 0.91)	–0.13 (–0.14 – –0.12)	–18.5	Medium	0.62
Dec/min	1.10 (0.98 – 1.22)	1.21 (1.10 – 1.33)	–0.11 (–0.12 – –0.11)	–10.4	Medium	0.56

Data are presented as least-squares mean (95% CI).

Difference: Difference (95% CI) of the least squares means between NYL and NPL, relative to NYL.

Percent Difference: Percent Difference of the least squares means between NYL and NPL, relative to NYL.

Cohen’s d: trivial effect = < 0.2; small effect = 0.2 – 0.49; medium effect = 0.5 – 0.79; large effect = ≥ 0.8.

Table 4.

Physical demand characteristics of external attackers according to competition standard.

	Competition standard
External attacker	NYL	NPL	Difference	Percent difference (%)	Effect size	d
TD/min	124.44 (120.22 – 128.66)	119.26 (115.94 – 122.58)	5.19 (4.28 – 6.09)	4.2	Medium	0.73
LSRD/min	84.90 (81.95 – 87.84)	84.07 (81.61 – 86.53)	0.82 (0.34– 1.31)	1	Trivial	0.16
MSRD/min	25.06 (22.65 – 27.47)	21.92 (19.93 – 23.90)	3.14 (2.72 – 3.57)	12.5	Medium	0.77
HSRD/min	15.18 (13.61 – 16.74)	14.07 (12.86 – 15.29)	1.10 (0.75 – 1.46)	7.3	Small	0.42
Acc/min	0.61 (0.50 – 0.73)	0.81 (0.71 – 0.91)	–0.20 (–0.21 – –0.19)	–32.3	Large	0.97
Dec/min	0.97 (0.84 – 1.10)	1.13 (1.01 – 1.24)	–0.16 (–0.17 – –0.14)	–16.2	Medium	0.77

Data are presented as least-squares mean (95% CI).

Difference: Difference (95% CI) of the least squares means between NYL and NPL, relative to NYL.

Percent Difference: Percent Difference of the least squares means between NYL and NPL, relative to NYL.

Cohen’s d: trivial effect = < 0.2; small effect = 0.2 – 0.49; medium effect = 0.5 – 0.79; large effect = ≥ 0.8.

The increased Acc/min (Figure 2(a)) recorded in NPL match-play may place a greater physiological demand on players compared to NYL match-play.^25,26 Accelerations contribute to a considerable proportion of the physiological load experienced by players during match-play and have been identified as critical indicators of position-specific match demands and external match loads.^25,26 Previous research pertaining to the evolution of technical and tactical aspects of soccer suggests that the proportion of players within selected dimensions of the field relative to the ball has increased in recent decades alongside an increased number of successful passes.^27,28 This evolution of technical and tactical aspects in addition to higher match success in NPL competition matches (85%) could explain the increase in Acc/min in NPL versus NYL match-play. As such, the increased Acc/min (Figure 2(a)) for Central Defenders (47.8%), External Defenders (20.5%), Midfielders (18.5%) and External Attackers (32.3%) could be attributed to decreased proximity between players, leading to an increased demand for short, multi-directional high-intensity accelerations in order to create greater passing opportunities between the reference team players or press opposition players when not in possession of the ball creating a greater number of attacking and defensive efforts in NPL versus NYL match-play.

Despite being a hierarchically lower standard, NPL competition match-play influenced the physical demands for External Defenders (Table 2), suggesting the need for individualised conditioning programs based upon competition standard and player position. Unlike previous investigations, this is the first study to analyse a single player cohort competing in two standards of competitions. Given that the Australian elite youth soccer player development pathway consists of a duel, segmented competition structure, understanding the influence of each competition standard should be of consideration to coaches and performance staff as they are charged with transitioning players to elite senior male soccer.

The limitations of this study are primarily related to the challenges of collecting data on high level performers. The different number of NYL (n = 8) and NPL (n = 21) competition matches is a limitation and future investigations should aim to include a similar number of matches at each competition standard. Previous research has shown that the physical demands of match-play differ according to the reference team and opposition formation.⁵ While other tactical formations have been reported, we contend that for our research question, having a single team formation and tactics used throughout the data collection period reduced the confounding variables involved and strengthened the study design. However, it should be noted that as the study was limited to investigating a single team, it is possible the findings of this study may not be generalised across the wider Australian elite youth soccer player development pathway. In addition, this study did not analyse the influence of techno-tactical related performance variables such as ball possession or goal scoring opportunities. Furthermore, competition related variables such as win to loss ratios were not considered. Given the seasonal differences between NYL and NPL competitions and the travel requirements for the NYL, the influence of temperature and extended ground travel should be analysed in future studies as challenging environmental conditions and lengthy periods of travel has been shown to impair match day performance.^29–31 Finally, it is important to consider that excluding data pertaining to the varying fitness levels and workloads across different periodisation periods and teams may pose a limitation on the study. As elite players are found to have greater physical capabilities compared to sub-elite it is reasonable to assume that elite players are capable of covering greater distances during competition match-play.⁸ In order to distinguish the influence of player status and competition standard future investigation should consider analysing fitness levels and workloads across different periodisation periods.

The present study highlights that competition standard influence the physical demands of match-play in Australian elite youth soccer players. Player position marginally influenced the amount of TD/min in NYL compared to NPL match-play. However, there was a larger influence of player position on HSRD/min in NYL relative to NPL match-play. In contrast the effect of player position and competition standard was reversed when considering the accelerations performed, with a greater number performed in NPL versus NYL match-play. Therefore, coaches and performance staff involved in the Australian soccer player development pathway should adopt a position and competition standard specific approach to training program design.

Practical applications

Coaches and performance support staff working in the Australian elite youth male soccer player development pathway need to consider the impact of varied competition standards and specific player position requirements when analysing and preparing for the physical demands of match-play. Coaches should design training programs to develop the ability to meet the higher demands of the NYL (professional development level) match-play but be mindful of the influence of competition standard on certain positions. Such data can provide vital information to assist youth players and coaches in the transition to higher standards of soccer. Furthermore, it may aid in the development of monitoring models for the physical demands of match-play as well as aid in the management of external player loading.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethics approval

Human Research Ethics Committee of the University of Canberra, Australia.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Michael G Sydney

Dale Chapman

Jocelyn K Mara

References

Trewin

Meylan

Varley

, et al. The influence of situational and environmental factors on match-running in soccer: a systematic review. Sci Med Football 2017; 1: 183–194.

Aquino

Vieira

LHP

Carling

, et al. Effects of competitive standard, team formation and playing position on match running performance of Brazilian professional soccer players. Int J Performance Anal Sport 2017; 17: 695–705.

Di Salvo

Pigozzi

Gonzalez-Haro

, et al. Match performance comparison in top English soccer leagues. Int J Sports Med 2012; 34: 526–532.

Buchheit

Mendez-Villanueva

Simpson

, et al. Match running performance and fitness in youth soccer. Int J Sports Med 2010; 31: 818–825.

Carling

Influence of opposition team formation on physical and skill-related performance in a professional soccer team. Eur J Sport Sci 2011; 11: 155–164.

Abbott

Brickley

Smeeton

NJ.

Physical demands of playing position within English Premier League academy soccer. Jhse 2018; 13.

Aquino

Munhoz Martins

Palucci Vieira

, et al. Influence of match location, quality of opponents, and match status on movement patterns in Brazilian professional football players. J Strength Cond Res 2017; 31: 2155–2161.

Rebelo

Brito

Maia

, et al. Anthropometric characteristics, physical fitness and technical performance of under-19 soccer players by competitive level and field position. Int J Sports Med 2013; 34: 312–317.

Goto

Morris

Nevill

ME.

Motion analysis of U11 to U16 elite English Premier League academy players. Journal of Sports Sciences 2015; 33: 1248–1258.

10.

Mendez-Villanueva

Buchheit

Simpson

, et al. Match play intensity distribution in youth soccer. Int J Sports Med 2012; 34: 101–110.

11.

O'Connor

Larkin

Mark Williams

Talent identification and selection in elite youth football: an Australian context. Eur J Sport Sci 2016; 16: 837–844.

12.

Bradley

Carling

Gomez Diaz

, et al. Match performance and physical capacity of players in the top three competitive standards of English professional soccer. Hum Move Sci 2013; 32: 808–821.

13.

Mara

Thompson

Pumpa

, et al. Quantifying the high-speed running and sprinting profiles of elite female soccer players during competitive matches using an optical player tracking system. J Strength Condition Res 2017; 31: 1500–1508.

14.

Waldron

Murphy

A comparison of physical abilities and match performance characteristics among elite and subelite under-14 soccer players. Pediatr Exerc Sci 2013; 25: 423–434.

15.

Keller

Raynor

Iredale

, et al. Tactical skill in Australian youth soccer: does it discriminate age-match skill levels? Int J Sports Sci Coach 2018; 13: 1057–1063.

16.

Edgecomb

Norton

KI.

Comparison of global positioning and computer-based tracking systems for measuring player movement distance during Australian football. J Sci Med Sport 2006; 9: 25–32.

17.

Barr

Beaver

Turczyn

, et al. Validity and reliability of 15 Hz global positioning system units for assessing the activity profiles of university football players. J Strength Cond Res 2019; 33: 1371–1379.

18.

R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, 2020.

19.

Bates

Mächler

Bolker

, et al. Fitting linear mixed-effects models using lme4. J Stat Soft 2015; 67: 48.

20.

Fox J and Weisberg S. An {R} Companion to Applied Regression, Third Edition. Thousand Oaks, CA: Sage, 2019. https://socialsciences.mcmaster.ca/jfox/Books/Companion/

21.

Winter

Linear models and linear mixed effects models in R with linguistic applications. arXiv:13085499 2013.

22.

Northey

Pumpa

Quinlan

, et al. Cognition in breast cancer survivors: a pilot study of interval and continuous exercise. J Sci Med Sport 2019; 22: 580–585.

23.

Bradley

Lago-Penas

Rey

, et al. The effect of high and low percentage ball possession on physical and technical profiles in English FA premier league soccer matches. J Sports Sci 2013; 31: 1261–1270.

24.

Andrzejewski

Konefał

Chmura

, et al. Match outcome and distances covered at various speeds in match play by elite German soccer players. Int J Perform Anal Sport 2016; 16: 817–828.

25.

Taylor

Wright

Dischiavi

, et al. Activity demands during multi-directional team sports: a systematic review. Sports Med 2017; 47: 2533–2551.

26.

Harper

Carling

Kiely

High-intensity acceleration and deceleration demands in elite team sports competitive match play: a systematic review and meta-analysis of observational studies. Sports Med 2019; 49: 1923–1947.

27.

Barnes

Archer

Hogg

, et al. The evolution of physical and technical performance parameters in the English Premier League. Int J Sports Med 2014; 35: 1095–1100.

28.

Bush

Barnes

Archer

, et al. Evolution of match performance parameters for various playing positions in the English Premier League. Hum Move Sci 2015; 39: 1–11.

29.

Paul

Bradley

Nassis

GP.

Factors affecting match running performance of elite soccer players: shedding some light on the complexity. Int J Sports Physiol Perform 2015; 10: 516–519.

30.

Mohr

Krustrup

Nybo

, et al. Muscle temperature and sprint performance during soccer matches – beneficial effect of re‐warm‐up at half‐time. Scand J Med Sci Sports 2004; 14: 156–162.

31.

Rabbani

Buchheit

Ground travel-induced impairment of wellness is associated with fitness and travel distance in young soccer players. Kinesiology (Zagreb, Online) 2016; 48: 200–206.