Secondary Logo

Journal Logo

Research Note

Does On-Field Sprinting Performance in Young Soccer Players Depend on How Fast They Can Run or How Fast They Do Run?

Mendez-Villanueva, Alberto; Buchheit, Martin; Simpson, Ben; Peltola, Esa; Bourdon, Pitre

Author Information
Journal of Strength and Conditioning Research: September 2011 - Volume 25 - Issue 9 - p 2634-2638
doi: 10.1519/JSC.0b013e318201c281
  • Free

Abstract

Introduction

The ability to perform high-speed running actions such as sprints to win possession of the ball or to pass defending players is believed to be critical to the outcome of soccer matches (2). As such, sprint ability has been reported to be a physical prerequisite for professional soccer players (5,10,17). Nevertheless, Mujika et al. (14) found no difference in sprint performance between successful and unsuccessful players progressing to professional levels. From a talent development perspective, Vaeyens et al. (18) reported that sprint ability could only discriminate between competitive standards when comparing preadolescent male players (i.e., under 13-14 years). As a consequence of these contradictory results, the relevance of sprinting speed for football talent identification and fitness testing can be questioned.

High-level soccer is a tactical game. As such, player behavior on the field is often constrained by tactical tasks that can vary because of factors such as playing style, playing position, or match score (2,7,17). Such tactical constraints may modulate the relationship between maximal performance (i.e., an intrinsic physical quality determined via specific field or laboratory tests) and actual performance during the game. For example, how fast players run during an actual match compared with how fast they are able to run in a controlled test? If soccer match play constrains the expression of their true maximal physical qualities, it could be possible that in-game performance rather than maximal performance, as assessed via field or laboratory tests, may be of greater relevance in determining the importance of running speed in soccer players (3,14). This leads to another question relevant to talent selection and development: “Under match conditions, do slower players use a greater percentage of their maximal sprinting speed (MSS) than faster individuals?” In this regard, slower players may compensate by either using a greater proportion of their MSS to attain a sufficient running speed or by changing behavior (e.g., the so-called “tactical insight” which could allow a player to “read the game” faster) (19). Thus, quantifying the percentage use of MSS attained during a game can give an insight into additional aspects that studies comparing sprinting performance assessed via field tests may not reveal. Moreover, quantifying the percentage of MSS used in the game may also reveal whether individuals can compensate for a poor physical capacity. To our knowledge, no studies have tested these aspects. Consequently, this case study aims to explore the associations between MSS and peak match running speed.

Methods

Experimental Approach to the Problem

In this investigation, an observational, case-control design was used to examine the effects of MSS on match running speed in highly trained young soccer players during international club games. The 2 fastest players of the academy provided an opportunity to compare their work rates and compare them with the other (slower) players. Player's MSS was determined using the fastest 10-m split time during an electronically timed 40-m sprint. Portable global position system (GPS) technology was used to assess game speed.

Subjects

Time-motion analysis of running activity was collected from 14 highly trained young male, outfield footballers (8 wide midfielders [WM] and 6 central defenders [CD], 173.2 ± 6.0 cm, 60.8 ± 8.1 kg, 16.7 ± 0.7 years) from the same high-performance soccer academy. All players participated on average in ∼14 hours of combined soccer (6-8 sessions), strength (1 session), and conditioning (1-2 sessions) training and competitive play (1 domestic game per week and 2 international games every 3 weeks) per week. Additionally, all players had a minimum of 6 years of soccer-specific training. Written informed consent was obtained from both the players and their parents before the investigation. The experimental protocol was approved by the Institutional Ethics Committee.

Experimental Procedures

Match analyses were performed 2-5 times on each player during a total of 14 friendly international club level matches played over a period of 4 months (February-May). The high level of the opposing teams and the consistency of the competition format both serve to reduce between match variability in running performance (15). All matches were played on identical 100 × 70-m outdoor natural grass fields with 11 players per side. Playing time was 2 halves of 40-45 minute each. Tactically, all teams used a 4-4-1-1 formation, a variation of 4-4-2 with one of the strikers playing as a “second striker,” slightly behind their partner. All players undertook a maximal running speed test to determine MSS. Because of the potentially confounding effect of maturation on physical performance, MSS was reassessed at least once within the 4-month investigation period. All MSS tests were performed in an indoor facility maintained at standard environmental conditions. Players wore running shoes during the MSS tests and soccer boots during matches. Every test session was preceded by a standardized 20-minute warm-up. Players were familiar with all testing procedures.

Maximal Sprinting Speed

Maximal sprinting speed was defined as the fastest 10-m split time (12) measured during a maximal 40-m sprint (dual-beam electronic timing gates set at 10-m intervals, Swift Performance Equipment, Lismore, Australia). Split times were measured to the nearest 0.01 seconds. Players commenced each sprint from a standing start with their front foot 0.5 m behind the first timing gate and were instructed to sprint as fast as possible over the 40-m distance. The players started when ready, thus eliminating reaction time and completed at least 2 trials with the best performance used as the final result.

Activity Pattern Measurements

A GPS unit capturing data at 1 Hz (SPI Elite, GPSports, Canberra, Australia) was fitted to the upper back of each player using an adjustable neoprene harness. This GPS system uses signals from at least 3 Earth-orbiting satellites to determine the player's position at a given time and therefore allow the calculation of movement speeds and distance traveled (9) Using this information, a receiver is able to calculate and record data on position, time, and velocity (13). Despite a possible underestimation of high-intensity running distance with the time resolution of 1 Hz, good accuracy (r = 0.97) (1) and reliability (coefficient of variation = 1.7% [1] and 2.3% [6]) have been reported for the assessment of peak sprinting speed for this GPS device compared to a infrared timing system. Moreover, in the absence of a “gold standard” method, the current system has been reported to be capable of measuring individual movement patterns in soccer (16).

Match Analysis

Time-motion data of all players who participated in the entire first half were collected (n = 36 files from 14 different players). To limit the possible effect of fatigue on player work rates (2,4), only the first halves were analyzed. Because of the different physical demands of different playing positions (2), the 2 fastest players (a WM and a CD) were compared with each of the slower players who played in the same position. All match data was analyzed with a custom-made Microsoft Excel program designed to provide objective measures of physical match performance. The highest speed attained during the match (i.e., peak game speed) was recorded and was also expressed as a percentage of MSS (2,4).

Statistical Analyses

Descriptive statistics are mean ± SD unless otherwise stated. Data were assessed for practical significance using an approach based on the magnitudes of differences (11). Within-position differences (i.e., faster vs. slower players) in maximal running speed and peak game speed were first expressed as standardized mean differences (Cohen effect sizes [ESs]) (11). Threshold values for Cohen ES statisticswere ≤0·0.2 trivial, >0.2-0.6 small, >0.6-1.2 moderate, >1.2-2.0 large; >2.0-4.0 very large. Confidence intervals (90%) for the (true) within-position differences were also calculated (11). The chances that the true values between the fast players were greater (i.e., greater than the smallest practically important effect, or the smallest worthwhile change [0.2 multiplied by the between-subject SD, based on Cohen's ES principle]), similar or smaller than those for the slower players were calculated. Quantitative chances of having different performances were assessed qualitatively as follows: <1%, almost certainly not; 1-5%, very unlikely; 5-25%, unlikely; 25-75%, possible; 75-95%, likely; 95-99, very likely; >99%, almost certain. If the chance of having better or poorer performances were both >5%, the true difference was assessed as unclear (11).

Results

Relative differences and qualitative outcomes resulting from the within-positions analysis are presented in Table 1. Compared with the other WMs, the fastest WM was almost certain to have achieved higher peak game speeds. Similarly, the fastest CB was very likely to have run faster than their slower counterparts. The percentage of MSS used in the game was likely higher for the fastest WM than for the slower WMs. On the contrary, the fastest CD likely used a lower percentage of MSS than the slower CDs.

T1-36
Table 1:
Within-position differences in 10-m running speed (10-m), MSS, peak game speed, and peak game speed expressed as a percentage of MSS.*

Results from between-position analysis are presented in Table 2. Among the fastest players, the WM had a likely faster peak game speed than the CB. On the contrary, the slower WMs had likely lower peak game speeds than the slower CDs. There was a very likely difference between the fastest CD and WM in the percentage of MSS used during the game, but the slower CDs and WMs did not differ (trivial ES and unclear difference).

T2-36
Table 2:
Between-position differences (i.e., CD compared with WM) in 10-m running speed (10-m), MSS, peak game speed, and peak game speed expressed as a percentage of MSS.*

Discussion

Despite the growing number of studies that have suggested that high-speed running performance is advantageous for elite soccer performance (5,10,17), its importance has been recently questioned (14). Surprisingly, to the best of our knowledge, no study has explored the relevance of high-speed running traits on physical performance in a game. The main findings of this case study are (a) faster players reach higher absolute running speeds during games than their slower counterparts regardless of the playing position; (b) slower WMs did not compensate for reduced MSS by increasing the percentage of MSS used during the game while the slower CDs did, and (c) both playing position and individual MSS play an important role in influencing the expression of their peak game speed.

Absolute peak speeds reached in games by the fastest WM and CD were ∼14 and ∼6% higher than the slower WMs and CDs, respectively. Peak speeds in games were on average 10-15% below players' MSS (Table 1), regardless of the position. Interestingly, the fastest WM attained a faster peak game speed (31.0 ± 0.4 km·h−1) than the slower WMs' MSS (30.2 ± 0.5 km·h−1). In addition, absolute peak speed attained in games was ∼5% higher for the fastest WM than for the fastest CD, despite their similar MSS (Table 2). As previously suggested for professional soccer players, the higher peak speed in games achieved by the WMs may be related to the fact that these players have more space and time along the flanks, allowing for full and longer acceleration (2). Contrary to this, the slower WMs recorded ∼3.5% lower peak game speeds than the slower CDs (Table 2). Interestingly, the MSS of the slower WMs was also ∼3.5% lower than the slower CDs. Given the higher peak game speeds reached by the fastest players, and the fact that all players (irrespective of their MSS) used a high percentage of their MSS, these results provide direct support to the hypothesis that maximal running speed can impact what a player can do in actual playing conditions. Although some very short duration sprints could have been missed by our 1-Hz GPS devices when compared with other soccer tracking systems (16), previous studies have reported good accuracy of peak speed during short sprints for these devices (6).

Slower CDs were all found to compensate for their lower MSS by attaining a higher percentage of their MSS in games compared with the fastest CD; no compensation was however shown for the slower WMs (Table 1). This compensation in the slower CDs suggests the possibility of a ‘speed threshold’ that CD must attain in order to succeed in this position. Thus, faster (i.e., higher MSS) players may not need to use as large a proportion of their MSS to succeed, whereas a slower player would. Also worth noting is that despite the compensation shown by the slower CDs, the fastest CD still reached substantially higher peak speeds in games. Irrespective of how fast they were, WMs showed no such compensation because they all attained near maximal running speeds (i.e., ∼90% MSS) while playing. As such, the fastest WM who has the capacity to run faster did so during the game as compared to WMs with lower MSS (Table 1). These findings expand on previous studies (2,3,7) and provide evidence that tactical roles associated with playing as a WM is less likely to restrain the expression of the player's maximal running speed during the game in comparison to playing as a CD.

Practical Applications

Because most sprints during games are performed over short distances (2), acceleration capacity is believed to be the most important speed quality in soccer. As such, speed sessions typically conducted by soccer coaches and fitness trainers include short sprints (typically <20 m). Our data however reveal that players also achieve very high sprinting speeds (i.e., >90% of MSS) during matches, suggesting that MSS in addition to acceleration can influence a player's physical performance during a match (8). The assessment of running speed in developing players should therefore include assessments of both acceleration (e.g., 10 m) and MSS (e.g., ≥40 m). It is recommended that fitness coaches regularly incorporate maximal speed drills in training that allow near MSS to be achieved. This may include maximal 30- to 60-m sprints and other training techniques (e.g., resistance training, functional training, plyometrics) specific to developing MSS. Finally, because playing as a WM is more likely to favor the expression of a player's MSS, considerable attention should be directed at these players both on-field and off-field training to maximize the development of both acceleration and MSS qualities.

References

1. Barbero-Alvarez, JC, Coutts, A, Granda, J, Barbero-Alvarez, V, and Castagna, C. The validity and reliability of a global positioning satellite system device to assess speed and repeated sprint ability (RSA) in athletes. J Sci Med Sport 13: 232-235, 2010.
2. Bradley, PS, Mascio, MD, Peart, D, Olsen, P, and Sheldon, B. High-intensity activity profiles of elite soccer players at different performance levels. J Strength Cond Res, 24: 2343-2351, 2010.
3. Buchheit, M, Mendez-Villanueva, A, Simpson, BM, and Bourdon, PC. Match running performance and fitness in youth soccer. Int J Sports Med, 31: 818-825, 2010.
4. Buchheit, M, Mendez-Villanueva, A, Simpson, BM, and Bourdon, PC. Repeated-sprint sequences during youth soccer matches. Int J Sports Med, 31: 709-716, 2010.
5. Cometti, G, Maffiuletti, NA, Pousson, M, Chatard, JC, and Maffulli, N. Isokinetic strength and anaerobic power of elite, subelite and amateur French soccer players. Int J Sports Med 22: 45-51, 2001.
6. Coutts, AJ and Duffield, R. Validity and reliability of GPS devices for measuring movement demands of team sports. J Sci Med Sport, 13: 133-135, 2010.
7. Di Salvo, V, Gregson, W, Atkinson, G, Tordoff, P, and Drust, B. Analysis of high intensity activity in Premier League soccer. Int J Sports Med 30: 205-212, 2009.
8. Duthie, GM, Pyne, DB, Marsh, DJ, and Hooper, SL. Sprint patterns in rugby union players during competition. J Strength Cond Res 20: 208-214, 2006.
9. Edgecomb, SJ and Norton, KI. Comparison of global positioning and computer-based tracking systems for measuring player movement distance during Australian football. J Sci Med Sport 9: 25-32, 2006.
10. Gissis, I, Papadopoulos, C, Kalapotharakos, VI, Sotiropoulos, A, Komsis, G, and Manolopoulos, E. Strength and speed characteristics of elite, subelite, and recreational young soccer players. Res Sports Med 14: 205-214, 2006.
11. Hopkins, WG, Marshall, SW, Batterham, AM, and Hanin, J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc 41: 3-13, 2009.
12. Korhonen, MT, Mero, A, and Suominen, H.Age-related differences in 100-m sprint performance in male and female master runners. Med Sci Sports Exerc 35: 1419-1428, 2003.
13. Larsson, P. Global positioning system and sport-specific testing. Sports Med 33: 1093-1101, 2003.
14. Mujika, I, Santisteban, J, Impellizzeri, FM, and Castagna, C. Fitness determinants of success in men's and women's football. J Sports Sci 27: 107-114, 2009.
15. Rampinini, E, Coutts, AJ, Castagna, C, Sassi, R, and Impellizzeri, FM. Variation in top level soccer match performance. Int J Sports Med 28: 1018-1024, 2007.
16. Randers, MB, Mujika, I, Hewitt, A, Santisteban, J, Bischoff, R, Solano, R, Zubillaga, A, Peltola, E, Krustrup, P, and Mohr, M. Application of four different football match analysis systems: a comparative study. J Sports Sci 28: 171-182, 2010.
17. Stolen, T, Chamari, K, Castagna, C, and Wisloff, U. Physiology of soccer: an update. Sports Med 35: 501-536, 2005.
18. Vaeyens, R, Malina, RM, Janssens, M, Van Renterghem, B, Bourgois, J, Vrijens, J, and Philippaerts, RM.A multidisciplinary selection model for youth soccer: the Ghent Youth Soccer Project. Br J Sports Med 40: 928-934; discussion 934, 2006.
19. Verheijen, R. Preparing the Korean National Team for the 2002 World Cup. Insight: Football Assoc Coaches J 6: 30-33, 2004.
Keywords:

association football; match analysis; high-speed running; playing position

Copyright © 2011 by the National Strength & Conditioning Association.