Validity of a Repeated-Sprint Test for Football

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Apr 16, 2008 - 2 Human Performance Laboratory, Mapei Sport Research Center, Castellanza,. Italy. 3 School of Sport and Exercise Sciences, University of ...
Training & Testing

Validity of a Repeated-Sprint Test for Football

Authors

F. M. Impellizzeri 1, 2, E. Rampinini 2, C. Castagna 3, D. Bishop 4, D. Ferrari Bravo 2, A. Tibaudi 2, U. Wisloff 5

Affiliations

The affiliations are listed at the end of the article

Key words " reliability l " construct validity l " soccer l " playing positions l " competitive level l

Abstract !

Three studies involving 108 football players were conducted to examine the reliability of a repeated-shuttle-sprint ability (RSSA) test and its ability to differentiate between players of various competitive levels and playing positions. Study 1: Short-term reliability was determined in 22 professional players completing the RSSA test (6 × 40-m sprints with 20 s of recovery between sprints) on two separate occasions. Study 2: Long-term reliability (seasonal changes) was examined in 31 professional players completing the RSSA test four times (during the preseason period, at the start, middle and end of the competitive season). Study 3: 108 players were divided

Introduction !

accepted after revision February 19, 2008 Bibliography DOI 10.1055/s-2008-1038491 Published online April 16, 2008 Int J Sports Med 2008; 29: 899 – 905 © Georg Thieme Verlag KG Stuttgart • New York • ISSN 0172-4622 Correspondence Dr. Franco M. Impellizzeri Neuromuscular Research Laboratory Schulthess Clinic Lengghalde 2 8008 Zurich Switzerland Phone: + 41(0)4 43 85 75 87 Fax: + 41(0)4 43 85 75 90 [email protected]

Association football (soccer) is a complex sport requiring the repetition of many different activities such as jogging, sprinting and jumping [6, 18, 26, 31]. Players are often required to repeatedly produce maximal or near maximal sprints of short duration (1 – 7 s) with brief recovery periods [6, 31]. Therefore, the ability to repeat multiple sprints at high speed is important for soccer physical performance [5, 32]. The use of tests consisting of several sprints interspersed with brief recovery periods, instead of a single sprint, should ensure physiological responses similar to those occurring during intense periods of play in actual matches [24, 27, 32]. For these reasons, the use of repeated-sprint ability exercises for the training and testing of soccer players is increasing [19, 23, 24, 27]. The validity of most currently used repeatedsprint ability tests is based predominantly on their intrinsic characteristics (logical validity). The use of these tests often assumes that they actually measure match-related physical perfor-

and compared according to competitive level or playing position. Standard error of measurement values expressed as coefficient of variation for RSSA mean time and best time were 0.8 and 1.3 % (short-term reliability) and 0.9 and 1.2% (long-term reliability), respectively. The smallest worthwhile changes were 0.5 % for both mean and best time. Professional players showed better RSSA performance than amateur players, and defenders displayed the lowest RSSA performance. In conclusion, the RSSA test showed adequate construct validity but only RSSA mean time showed sufficient reliability to detect large training-induced changes but not small important differences.

mance (construct validity) [14]. However, to the authors’ knowledge, only one study examined the construct validity, as indicated by match-related physical performance, of a repeated-shuttle-sprint ability (RSSA) test for soccer players [21]. Rampinini et al. [21] have shown, in professional soccer players, that there are moderate but significant correlations between sprinting (r = – 0.65) and high-intensity running (r = – 0.60) completed during official match-play and the mean performance during an RSSA shuttle-running test (six 40-m shuttle sprints interspersed with 20 s of passive recovery). These relationships confirmed the involvement of physical capacities actually taxed during the high-intensity phases of the game. Given that several factors that can influence actual physical-match performance, these correlations support the construct validity of the investigated RSSA test. However, the strength of the correlations does not support the predictive validity of the test, for which r values above 0.90 are usually necessary. Although Rampinini et al. [21] have provided preliminary convergent evidence to the construct

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Training & Testing

validity of the RSSA test, several studies are required to build up a body of evidence to support the validity of a test [2]. The construct validity of a test can also be examined by comparing the test scores of populations assumed to differ in physical requirements during a match (know-group difference technique) and hence assumed to be characterized by different physical capacities [28]. Some studies, indeed, have examined the ability of field tests to differentiate between soccer players of different competitive levels or playing positions [9,15]. To be valid and applicable, a test must also be reliable. The knowledge of the reliability of a test allows one to understand if the instrument can be used to detect changes as a consequence of interventions (signal-tonoise ratio) and to better interpret the test results. Therefore, both short- and long-term reliability should be calculated to supply information to researchers and practitioners interested in examining the efficacy of specific interventions over different time frames. For example, short-term reliability can be used to calculate the individual minimum detectable change, while long-term reliability allows the estimation of sample sizes necessary to detect meaningful changes in intervention studies and/ or to estimate the individual differences in response to treatments [11]. Therefore, three studies were conducted to determine 1) the short- and 2) long-term reliability, and 3) to examine the ability of the RSSA test proposed by Rampinini et al. [21] to differentiate between football players of different competitive levels and playing positions (construct validity).

Methods !

fessional soccer players (age 25 ± 5 years, body mass 78 ± 8 kg, and height 181 ± 5 cm) recruited from three teams competing in their national league and in international and national cup competitions. Data were collected from 2006 and 2007 and only players with field tests completed in four selected periods of the season (every three months) were involved in the study: the first week of the preseason training (PRE); within the first 4 weeks from the start of the competitive season (EARLY); within the 4 weeks in the middle of the competitive season (MID); and within 4 weeks before the end of the season (END). During the Early to Mid period, teams played one match a week (national championship) and one in-week match (national and international competitions). The generic training plan completed by the soccer players involved in this study was supplied by the fitness coaches of the teams. The soccer players completed RSSA-based training sessions two to three times a week during the pre-competition training period, and once a week during the competitive season. In the remaining part of the physical training (twice a week during the preseason and once a week during the competitive season), players completed aerobic high-intensity interval training sessions using both specific (small-sided games and soccer-specific circuits) and generic (running) exercises [13]. Training also included sessions of plyometric training, but no resistance training sessions were completed with the exception of injured players who performed resistance training during the rehabilitation (these players were excluded from the study). Each set (from 2 to 4) of the RSSA training consisted of 5 to 10 sprints (5, 10, 20 and 40 m), for a maximal total distance of 40 m for each sprint. The recovery between sprints ranged from 20 s to 1 min, and the passive recovery duration between sets ranged from 2 to 4 min.

Subjects and study design The present investigation consisted of three separate studies involving a total of 108 male soccer players participating in one or more of these studies. The study was approved by the Independent Institutional Review Board according to the Guidelines and Recommendations for European Ethics Committees by the European Forum for Good Clinical Practice. Data collection started in 2005 and finished in 2007. Before each testing session, subjects were instructed not to eat for at least three hours before testing and to maintain the normal dietary habits in the two days before testing. Tests were always completed at least 48 hours after the match and after one to two days of tapering. In the preseason period, tests were performed during a tapering week, after two to three days of reduced training load.

Study 1 Short-term reliability. Reliability was determined in 22 professional football players (age 22 ± 1 years, body mass 73 ± 5 kg, and height 177 ± 4 cm) from the same team who completed the RSSA test twice within one week; at least 48 hours separated the trials. The RSSA tests were completed at the same time of the day after a 10-min warm-up of low-intensity running and striding, followed by three submaximal 40-m shuttle sprints (20 + 20 m). The RSSA test was completed within 5 min after the warm-up. Players were already familiar with this test that was part of their routine assessment. Therefore, no familiarization trials were necessary.

Study 2 Long-term reliability (seasonal changes). In the second study, we examined the long-term reliability in the RSSA test in 30 pro-

Impellizzeri FM et al. Validity of a … Int J Sports Med 2008; 29: 899 – 905

Study 3 Differences between competitive level and playing position. In this study, 108 football players (age 24 ± 4 years, body mass 75 ± 7 kg, and height 179 ± 5 cm) tested from three to five times during the season were selected among professional and amateur players. For each player, the best test was selected to obtain a more representative test score of the examined physical capacity. Players were classified in three groups according to their level: 1) top-professional (players of teams participating in the first division championship of their nation); mid-professional (players of teams participating in the second and third division championships of their nation); and 3) amateur (nonprofessional). Soccer players were also assigned to one of four playing position groups based on the indication of their coaches: 1) defenders; 2) fullbacks; 3) midfielders; and 4) forwards.

RSSA test protocol To measure RSSA, we used a test consisting of six 40-m (20 + 20m sprints with 1808 turns) shuttle sprints separated by 20 s of passive recovery [21]. This test was designed to measure both repeated-sprint and change in direction abilities. The athletes started from a line, sprinted for 20 m, touched a line with a foot and came back to the starting line as fast as possible. After 20 s of passive recovery, the soccer player restarted again. Immediately after the warm-up, each player completed a preliminary single shuttle-sprint test using a photocells system (Microgate, Bolzano, Italy). This trial was used as the criterion score during the subsequent 6 × 40-m shuttle sprint test [21]. After the first preliminary single shuttle-sprint, subjects rested for 5 min before the start of the RSSA test. If performance in the first sprint of an

Training & Testing

RSSA test was worse than the criterion score (i.e., an increase in time greater than 2.5 %), the test was terminated immediately and subjects were required to repeat the RSSA test with maximum effort after a further 5-min rest. Five seconds before the start of each sprint, subjects assumed the ready position and waited for the acoustic start signal (with 5 s of countdown). Best time in a single trial (RSSAbest), mean time (RSSAmean) and decrement (RSSAdecrement) were determined according to Rampinini et al. [21]. Specifically, the RSSAdecrement was calculated as RSSAmean/RSSAbest and expressed as percent. All tests were completed outdoors on natural grass surface.

Statistical analyses Unless otherwise noted, all data are presented as mean ± standard deviation (SD). Relative reliability concerns the degree to which individuals maintain their position in a sample with repeated measurements [4]. We assessed this type of reliability using the intraclass correlation coefficient [ICC(2,1), a two-way random effects model with single measure]. We considered an ICC over 0.90 as high, between 0.80 and 0.90 as moderate and below 0.80 as low [30]. Absolute reliability is the degree to which repeated measurements vary for individuals [4] and we expressed this type of reliability with the standard error of measurement expressed in absolute terms (SEM) or as coefficient of variation (CV) [11]. Short-term relative and absolute reliability were determined using the tests completed twice in one week (Study 1). The percent change was calculated using the change scores of log transformed data of the two trials. The effect size of the difference (d) was determined as: (mean value trial 2 – mean value of trial 1)/pooled SD. The modified scale by Hopkins (www.sportsci.org/resource/stats/2002) was used for the interpretation of d: trivial, < 0.2; small, 0.2 – 0.6; moderate, 0.6 – 1.2; and large, > 1.2. Long-term absolute and relative reliability were examined using the four RSSA test sessions (Early, Start, Mid, and End). Percent differences in means (seasonal changes) and the corresponding 90 % confidence intervals were calculated from log transformed data. We also calculated the likelihood that the true values of estimated difference in RSSA parameters were substantial (i.e., larger than the smallest worthwhile change, SWC). Threshold for assigning qualitative terms to chances of substantial differences were as follows: < 1%, almost certainly not; < 5%, very unlikely; < 25 %, unlikely or probably not; > 50 %, possibly; > 75%, likely or probable; > 95 %, very likely; > 99%, almost certain [16]. Different methods can be used to determine the small worthwhile change [3,12]. In the present study, the SWC (expressed as percentage) was calculated as a proportion of the effect size which represents the magnitude of improvement in a variable as a function of the between-subjects standard deviation of the investigated population (i.e., 0.2 times the between-subject SD of top- and mid-professional football players) [11,12]. The differences between competitive levels and playing positions were examined using a two-way ANOVA (3 × 4 design). The independent variables included a between-subject factor “competitive level” with three levels (top-professional, mid-professional, and amateur), and a between-subject factor “playing position” with four levels (defender, fullback, midfielder, and forward). When a significant F-value was found (p £ 0.05), the Bonferroni post hoc test was applied. All statistical analyses were performed with SPSS 13.0.

Results !

Study 1 Short-term reliability. Absolute and relative SEM were 0.06 s (CI 90% 0.04 – 0.07 s) and 0.8 % (CI 90% 0.6 – 1.0%) for RSSAmean, 0.09 s (CI 90% 0.07 – 0.12 s) and 1.3 % (CI 90% 1.0 – 1.7 %) for RSSAbest, and 1.2 s (CI 90% 0.9 – 1.6 s) and 30.2 % (CI 90% 23.6 – 42.7%) for RSSAdecrement. Trivial to small differences were found between trial 1 and trial 2 for RSSAmean (7.20 ± 0.11 s vs. 7.19 ± 0.14 s, respectively: effect size 0.09 [trivial]), for RSSAbest, (6.90 ± 0.09 s vs. 6.92 ± 0.10 s, respectively; effect size = 0.24 [small]), and for RSSAdecrement (4.3 ± 1.2 % vs. 3.8 ± 1.4 %, respectively; effect size = 0.36 [small]). ICC values were 0.81 (CI 90% 0.64 – 0.90) for RSSAmean, for 0.15 (– 0.21 – 0.48) for RSSAbest, and 0.17 (CI 90% – 0.18 – 0.49) for RSSAdecrement.

Study 2 Long-term reliability (seasonal changes). Descriptive data of the four testing sessions and the SEM values expressed as CV cal" Table culated from two consecutive sessions are presented in l 1. The CV calculated increasing the time between tests (i.e., Pre vs. Mid and Pre vs. End) was similar to Pre vs. Early (data not shown). The mean CV calculated from all the four testing sessions (Pre, Early, Mid and End) was 0.9 % (CI 90% 0.8 – 1.1%) for RSSAmean, 1.2 % (CI 90% 1.1 – 1.4 %) for RSSAbest, and 29.8 % (CI 90% 26.1 – 34.7 %) for RSSAdecrement. The SWC values for RSSAmean RSSAbest and RSSAdecrement, were 0.5, 0.5 and 8.4%, respectively. The ICC values were 0.58 (CI 90% 0.38 – 0.74) for RSSAmean, 0.63 (CI 90% 0.49 – 0.75) for RSSAbest, and 0.49 (CI 90% 0.33 – 0.65) for RSSAdecrement. RSSA mean time decreased by a moderate and substantial – 2.2% " Fig. 1 A). This improvement was followed by from Pre to Early (l a small but likely 0.8 % worsening in RSSAmean in the Mid session, that persisted until the end of the competitive season. A similar change pattern was found for RSSAbest, with a small (– 1%) but likely substantial improvement between Pre and Early, followed by a small (0.9 %) and likely worsening in RSSAbest, and a trivial " Fig. 1 B). There was a change (– 0.2 %) between Mid and End (l small and very likely 22.7 % decrease in RSSAdecrement, from Pre " Fig. 1 C). to Early followed by trivial changes (0 to – 6.2%) (l

Study 3 Differences between competitive level and playing position. " TaDetailed results of the two-way ANOVAs are presented in l ble 2. No “competitive level” × “playing position” interactions were found, while main effects were significant. Professional players showed higher RSSA performance (RSSAmean, RSSAbest and RSSAdecrement) than amateur players. Defenders were players with the lower RSSA performance (RSSAmean and RSSAbest) compared to the other playing positions.

Discussion !

The differences found between players of different competitive levels and playing positions further support the construct validity of this test for measuring the ability to repeat shuttle-sprints in football players. However, among the various RSSA parameters, only the mean time showed sufficient reliability to detect large training-induced changes, but not smallest important differences.

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901

0.9 1.0 29.8 (0.7 – 1.1) (0.9 – 1.4) (17.5 – 28.5) 0.8 1.1 21.6 (0.7 – 1.1) (1.3 – 2.1) (29.4 – 49.2)

(CI 90%)

7.20 ± 0.13 6.92 ± 0.15 4.0 ± 1.7 7.16 ± 0.15 6.87 ± 0.17 4.3 ± 1.7 7.32 ± 0.13 6.94 ± 0.15 5.4 ± 2.2 RSSAmean (s) RSSAbest (s) RSSAdecrement (%)

7.22 ± 0.14 6.93 ± 0.15 4.2 ± 1.6

1.0 1.6 36.7

End – Mid

CV (CI 90%)

Mid – Early

CV (CI 90%) Mean ± SD

CV

End

Mean ± SD Mean ± SD

Mean ± SD

Early Pre

Parameters

Mid

Early – pre

(0.8 – 1.2) (0.8 – 1.3) (24.0 – 39.6)

Training & Testing

Table 1 Seasonal changes and standard error of measurement expressed as coefficient of variation (CV) for the three parameters calculated from the repeated-shuttle sprint ability (RSSA) test (n = 30)

902

Impellizzeri FM et al. Validity of a … Int J Sports Med 2008; 29: 899 – 905

Fig. 1 A to C Percentage changes between testing sessions (bars indicate uncertainty in the true mean change; 90 % confidence limits). Trivial area was calculated from the smallest worthwhile change determined as 0.2 times the between-athlete variation.

The results of the short-term reliability study (Study 1) showed that RSSAmean is the parameter with the greatest absolute reliability, while the percent decrement is the least reliable. The CV values found in the present study for RSSAmean is similar to the values showed by Fitzsimons et al. [10] who reported a CV of 0.8 % for the total time of a repeated-sprint ability running test consisting of 6 × 40-m sprints with 30 s of recovery. In the present study, the test included shuttle-sprints. A greater CV (1.8 %) has been reported by Wragg et al. [32] for the repeatedsprint ability test proposed by Bangsbo [5] which included 7 × 34.2-m sprints with direction changes. Consistent with previous investigations using both running and cycling sprints [10,

Training & Testing

Table 2 Differences in repeated-shuttle-sprint ability (RSSA) between competitive levels and playing positions

Competitive level Top-pro (n = 30) Mid-pro (n = 45) Amateur (n = 33) Main factor Post hoc analysis Playing position Defenders (n = 34) Fullbacks (n = 20) Midfielders (n = 33) Forwards (n = 21) Main factor Post hoc analysis Role X level interaction

RSSA best (s)

RSSA mean (s)

RSSA dec (%)

Mean ± SD

Mean ± SD

Mean ± SD

6.88 ± 0.19 6.83 ± 0.18 7.08 ± 0.23 p < 0001 TP = P < AM*

7.12 ± 0.17 7.20 ± 0.19 7.55 ± 0.25 p < 0001 TP = P < AM*

3.3 ± 1.5 5.1 ± 1.8 6.1 ± 2.0 p < 0.001 TP < MP = A

7.01 ± 0.23 6.83 ± 0.22 6.90 ± 0.21 6.91 ± 0.23 p = 0.012 (D > FU = M) = FO* p = 0.900

7.40 ± 0.28 7.18 ± 0.27 7.25 ± 0.27 7.26 ± 0.21 p = 0.004 D > FU = M = FO* p = 0.927

5.2 ± 2.4 4.8 ± 2.2 4.8 ± 1.9 4.8 ± 1.7 p = 0.930 p = 0.714

* p < 0.05; TP: top-professional players; P: mid-professional players; AM: amateur players; D: defenders; FU: fullbacks; M: midfielders; FO: forwards

17], the least reliable parameters calculated from the RSSA tests is the percent decrement. Indeed, in the present study, the CV found for the decrement in performance during the RSSA is similar to the 31.2 % reported by McGawley and Bishop et al. [17] during 6-s cycling sprints, and greater that 18.5 % reported by Fitzsimons et al. [10] during sprint running. Relative reliability showed very low ICC for RSSAbest and RSSAdecrement, while moderate ICC was found for RSSAmean. Therefore, the only parameter showing an absolute and relative reliability acceptable for monitoring football players is RSSAmean. The RSSAdecrement consistently showed the poorest reliability (absolute and relative) indicating that this parameter should not be used to evaluate football players. Indeed, the minimal detectable change [11], which is the individual minimum difference that can be interpreted as “real” with an acceptable probability level (84 %), resulted in 60 % for the RSSAdecrement, while the minimum detectable changes for RSSA mean and best were 1.6 and 2.6, respectively. Trivial to small differences were found between tests. However, all the subjects involved in this study were already familiar with the specific test protocol since it has been used for their routine testing and/or training exercises. With players not previously familiarized, one or two familiarization trials may be necessary to prevent a learning effect in repeated-sprint-based tests [25]. The CV determined from Pre to Early in the long-term reliability study were slightly greater than those obtained in the shortterm reliability study and the other seasonal phases. This was expected since, in the short-term reliability, it can be assumed that there is no true change in individuals’ measurements between trials, and during the competitive season physical capacities tend to remain relative stable at least at group level [29]. On the other hand, during the preseason period with players resuming training after a relative long rest period (three to four weeks), substantial changes in physical capacity can be more easily detected. Therefore, the CV obtained during the preseason training period was probably inflated by individual differences in training response [11], which can increase the CV. The RSSA mean and best time showed a likely substantial but small increase between the start and middle of the competitive season. This worsening of RSSA performance after the first part of the competitive season persisted until the end of the season. As the training programs included only one RSSA training ses-

sion a week during the competitive season, it is possible that this low specific volume was not sufficient to maintain this physical ability even with the additional in-week matches for international and national competitions (cups) played in the Early to Mid period. Alternatively, the fatigue accumulated in the first part of the competitive season may have reduced this physical ability. However, further studies are necessary to confirm these speculations. The absolute and relative SEM values obtained in the long-term reliability study can supply useful information to researchers and practitioners interested in examining the efficacy of specific interventions (training, nutritional, etc.). Indeed, the SEM can be used to calculate the sample size needed to detect changes over time frames similar to the ones used in the present study. Furthermore, these results can assist to better interpret the results of intervention studies, for example, by calculation of the individual responses to interventions [11]. The long-term reliability results can also be used to estimate the sensitivity of RSSA parameters to training interventions as expressed by the signalto-noise ratio (intervention-induced changes/typical error of measurement) [1]. In a previous study [7], we found a change in RSSAmean of 2.1% after 7 weeks of repeated-sprint based training completed at the beginning of the competitive season. The CV obtained in the present study from Early to Mid was about onethird of the changes induced on RSSAmean by the specific sprint training. This suggests an acceptable sensitivity of this parameter to detect changes determined by specific training interventions even during the competitive season. On the other hand, the RSSA best and decrement scores changed by 1 and 10% respectively, corresponding to values similar or lower than the CV found for these parameters in the reliability studies. This indicates a low sensitivity of these parameters, especially if compared to the RSSAmean. Therefore, only RSSAmean can be useful to quantify large changes induced by specific training strategies. However, as the reliability of RSSAmean was twice the small worthwhile change, it is unlikely that it can be used to detect smaller but important differences or individual changes. Furthermore, low ICCs were found for all the RSSA parameters. Therefore, other strategies such as the average of repeated tests should be used to improve the reliability of RSSA parameters including RSSAmean.

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Training & Testing

In a previous study we have already supplied evidence supporting the construct validity of this RSSA test protocol as an indicator of physical capacities actually involved during match play [21]. Specifically, we found significant correlations between this test and the amount of high-intensity activity completed during actual match play in professional football players. Based on these findings, it could be possible that the players of different playing position, that are characterized by different physical activity requirements during a match, would also display different results in this RSSA test. Various studies have described the physical match performance of soccer players during official games [8,18, 22]. The methodological differences between these studies make accurate comparison of these studies difficult. Specifically, previous studies have used different match analysis techniques, different definitions for running speed ranges in each locomotor category and varied sample sizes, all of which limit the ability to precisely evaluate the differences between these studies. However, these studies have consistently shown that defenders cover less distance in high-intensity running and sprinting compared to the other playing positions [8,18, 22]. These findings suggest that defense is probably the less physical demanding role as also indicated by the lower V˙O2max values reported by Puga et al. [20] for centerbacks (54.8 mL • kg–1 • min–1) compared to the other playing positions (> 60.6 mL • kg–1 • min–1). This has been also confirmed by Krustrup et al. [15] and Mohr et al. [18] who have shown that defenders are the players with the poorer performance in the yo-yo intermittent recovery test. As expected, the defenders showed the poorer performance in the RSSA test, which is consistent with the lower physical requirements during the match for this playing position. Mohr et al. [18] have also shown that top professional players completed greater high-intensity running distance during a game and have better yo-yo test performance than lower level players. Consistent with their findings, we found a lower RSSA performance in amateur compared to professional soccer players. Taken together the results of the present study further support the validity of the RSSA test for football players. In conclusion, this study showed that among the various parameters that can be calculated from the RSSA test, only the mean time to complete the 6 sprints (RSSAmean) displays sufficient sensitivity to detect large changes induced by specific training interventions, but its reliability also suggests a moderate ability to detect smallest but worthwhile differences or changes in individuals. The ability to discriminate between players of different competitive levels and playing position further support the construct validity of this test. However, a definitive confirmation of the validity of this test (exclusively RSSAmean) would require an examination of the correlation between changes in this test and changes in the ability to complete high-intensity activities during a game using controlled laboratory football-match simulations. Unfortunately, to the authors’ knowledge, this kind of validation has been not verified for any field test used in football. Therefore, further studies in this direction are warranted.

Acknowledgements !

We would like to thank Domenico Carlomagno, Maurizio Fanchini, Luca Morellini and Roberto Sassi for their support during the data collection. We would also like to thank the reviewers for the valuable comments and suggestions.

Impellizzeri FM et al. Validity of a … Int J Sports Med 2008; 29: 899 – 905

Affiliations 1 2

3

4

5

Neuromuscular Research Laboratory, Schulthess Clinic, Zurich, Switzerland Human Performance Laboratory, Mapei Sport Research Center, Castellanza, Italy School of Sport and Exercise Sciences, University of Rome Tor Vergata, Rome, Italy Team Sport Research Group, Facoltà di Scienze Motorie, Università Degli Studi di Verona, Verona, Italy Circulation and Medical Imaging, Norwegian University of Science and Technology, Faculty of Medicine, Trondheim, Norway

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