Rugby league is a contact team sport and is intermittent in nature, with periods of high-intensity activity (running, tackling) and low-intensity recovery (walking, jogging, and standing). Games are divided into 2 halves of 30 and 40 minutes for junior and senior players, respectively. Competitive play has been shown to generate heart rates (HRs) equating to 84.3 ± 4.8% (5) and 86.7 ± 4.4% (6) of maximal values. Rugby league therefore can be assumed to place a significant demand on aerobic metabolism and duly requires high levels of aerobic fitness (3,8-10,13,24).
To produce efficient training sessions, coaches of sports teams seek multiple component training methods to enable fitness and technical and tactical elements to be trained simultaneously. In recent years, small-sided games (SSGs) have emerged as one such method, which, although generic in their function, can be made sport-specific to accommodate the rules, movement patterns, and physical demands of a particular sport. In adopting this method, coaches are being persuaded that SSGs can be conducted at intensities sufficient to enable aerobic adaptations and allow transfer of skill from a pressurized training environment to a competitive environment. To achieve aerobic conditioning through SSGs, a high-intensity interval-training format has been adopted in soccer (4,16,18-20,25), rugby union (15), and rugby league (11,12). The majority of soccer SSG studies have adopted a framework of 4-minute SSGs at 90-95% of maximal heart rate (HRmax) with 3 minutes of active recovery between games at ∼70% HRmax (4,16,19,20). This format follows traditional high-intensity interval training for aerobic conditioning (1), which has been shown to increase o2max (17) while simultaneously providing an ecologically valid training method (19) and a more motivating training stimulus than traditional aerobic conditioning methods (20). Of note, it has been suggested that the training intensity of SSGs should be greater than that elicited during competitive match play to facilitate conditioning (19).
Previous studies have found that SSG exercise intensity can be manipulated by altering playing area size and player number. Rampinini et al. (26) reported that, although HR responses were similar between smaller and medium-sized playing areas during soccer SSGs, values were significantly higher when played in a larger area. Conversely, Tessitore et al. (28) reported that a smaller playing area size (30 × 40 m) elicited a higher HR response than a larger playing area size (50 × 40 m) in 6v6 soccer SSGs, which the authors suggested was a result of greater man-to-man defending in the smaller-sized area. Moreover, other studies that have investigated the combined effects of altering playing area size and player number typically have found that decreasing player number and increasing playing area size increased HR intensity (25,26). However, caution should be taken when comparing such studies owing to the use of inconsistent playing area sizes (25,26), which does not allow the isolated effect of changing the number of players to be observed (20).
Due concern also needs to be given to the reliability of SSGs so that coaches can be confident in their ability to provide a consistent aerobic training stimulus. Little and Williams (22) have reported small test-retest differences in HRs across soccer SSGs with different player numbers and playing area sizes (coefficients of variance of <3% and ratio limits of agreement of 1.8-3.8% HRmax). Similar findings by Hill-Haas et al. (18) also have indicated that soccer SSGs provide a reliable aerobic conditioning stimulus in adolescent soccer players, with a technical error of <5% in mean HR, total distance covered, and the percentage of total time moving at 0-6.9 km·h−1 during soccer-specific SSGs. However, to date, there has been no reliability analysis conducted on rugby league-specific SSGs; therefore, it is unclear if such games produce consistent stimuli to elicit aerobic adaptations on a test-retest basis. Furthermore, research to date has focused on senior rugby league (11,12) and rugby union players (15), with less scrutiny of the effects of SSGs on junior rugby league players. Finally, there has been no analysis of the effect of age on SSG variables, despite the finding that junior rugby league players of different ages adapt differently to a given training stimulus (11,14). Accordingly, the purpose of this study was to examine the effects of altering playing area size and player number on HR responses in junior rugby league SSGs and the reproducibility of these responses over 2 repeated trials.
Experimental Approach to the Problem
All participants performed a laboratory-based peak oxygen uptake (o2peak) test 1 week prior to the field testing. The field testing was conducted across 2 evening training sessions at the same time of day during the competitive season, on the same outside grass playing surface, and under similar weather conditions. The SSGs were conducted with the player numbers and playing area sizes commonly used in high-level junior rugby league training, yielding 6 different conditions. Each SSG condition was administered on 2 separate occasions, 7 days apart, with all 4v4 SSGs being carried out in the first session and 6v6 SSGs in the second session. In the first session, players in the 12- to 13-year-old age group performed 2 trials of the game in the small, medium, and large playing areas, respectively. This order then was reversed for players in the 15- to 16-year-old age group. In the second session the order of playing area sizes were reversed in each age group to minimize the occurrence of an ordering effect. Furthermore, a recovery of 3 minutes was permitted between each game. Therefore, all participants took part in a total of 12 SSGs. The intensity of each SSG was determined as a mean percentage of HRmax because this method has been shown to be a practical and valid measurement within soccer SSGs (23).
It was hypothesized that 4v4 SSGs would elicit a greater HR intensity than 6v6 SSGs in each playing area size. The large playing area was hypothesized to elicit a higher HR intensity than the medium and small sizes and there would be no difference in HR intensity (% HRmax) as a result of age. It was also hypothesized that there would be no difference in HR intensity between trials.
Twenty-two junior male rugby league players (mean age: 14.5 ± 1.5 years; stature: 172.5 ± 11.4 cm; body mass: 67.8 ± 15.1 kg; o2peak: 53.3 ± 5.6 mL·kg−1·min−1; HRmax: 198 ± 7.8 beats·min−1) volunteered to participate in the study. The players trained in 2 discrete age categories within a professional club: 12 to 13 (n = 8) and 15 to 16 (n = 14) years (Table 1). All players were well trained and participated in a structured conditioning program consisting of resistance training and field conditioning. Participants and their parents or guardians were fully informed of the experimental risks and signed an informed consent document prior to participating. The investigation was approved by an institutional Research Ethics Committee.
o2peak was determined from metabolic responses to a running protocol on a motorized treadmill (HP Cosmos, Pulsar, HP Cosmos, Nussdorf-Traunstein, Germany). Following a 3-minute warm-up at 8 km·h−1, participants ran for 1 minute at a constant speed (12 km·h−1 and 10 km·h−1 for the 15-16 and 12-13 year olds, respectively) with the treadmill set at 0% gradient. Thereafter the gradient was increased by 2% every minute until voluntary exhaustion occurred. Expired air was collected continuously using a previously calibrated gas analysis system (Cosmed Quark b2, Cosmed, S.r.l., Rome, Italy). On completion, the o2 data were averaged over 15 seconds, with o2peak defined as the highest oxygen consumption during the test and confirmed if either HR had reached within 5% of age-predicted maximum or a respiratory exchange ratio (RER) >1.15 was obtained (27). Although not assessed in this study, such a protocol previously has been demonstrated to elicit reliable data (R = 0.90) among young boys (29). HR was recorded continuously during the test (Polar Team System, Polar, Oy, Finland) and averaged over 5 seconds. HRmax was taken as the highest HR achieved and was used to represent SSG intensity as a percentage of HRmax (% HRmax).
HR responses were recorded (Polar Team System) during all 12 SSGs; 4v4 and 6v6 played in a structured sequence on 15 × 25 m (small), 20 × 30 m (medium), and 25 × 35 m (large) playing area sizes on 2 separate occasions. In the manner described by Helgerud et al. (16) and Hoff et al. (19), the SSGs lasted 4 minutes (with 3 minutes of active rest between each game in which players could drink ad libitum) and had standardized rules refereed by a qualified coach. The SSG was “offside touch” and the rules were as follows: The team in possession maintained the ball until touched by a defender, a try was scored, or an error was made (dropped ball, ball out of play), following which possession was turned over; running with the ball was permitted; passes in any direction were permitted; a tackle was simulated by a 2-handed touch from a defender; attacking players were only allowed 5 m offside from the ball carrier; and play was restarted after each touch by tapping the ball with the foot to recommence play. Players were habituated to SSG training and were verbally encouraged to maintain high work intensities throughout each game. Extra rugby balls were placed on each try line, ball boys were placed on the side lines, and a quick restart was encouraged to maximize the time the ball was in play.
Players' mean HRs for each SSG were converted to a percentage of their HRmax obtained from the laboratory-based treadmill test. Descriptive statistics (mean ± SD) were calculated for HRmax values for the sample as a whole and for each age group. The distributions of the HRmax variables were checked for normality via the Shapiro-Wilk statistic and for homogeneity of variance via the Levene statistic. These assumptions were found to be satisfied. Two 3-way analyses of variance (ANOVAs) with repeated measures were conducted to assess the variability of HR responses resulting from the 3 factors (player number, playing area size, trial) in each age group, with alpha set at 0.05. Assumptions of sphericity were assessed using the Mauchly's test of sphericity. Post hoc analyses, where appropriate, were conducted via multiple Bonferroni-adjusted t-tests. The reliability of the SSGs was assessed through intraclass correlation coefficients (ICC) and the 95% limits of agreement (LoA) technique (2).
The SSGs performed within this study elicited average HR intensities ranging from 85.0 to 91.5% HRmax (Table 3), with the 4v4 SSGs in the 15 to 16 age group eliciting higher than 90% HRmax for all playing area sizes (Table 2). The 15 to 16 age group 3-way interaction (player number × playing area size × trial) was significant (F2,40 = 40.4, p < 0.001), although this was solely a result of significant variability occurring between trials in the small 6v6 SSG (p < 0.05).
Analysis of variance indicated that there was a significant main effect of player number in the 15 to 16 age group (F1,13 = 40.4, p < 0.001), with mean HR being higher in the 4v4 (90.6% HRmax) than the 6v6 SSGs (86.2% HRmax), independent of playing area size (Table 2). There were no significant differences in HR intensity between the 4v4 (88.1% HRmax) and 6v6 (89.3% HRmax) conditions in the 12 to 13 age group (F1,7 = 2.987, p = 0.128) (Table 3).
Playing Area Size
In the 15 to 16 age group, there was no significant effect of playing area size with mean HRs of 87.4, 88.8, and 89.0% HRmax in the small, medium, and large playing areas, respectively. There was also no significant effect in the 12 to 13 age group (F2,14 = 1.0, p = 0.13) with %HRmax values of 88.2, 88.7, and 89.3% for small, medium, and large playing areas, respectively (Table 3).
The variability from trials was not significant in the 15 to 16 (F1,13 = 1.9, p = 0.20) and 12 to 13 (F1,7 = 1.0, p = 0.35) age groups. The 4v4 medium SSG was the most reliable in the 15 to 16 age group (ICC = 0.91 and LoA = 0.4 ± 0.5% HRmax). The 4v4 large (ICC = 0.99 and LoA = 0.8 ± 0.7% HRmax) and 6v6 medium (ICC = 0.94 and LoA = 0.8 ± 2.9% HRmax) SSGs produced the most consistent data in the 12 to 13 age group. When the 2 groups' data were combined, the 4v4 large and medium and the 6v6 medium were the most reliable conditions, having the narrowest LoA and highest ICC between SSG trial 1 and 2 (Table 4).
The SSGs performed within this study elicited mean HR intensities higher than 85% HRmax, which are considered to be both “high” in competitive junior rugby league (6) and above match intensity (5). The 4v4 SSGs elicited an average HR intensity higher than 90% HRmax within the older players (15-16 years), demonstrating that SSGs specific to rugby league can elicit the recommended SSG HR intensity for aerobic conditioning (16,19). The mean HR responses during the 4v4 SSGs were consistently higher than those of the 6v6 SSGs, albeit among the older junior players only. Although we are not able to quantify this, a likely explanation for the difference in HR response between 4v4 and 6v6 SSGs was the occurrence of a greater frequency of contact with the ball and overall individual involvement when player number was reduced (21). Although it is unsatisfactory to compare directly the physiological responses of sport-specific SSGs, this effect is consistent with previous research among soccer players (23,25,26), Moreover, that we observed no difference in mean HR between the 4v4 and 6v6 SSGs in our 12 to 13 age group is of more immediate interest and may reflect a developmental issue with respect to spatial awareness.
Because adults exhibit a much better distinction of extrapersonal space when compared to children (7), in an applied context this might translate into younger players demonstrating a poorer spatial awareness compared to older players during SSGs wherein a defined area of play is used. This would cause them, regardless of the player number and therefore the amount of space available, to self-restrict the area in which they work. Additionally, such individuals might be more inclined to focus their attention on the point of interest-that is, the ball or the player holding the ball-rather than events occurring elsewhere. Accordingly, our data tentatively support the anecdotal evidence posited by coaches that young players tend to play in a confined area even when considerable space is available to them. On this theme, it was hypothesized that increasing playing area size would result in an increase in intensity from players having more space in which to play and having more scope to be exertive. However, in both the 15 to 16 and 12 to 13 age groups, there was no significant difference in the observed HRs between the 3 playing area sizes. Taken at face value, this finding suggests that the area sizes typically used by rugby league coaches do not independently contribute to the challenge of optimizing SSG intensity for aerobic conditioning among junior players.
The interaction between player number and area size revealed no effect on mean HR, although when the variance over the 2 trials also was considered, the resulting 3-way interaction was significant in the 15 to 16 age group (Table 4). Although we identified this was owing to a significant mean difference (decrease) occurring between trials in the small 6v6 SSG only, other than suggesting that the relatively restricted space in this condition might have been a factor, it is difficult to explain. This is particularly so because the mean HR responses in all the other SSGs were found to be consistent (within ± 1.9 %HRmax) over the repeated trials. Nonetheless, the issue of the reliability of the SSGs deserves further scrutiny.
From a coach's perspective, it is imperative that SSGs can stimulate physiological responses that are reproducible so that they can use SSGs as part of a periodized training program. Of note, such consistency needs to be achieved by most, if not all, players and the extent of this is best reflected in the random error component of the 95% LoA statistic. In considering the data overall, and in the absence of any comparable figures for rugby league, our LoA enable a favorable interpretation of the reliability of the HR responses in all the SSGs apart from the small 6v6 condition (see earlier). This judgment is qualified on the basis that, in the worse-case scenario (6v6 large), HRs (for 95% of the players) were no more than approximately 5% HRmax higher or lower in trial 2 compared to trial 1, reflecting that, in most cases, intensities of greater than 85% HRmax were achieved in both trials. This pattern was found to be independent of age group, albeit with the exception referred to previously and the 4v4 medium SSG played by the 12 to 13 year olds, for which the variability was up to about 7% HRmax between trials. Particular SSGs could be singled out in each group as being the most reliable-for example, the 4v4 large (12-13) and 4v4 medium (15-16), with random error between trials being less than 3% HRmax, but it would be difficult to provide a viable explanation for this.
SSGs are being used frequently as a conditioning stimulus within rugby league across all levels. The purpose of the current research is to develop a format for using SSGs in a way that will enable coaches to optimize such conditioning. The present study is the first to report the HR responses and repeatability of these responses to altering playing area size and player number in rugby league-specific SSGs within 2 discrete junior age groups. Although the majority of SSG studies do not state SSG specifications, the authors acknowledge that the off-side nature of the SSGs utilized within this study is a potential limitation. However, a conditioning SSG that incorporates key game-related skills (evasion, support play, peripheral vision, spatial awareness, game awareness) and is widely utilized within rugby league training was selected through consultation with senior coaches within the professional game.
The findings demonstrate that SSGs can elicit high and repeatable HR responses adequate for aerobic conditioning. Altering playing area size had no effect, whereas player number was found to elicit different HR responses for junior players of different ages, suggesting that coaches should be cognizant of the potential mediating effect that age and player number might impose upon SSGs-specifically, that older junior players experienced a higher training stimulus from 4v4 SSGs than 6v6 SSGs and that younger junior players experienced the same training stimulus in both 4v4 and 6v6 SSGs. Therefore, conditioning coaches should be aware that 4v4 SSGs elicit a stronger aerobic conditioning stimulus than 6v6 SSGs in older junior players and that altering the player number will not affect the SSG intensity in younger junior players. Moreover, coaches can be confident that utilizing SSGs within their training programs will provide a consistent training stimulus.
The authors would like to acknowledge the financial support for this study provided by the Rugby Football League (RFL).
1. Billat, LV. Interval training for performance: A scientific and empirical practice. Special recommendations for middle- and long-distance running. Part I: Aerobic interval training. Sports Med
31: 13-31, 2001.
2. Bland, JM and Altman, DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet
8: 307-310, 1986.
3. Brewer, J, Davis, J, and Kear, JA. A comparison of the physiological characteristics of rugby league forwards and backs. J Sports Sci
12: 158, 1994.
4. Chamari, K, Hachana, Y, Kaouech, F, Jeddi R, Moussa-Chamati, I, and Wisloff, U. Endurance training and testing with the ball in young elite soccer players. Br J Sports Med
39: 24-28, 2005.
5. Coutts, A, Reaburn P, and Abt, G. Heart rate, blood lactate concentration and estimated energy expenditure in a semi- professional rugby league team during a match: A case study. J Sports Sci
21: 97-103, 2003.
6. Estell, J, Lord, P, Barnsley, L, Shenstone, B, and Kannangara, S. The physiological demands of rugby league. In: Proceedings of the Australian Conference of Science and Medicine in Sport. Sports Medicine Australia. Canberra, 1996. pp. 388-389.
7. Gabbard, C, Cordova, A, and Ammar, D. Estimation of reach in peripersonal and extrapersonal space: A developmental view. Dev Neuropsychol
32: 749-756, 2007.
8. Gabbett, TJ. Physiological and anthropometric characteristics of amateur rugby league players. Br J Sports Med
34: 303-307, 2000.
9. Gabbett, TJ. Physiological characteristics of junior and senior rugby league players. Br J Sports Med
36: 334-339, 2002.
10. Gabbett, TJ. Physiological and anthropometric characteristics of junior rugby league players over a competitive season. J Strength Cond Res
19: 764-771, 2005.
11. Gabbett, TJ. Performance changes following a field conditioning program in junior and senior rugby league players. J Strength Cond Res
20: 215-221, 2006.
12. Gabbett, TJ. Skill-based conditioning games as an alternative to traditional conditioning for rugby league players. J Strength Cond Res
20: 309-315, 2006.
13. Gabbett, TJ and Herzig, PJ. Physiological characteristics of junior elite and sub-elite rugby league players. Strength Cond Coach
12: 19-24, 2004.
14. Gabbett, TJ, Johns, J, and Rieman, M. Performance changes following training in junior rugby league players. J Strength Cond Res
22: 910-917, 2008.
15. Gamble, PA. Skill-based conditioning games approach to metabolic conditioning for elite rugby football players. J Strength Cond Res
18: 491-497, 2004.
16. Helgerud, J, Engen, LC, Wisloff, U, and Hoff, J. Aerobic endurance training improves soccer performance. Med Sci Sports Exerc
17. Helgerud, J, Hoydal, K, Wang, E, Karlsen, T, Berg, P, Bjerkaas, M, Simonsen, T, Helgesen, C, Hjorth, N, Bach, R, and Hoff, J. Aerobic high-intensity intervals improve VO2
max more than moderate training. Med Sci Sports Exerc
39: 665-671, 2007.
18. Hill-Haas, S, Coutts, A, Roswell, G, and Dawson, B. Variability of acute physiological responses and performance profiles of youth soccer players in small-sided games. J Sci Med Sport
11: 487-490, 2008.
19. Hoff, J, Wisloff, U, Engen, LC, Kemi, OJ, and Helgerud, J. Soccer specific aerobic endurance training. Br J Sports Med
36: 218-221, 2002.
20. Impellizzeri, FM, Marcora, SM, Castagna, C, Reilly, T, Sassi, A, Iaia, FM, and Rampinini, E. Physiological and performance effects of generic versus specific aerobic training in soccer players. Int J Sports Med
27: 483-492, 2006.
21. Jones, S and Drust, B. Physiological and technical demands of 4 v 4 and 8 v 8 games in elite young soccer players. Kinesiology
39: 150-156, 2007.
22. Little, T and Williams, AG. Suitability of soccer training drills for endurance training. J Strength Cond Res
20: 316-319, 2006.
23. Little, T and Williams, A.G. Measures of exercise intensity during soccer training drills with professional soccer players. J Strength Cond Res
21: 367-371, 2007.
24. Meir, R, Newton, R, Curtis, E, Fardell, M, and Butler, B. Physical fitness qualities of professional rugby league football players: Determination of positional differences. J Strength Cond Res
15: 450-458, 2001.
25. Owen, A, Twist, C, and Ford, P. Small-sided games: The physiological and technical effect of altering pitch size and player numbers. Insight
7: 50-53, 2004.
26. Rampinini, E, Impellizzeri, FM, Castagna, C, Abt, G, Chamari, K, Sassi, A, and Marcora, SM. Factors influencing physiological responses to small-sided soccer games. J Sports Sci
25: 659-666, 2006.
27. Rowland, TW. Aerobic exercise testing protocols. In: Rowland, TW, ed. Paediatric laboratory exercise testing
. Champaign, Illinois: Human Kinetics, 1993. pp. 19-42.
28. Tessitore, A, Meeusen, R, Piacentini, MF, Demarie, S, and Capranica, L. Physiological and technical aspects of 6-a-side soccer drills. J Sports Med Phys Fitness
46: 36-43, 2006.
29. Turley, KR, Rogers, DM, Harper, KM, Kujawa, KI, Wilmore, JH. Maximal treadmill versus cycle ergometry testing in children: Differences, reliability and variability of responses. Ped Ex Sci
7: 49-60, 1995.
Keywords:© 2010 National Strength and Conditioning Association
integrated training; aerobic conditioning; specificity