Secondary Logo

Share this article on:

Relationship Between Running Loads and Soft-Tissue Injury in Elite Team Sport Athletes

Gabbett, Tim J; Ullah, Shahid

Journal of Strength and Conditioning Research: April 2012 - Volume 26 - Issue 4 - p 953–960
doi: 10.1519/JSC.0b013e3182302023
Original Research

Relationship between running loads and soft-tissue injury in elite team sport athletes. J Strength Cond Res 26(4): 953–960, 2012—Although the potential link between running loads and soft-tissue injury is appealing, the evidence supporting or refuting this relationship in high-performance team sport athletes is nonexistent, with all published studies using subjective measures (e.g., ratings of perceived exertion) to quantify training loads. The purpose of this study was to investigate the risk of low-intensity (e.g., walking, jogging, total distances) and high-intensity (e.g., high acceleration and velocity efforts, repeated high-intensity exercise bouts) movement activities on lower body soft-tissue injury in elite team sport athletes. Thirty-four elite rugby league players participated in this study. Global positioning system data and the incidence of lower body soft-tissue injuries were monitored in 117 skill training sessions during the preseason and in-season periods. The frailty model (an extension of the Cox proportional regression model for recurrent events) was applied to calculate the relative risk of injury after controlling for all other training data. The risk of injury was 2.7 (95% confidence interval 1.2–6.5) times higher when very high–velocity running (i.e., sprinting) exceeded 9 m per session. Greater distances covered in mild, moderate, and maximum accelerations and low- and very low–intensity movement velocities were associated with a reduced risk of injury. These results demonstrate that greater amounts of very high–velocity running (i.e., sprinting) are associated with an increased risk of lower body soft-tissue injury, whereas distances covered at low and moderate speeds offer a protective effect against soft-tissue injury. From an injury prevention perspective, these findings provide empirical support for restricting the amount of sprinting performed in preparation for elite team sport competition. However, coaches should also consider the consequences of reducing training loads on the development of physical qualities and playing performance.

1School of Exercise Science, Australian Catholic University, Queensland, Australia

2School of Human Movement Studies, The University of Queensland, Queensland, Australia

3School of Human Movement and Sport Sciences, University of Ballarat, Victoria, Australia.

Address correspondence to Tim Gabbett, tim–gabbett@yahoo.com.au.

Back to Top | Article Outline

Introduction

The training-performance relationship is of particular importance to coaches to determine the optimum amount of training required to attain specific performance levels (4,11). Bannister et al. (6–8) proposed a statistical model to describe an athlete's response to a given training stimulus. According to this model, the performance of an athlete in response to training can be estimated from the difference between a negative function (fatigue) and a positive function (fitness). Studies have described the training-performance relationship as analogous with the dose-response relationship reported in pharmacological studies, with the primary goal of providing a training stimulus that maximizes performance potential and minimizes the negative consequences of training (i.e., injury, illness, fatigue, overtraining) (26).

Several studies have investigated the influence of training volume, intensity, and frequency on athletic performance, with performance generally improving with increases in training load (11,32). Studies of the training-performance relationship in individual sports (e.g., swimming and running) have found a positive relationship between both greater training volume and performance (12) and higher training intensity and performance (27). Foster et al. (11) studied 56 runners, cyclists, and speed skaters during 12 weeks of training and reported that a 10-fold increase in training load was associated with an approximately 10% improvement in performance. Moreover, Stewart and Hopkins (32) reported a significant relationship between greater training volume and performance (r = 0.50–0.80) and higher training intensity and performance (r = 0.60–0.70) in competitive swimmers. However, it has also been shown that negative adaptations to exercise training are dose related, with the highest incidence of illness and injury occurring when training loads are highest (10,15). In a recent study of Ironman distance triathletes, Vleck et al. (34) demonstrated a significant relationship between the amount of intensive training sessions performed and the incidence of overuse injury. These findings have been confirmed in studies of international rowers (35) and military personnel (29); higher training loads and running volumes were associated with higher injury rates. A limitation of all of these studies is that training intensities were subjectively determined, and total weekly volumes were not partitioned into the amount of running performed at low and high intensities.

In contrast to most individual sports, team sports (e.g., ice hockey, rugby, soccer, basketball, and lacrosse) are often characterized by short repeated sprints, rapid acceleration, deceleration, and changes of direction and an ability to produce high levels of muscular force extremely rapidly (17,31). As a result, team sport athletes are required to have well-developed speed, strength, muscular power, agility, and maximal aerobic power (V[Combining Dot Above]O2max). Previous studies of team sport athletes have reported significant positive relationships between training loads and training-injury rates (15,21), suggesting that the harder these athletes train, the more injuries they will sustain. Furthermore, reductions in training loads have been shown to reduce training-injury rates and result in greater improvements in V[Combining Dot Above]O2max (14). In a squad of high-performance basketball players, Anderson et al. (1) reported a significant relationship (r = 0.68) between training load and injury, suggesting that the periodization pattern of basketball training may be linked to the likelihood of injury. However, it has also been shown that team sport athletes who perform <18 weeks of preseason training before sustaining an initial injury are at increased risk of sustaining a subsequent injury, whereas players with a low off-season V[Combining Dot Above]O2max are at increased risk of sustaining an injury (19). Clearly, training for team sports reflects a balance between the minimum training load required to elicit an improvement in fitness and the maximum training load tolerable before sustaining marked increases in injury rates.

A considerable proportion of injuries sustained by team sport athletes are noncontact, soft-tissue issues that occur as a result of excessive training loads, inadequate recovery, and overtraining (13,16,20). These injuries, which are largely preventable, have the potential to impact on team selections and as a result may influence team performance. As team sport athletes use a combination of traditional conditioning, skills ‘drills,' and small-sided games in training, the quantification of running loads for these athletes has often proved difficult. Until recently, estimates of the physiological demands of training (and competition) activities were dependent on time-consuming and often laborious video tracking technology. With the introduction of microtechnology (e.g., global positioning systems [GPS] and accelerometers) into the high-performance sporting environment, sport scientists are now able to quantify the distance covered in discrete velocity bands, along with short duration, high-acceleration efforts; high-velocity sprints; and repeated high-intensity exercise bouts (18). Furthermore, research from our laboratory (22) has also recently validated this technology to automatically detect other physically demanding activities that regularly occur in team sport activities (e.g., the frequent tackles and collisions that occur in the rugby codes).

This technology has obvious applications for conditioning coaches responsible for designing and delivering periodized training programs; coaches can quickly identify athletes who have performed the ‘planned' training load, and those athletes who may be susceptible to injury or illness because of overtraining. Indeed, conditioning coaches often use GPS data to restrict the amount of high-intensity running athletes perform in a given training session or across training sessions. Although the potential link between running loads and soft-tissue injury is appealing, the evidence supporting or refuting this relationship in high-performance team sport athletes is nonexistent, with all published studies using subjective measures (e.g., ratings of perceived exertion) to quantify training loads. With this in mind, the purpose of this study was to document the running loads performed during training in elite team sport athletes. The second purpose was to investigate the relative risk of low-intensity (e.g., walking, jogging, total distances) and high-intensity (e.g., high acceleration and velocity efforts, repeated high-intensity exercise bouts) movement activities on lower body soft-tissue injury in these athletes.

Back to Top | Article Outline

Methods

Experimental Approach to the Problem

Global positioning system and lower body soft-tissue injury data were prospectively recorded over one season in elite National Rugby League (NRL) players. Data were collected during the preseason and in-season periods. The frailty model (an extension of the Cox proportional regression model for recurrent events) (25) was applied to calculate the relative risk of injury after adjusting for all other training data. It was hypothesized that higher total running volumes and greater amounts of very high–velocity running (i.e., sprinting) would be associated with an increased risk of lower body soft-tissue injury.

Back to Top | Article Outline

Subjects

Thirty-four elite team sport athletes (mean ± SD age, 23.6 ± 3.8 years; playing experience, 55.0 ± 72.2 NRL matches; and V[Combining Dot Above]O2max, 54.6 ± 2.4 ml·kg−1·min−1) participated in this study. All the participants were highly motivated players from the same professional rugby league club that regularly trained as part of the elite NRL squad. All the players were competing in the NRL competition and were free from injury at the commencement of the study. Along with the British Super League, the NRL is considered to be of the highest standard of rugby league competition in the world. All the participants received a clear explanation of the study, and written consent was obtained. The Institution Ethics Committee for Human Investigation approved all experimental procedures.

Movement was recorded by a GPS unit (MinimaxX, Catapult Innovations, Melbourne, Australia) sampling at 5 Hz. The GPS signal provided information on speed, distance, position, and acceleration. The GPS unit also included triaxial accelerometers and gyroscopes sampling at 100 Hz, to provide greater accuracy on speed and acceleration and information on physical contact and repeated high-intensity efforts (RHIEs). The unit was worn in a small vest, on the upper back of the players.

Data were categorized into (a) discrete acceleration bands, corresponding to mild (0.55–1.11 m·s−2), moderate (1.12–2.78 m·s−2), and maximal (≥2.79 m·s−2) accelerations (2); (b) discrete movement velocity bands, corresponding to very low–intensity (0–1 m·s−1), low-intensity (1–3 m·s−1), moderate-intensity (3–5 m·s−1), high-intensity (5–7 m·s−1), and very high–intensity (>7 m·s−1) velocities (9); and (c) RHIE bouts (18). An RHIE bout was defined as 3 or more high-acceleration, high-velocity, or contact efforts with <21 seconds recovery between efforts (3,18). Several authors have found the accuracy of GPS technology for measuring the movement of athletes to be very good, including Townshend et al. (33) who reported that 90.8% of GPS velocity measurements were <0.1 m·s−1 from actual velocity and that the mean distance error was 1.1 ± 0.3 m. The GPS units used in this study have been shown to have acceptable reliability and validity for estimating total distances and total distance covered at high intensities (28), whereas the accelerometers and gyroscopes embedded in the units have also been shown to offer a valid measurement of tackles and repeated efforts commonly observed in collision sports (22).

The GPS data and the incidence of lower body soft-tissue injuries were monitored over one NRL season. Data were collected from 117 skills training sessions during the preseason and in-season periods. The season lasted from November through September. Each player participated in up to 5 skills or conditioning sessions per week. The players were assigned to 1 of 4 positional groups; training for these groups differed relative to specific on-field skills and physiological demands. The 4 groups included hit-up forwards (props), wide running forwards (second row and locks), adjustables (hookers, halfbacks, five-eighths, and fullbacks), and outside backs (centers and wing). The players were allocated into the positional group at the beginning of the season and remained in that training group for the duration of the season. Skill sessions were designed to develop passing and catching skills, tackling technique, support play, defensive line speed and shape, and ball control. Although some differences existed in the intensity of activities performed throughout the season, the types of activities performed in the preseason training phase were similar to those in the early-competition and late-competition training phases. The duration of training sessions was typically between 60 and 100 minutes.

An injury was defined as any noncontact, lower body soft-tissue injury suffered by a player during a training session. The soft-tissue injuries in this study included muscular strains, tears, and tendon injuries. All the injuries were diagnosed by the club physiotherapist and were classified as a transient (no training missed), time loss (any injury resulting in missed training) (22), or a missed match (any injury resulting in a subsequent missed match) injury (23,24). Injury was verified by the presence of one of more of the following characteristics: pain, tenderness, swelling, and restricted range of motion.

Back to Top | Article Outline

Statistical Analyses

Descriptive statistics were expressed as means, ranges, and the standard errors (SEs) of running loads during the preseason, early-competition, and late-competition phases of the season. Injury incidence was calculated by dividing the total number of injuries by the total number of training hours and expressed as rates per 1,000 hours. The 95% confidence intervals (CIs) were calculated using the Poisson distribution, and the level of significance was set at p ≤ 0.05. The frailty model (an extension of the Cox proportional regression model for recurrent events) (25) was applied to calculate the relative risk of injury after adjusting for all other training data. The SPSS (version 18.0) and R (version 2.12.1) (30) software were used to analyze the data. Based on a total of 101 injuries from 3,978 player-sessions (i.e., 34 players participating in 117 training sessions), the calculated statistical power to establish the relationship between running loads and soft-tissue injuries was ≥80% (5).

Back to Top | Article Outline

Results

The running loads performed during the preseason, early-competition, and late-competition phases of the season are shown in Table 1 and Figure 1. Total distances were higher in the preseason than in the early- and late-competition training phases.

Table 1

Table 1

Figure 1

Figure 1

The incidence of transient soft-tissue injuries was 37.4 (95% CI 26.7–51.0) per 1,000 hours. The incidence of injury resulting in time loss was approximately 3 times higher (42.1 [95% CI 30.7–56.3] per 1,000 hours) than that resulting in a missed match (13.1 [95% CI 7.2–22.0] per 1,000 hours). Wide running forwards had higher incidence rates for no time loss injuries (81.2 [95% CI 50.2–124.0] per 1,000 hours) than the other positional groups (Table 2). However, injuries resulting in time loss (71.8 [95% CI 38.2–122.8] per 1,000 hours) and missed matches (33.1 [95% CI 12.2–72.2] per 1,000 hours) were higher in the outside backs than in the other positional groups.

Table 2

Table 2

The distance covered in mild, moderate and maximum accelerations, and at moderate intensity movement velocities were found to be significant risk factors for no time loss injuries. Similar factors (distances covered in mild, moderate and maximum accelerations, and low-intensity movement velocities) were also found to predict the incidence rates for time loss injuries. Because of the small number of cases, no factors were found to be significantly related with missed match injuries (Table 3).

Table 3

Table 3

When adjusting other factors, the frailty model showed that the risk of no time loss injury was 2.7 (95% CI 1.2–6.5) times higher when very high–intensity running exceeded 9 m per session, compared with ≤9 m per session (Table 4). The distances covered in mild, moderate, and maximum accelerations were found to be significantly related with no time loss injuries; the higher the acceleration, the lower the risk of no time loss injuries (0.2 [95% CI 0.1–0.4] for mild acceleration; 0.3 [95% CI 0.1–0.6] for moderate acceleration; 0.4 [95% CI 0.2–0.8] for maximum acceleration). Very low– and low-intensity movement velocities and moderate and maximum accelerations were found to be significantly related to the risk of time loss injuries. A 60% lower risk of time loss injury was observed (relative risk 0.4, 95% CI 0.2–0.9) when very low–intensity running exceeded 542 m per session, compared with ≤542 m per session and when the distance covered in moderate acceleration activity was >217 m per session, compared with ≤217 m per session. The relative risk of injury was lower (relative risk 0.5, 95% CI 0.2–0.9) when the distance covered in low-intensity running was >2,342 m per session and maximum acceleration distance was >143 m per session.

Table 4

Table 4

Back to Top | Article Outline

Discussion

This study is the first to investigate the relationship between running loads and lower body soft-tissue injury risk in elite team sport athletes. This study also adds to the training-injury literature by using a novel emerging technology (i.e., GPS and associated microtechnology) commonly used to monitor training loads in the elite team sport environment. The results of this study demonstrate that greater amounts of very high–velocity running (i.e., sprinting) are associated with an increased relative risk of lower body soft-tissue injury. In addition, the relative risk of sustaining a soft-tissue injury was significantly lower in players who covered greater distances at very low, low, and moderate intensities. From an injury prevention perspective, these findings provide empirical support for restricting the amount of sprinting performed in preparation for elite team sport competition.

The incidence and relative risk of soft-tissue injury was lower in players who covered greater distances at very low (i.e., 0–1 m·s−1), low (i.e., 1–3 m·s−1), and moderate (i.e., 3–5 m·s−1) intensities. These findings are in direct contrast to our hypothesis that greater running volumes would be associated with a higher incidence of injury. Previous studies of military personnel have demonstrated that higher running volumes were associated with higher injury rates (29). A limitation of that study was that total weekly volumes were estimated and were not partitioned into the amount of running performed at low and high intensities. With advances in player tracking technology, we were able to measure total distances, and distances covered at low, moderate, and high velocities, maximal acceleration efforts, and RHIE (i.e., sprinting and tackling) bouts. Given the importance of tackling, collisions, and repeated efforts to physical performance in rugby league (22), and the likelihood that these highly intense activities could contribute to injury risk, it was thought imperative to quantify these activities relative to soft-tissue injuries. Although the average total distances performed in this study would not be considered excessive and are likely much lower than those performed by other team sport athletes where a greater emphasis is on running as a conditioning modality (e.g., Australian football), the present findings demonstrate that the total distance covered and distances covered at low and moderate speeds offer minimal soft-tissue injury risk, with distances covered at lower intensities actually providing a protective effect against soft-tissue injury.

Greater than 9 m of very high–intensity running (i.e., high-velocity sprinting) per session was associated with a 2.7 times greater relative risk of injury than low amounts of high-speed running. These findings highlight that the volume of high-speed running contributes significantly to injury risk in elite team sport athletes. Although 9 m of very high–velocity running per session is negligible, it should be noted that the majority of sprint efforts performed in team sports are short duration, maximal acceleration efforts that do not achieve maximal velocities (31). Moreover, higher volumes of mild, moderate, and maximum acceleration efforts were associated with a reduced relative risk of soft-tissue injury. Although these findings provide empirical support for limiting the amount of high-velocity sprinting performed in training sessions, a fine balance exists between restricting training loads for injury prevention purposes and increasing training loads to physically prepare players for the most demanding periods of competition. Indeed, the finding that relative training intensity (i.e., meters per minute) was not associated with soft-tissue injury risk should encourage coaches to maintain intensity within the training environment.

It should be noted that although the overall incidence of soft-tissue training injuries resulting in a missed match was high (13.1 per 1,000 training hours), no running variables were significantly associated with missed match injury risk. Furthermore, none of the running variables increased the relative risk of time loss injury, with low- and very-low velocity running, and distances covered in mild, moderate, and maximum accelerations offering a protective effect against time lost through soft-tissue injury. Although various running variables were associated with transient injury risk, these findings indicate that the running loads described in this study had minimal influence over the incidence or relative risk of severe (i.e., time loss or missed match) injuries.

Although the incidence of training injuries in this study (13.1 per 1,000 training hours) was lower than that previously reported for match injuries (60.3 per 1,000 playing hours) (23), injury rates were of sufficient concern to warrant an understanding of training demands and the relative risk of injury with different running loads. Although wide running forwards had the greatest incidence of transient injuries, soft-tissue injuries resulting in lost training time and missed matches were greatest in the outside backs positional group. Interestingly, the outside backs positional group have also been reported to perform more high-speed running, achieve higher absolute and relative velocities, and be involved in a greater number of maximal acceleration efforts during competition than any of the other rugby league positional groups (18).

In conclusion, this study investigated the relative risk of low- and high-intensity running loads on lower body soft-tissue injury in elite team sport athletes. The results of this study demonstrate that greater amounts of very high–velocity running (i.e., sprinting) are associated with an increased relative risk of lower body soft-tissue injury. From an injury prevention perspective, these findings provide empirical support for restricting the amount of sprinting performed in preparation for elite team sport competition.

Back to Top | Article Outline

Practical Applications

The results of this study have several practical implications for the strength and conditioning coach. Although it has been suggested that high running volumes increase the risk of soft-tissue injury, evidence supporting the link between running loads and soft-tissue injury is far from substantive. Greater distances covered in very low, low, and moderate speed running were associated with a lower risk of soft-tissue injury, whereas greater amounts of very high–velocity running (i.e., sprinting) were associated with an increased risk of soft-tissue injury. Restricting the amount of sprinting performed in preparation for elite team sport competition may reduce the risk of soft-tissue injury; however, coaches should also consider the consequences of reducing training loads on the development of physical qualities and playing performance.

Back to Top | Article Outline

References

1. Anderson L, Triplett-McBride T, Foster C, Doberstein S, Brice G. Impact of training patterns on incidence of illness and injury during a women's collegiate basketball season. J Strength Cond Res 17: 734–738, 2003.
2. Aughey RJ, Falloon C. Description of accelerations in Australian rules football: a new insight into high intensity activity (abstract). Coach Sport Sci J 3:16, 2008.
3. Austin DJ, Gabbett TJ, Jenkins DG. Repeated high-intensity exercise in professional rugby league. J Strength Cond Res 25:1898–1904, 2011.
4. Avalos M, Hellard P, Chatard JC. Modeling the training-performance relationship using a mixed model in elite swimmers. Med Sci Sports Exerc 35: 838–846, 2003.
5. Bahr R, Holme I. Risk factors for sports injuries—A methodological approach. Br J Sports Med 37: 384–392, 2003.
6. Bannister EW, Calvert TW. Planning for future performance: implications for long term training. Can J Appl Sports Sci 5: 170–176, 1980.
7. Bannister EW, Calvert TW, Savage MV, Bach T. A systems model of training for athletic performance. Aust J Sports Med 7: 57–61, 1975.
    8. Bannister EW, Good P, Holman G, Hamilton CL. Modeling the training response in athletes. In: The 1984 Olympic Scientific Congress Proceedings. Sport and Elite Performers. D.M Landers, ed. Champaign, IL: Human Kinetics, 1986, vol. 3, pp. 7–23.
    9. Dwyer DB, Gabbett TJ. Global positioning system data analysis: velocity ranges and a new definition of sprinting for field sport athletes. Journal of Strength and Conditioning Research, in press.
    10. Foster C. Monitoring training in athletes with reference to overtraining syndrome. Med Sci Sports Exerc 30: 1164–1168, 1998.
    11. Foster C, Daines E, Hector L, Snyder AC, Welsh R. Athletic performance in relation to training load. Wisc Med J 95: 370–374, 1996.
    12. Foster C, Daniels JT, Yarbrough RA. Physiological and training correlates of marathon running performance. Aust J Sports Med 9: 58–61, 1977.
    13. Gabbett TJ. Incidence of injury in semi-professional rugby league players. Br J Sports Med 37: 36–43, 2003.
    14. Gabbett TJ. Influence of training and match intensity on injuries in rugby league. J Sports Sci 22: 409–417, 2004.
    15. Gabbett TJ. Reductions in pre-season training loads reduce training injury rates in rugby league players. Br J Sports Med 38: 743–749, 2004.
    16. Gabbett TJ. Changes in physiological and anthropometric characteristics of rugby league players during a competitive season. J Strength Cond Res 19: 400–408, 2005.
    17. Gabbett TJ. Science of rugby league football: A review. J Sports Sci 23: 961–976, 2005.
    18. Gabbett TJ. Sprinting patterns of National Rugby League competition. J Strength Cond Res, in press.
    19. Gabbett TJ, Domrow N. Risk factors for injury in sub-elite rugby league players. Am J Sports Med 33: 428–434, 2005.
    20. Gabbett TJ, Domrow N. Relationships between training load, injury, and fitness in sub-elite collision sport athletes. J Sports Sci 25: 1507–1519, 2007.
    21. Gabbett TJ, Jenkins DG. Relationship between training load and injury in professional rugby league players. J Sci Med Sport 14: 204–209, 2011.
    22. Gabbett T, Jenkins D, Abernethy B. Physical collisions and injury during professional rugby league skills training. J Sci Med Sport 13: 578–583, 2010.
    23. Gibbs N. Injuries in professional rugby league: A three-year prospective study of the South Sydney professional rugby league football club. Am J Sports Med 21: 696–700, 1993.
    24. Gissane C, Jennings D, Kerr K, White J. Injury rates in rugby league football: Impact of change in playing season. Am J Sports Med 31: 954–958, 2003.
    25. McGilchrist CA, Aisbett CW. Regression with frailty in survival analysis. Biometrics 47: 461–466, 1991.
    26. Morton RH. Modelling training and overtraining. J Sports Sci 15: 335–340, 1997.
    27. Mujika I, Chatard JC, Busso T, Geyssant A, Barale F, Lacoste L. Effects of training on performance in competitive swimming. Can J Appl Physiol 20: 395–406, 1995.
    28. Petersen C, Pyne D, Portus M, Dawson B. Validity and reliability of GPS units to monitor cricket-specific movement patterns. Int J Sports Physiol Perform 4: 381–393, 2009.
    29. Pope R, Firman J, Prigg S. Cost savings associated with injury prevention in army basic training. In: Proceedings of the Fifth International Olympic Committee World Congress on Sport Sciences, 1999, pp. 228.
    30. R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2011. ISBN 3-900051-07-0, URL <http://www.R-project.org/>. Accessed date February 25, 2011.
    31. Spencer M, Bishop D, Dawson B, Goodman C. Physiological and metabolic responses of repeated-sprint activities: specific to field-based team sports. Sports Med 35: 1025–1044, 2005.
    32. Stewart AM, Hopkins WG. Seasonal training and performance of competitive swimmers. J Sports Sci 18: 873–884, 2000.
    33. Townshend AD, Worringham CJ, Stewart IB. Assessment of speed and position during human locomotion using nondifferential GPS. Med Sci Sports Exer 40: 124–132, 2008.
    34. Vleck VE, Bentley DJ, Millet GP, Cochrane T. Triathlon event distance specialization: Training and injury effects. J Strength Cond Res 24: 30–36, 2010.
    35. Wilson F, Gissane C, Gormley J, Simms C.A. 12-month prospective cohort study of injury in international rowers. Br J Sports Med 44: 207–214, 2010 .
    Keywords:

    injury risk; running loads; global positioning system; rugby league; injury prevention

    Copyright © 2012 by the National Strength & Conditioning Association.