Warren et al.: A free-running case study
Serb J Sports Sci 7(1): 25-30
Serbian Journal of Sports Sciences
2013, 7(1): 25-30
ISSN 1820-6301 ID 198165772
UDC 796.4
Original article Received: 07 Jan 2013 Accepted: 16 Mar 2013
A FREEFREE-RUNNING CASE STUDY James Warren1, Jonathan Sinclair2 & Lindsay Bottoms1 School of Health, Sport and Bioscience, University of East London, UK. Division of Sport Exercise and Nutritional Sciences, University of Central Lancashire, UK. 1
2
Abstract Free-running has recently spread over the digital media and has since become an official sport. Despite this increase in popularity there is no peer-reviewed literature on the physiology and anthropometry of the athletes or the physical demands of the sport. This study aimed to define free-running and explore some of the physiological characteristics of the athletes and the sport, by undertaking the assessment of anthropometric data and vertical jump performance in 7 free-runners; in addition, GPS information was gathered from 3 training sessions for one free-runner. The free-runners in the present study displayed high power output as result of high vertical jump performance. They also displayed low levels of body fat and low body mass. The GPS data illustrated that free-running is an intermittent sport relying heavily on the phosphagenic energy system; therefore, free-runners should focus their training utilising this energy system. Another outcome from the research is the suggestion that future studies should trial different equipment to monitor the physiological demands and intensity of the sport due to particularly high-intensity short bursts of energy utilised.
Key words: Free-running, profiling, training, case study
INTRODUCTION Free-running is a recently developed sport and a global phenomenon that began official competition in 2008, when the first annual games were held in London, England [1]. Prior to this, free-running was an unknown discipline which originated in France as L’Art du Déplacement in the 1980’s. L’Art du Déplacement derived from the French Military training Parcours du Combattant, a movement-based obstacle course pioneered by Georges Herbert and inherited by Raymond Belle and his son David Belle. This discipline then became Parkour [6, 7, 19]. Parkour was extended child’s play to David Belle, Sebastien Foucan and other associates. They formed the Yamakasi training group in the Parisian suburbs drawing influences from Bruce Lee and Jackie Chan, and developed parkour as a spiritual and physical mastery of one’s own movement seeking to challenge one’s self [6, 7]. 2001 yielded the first media exposure of parkour in Yamakasi: Les Samouraïs des Temps Modernes initiating a divide in the discipline. Further media exposure provoked the appearance of the term Free-running among English speaking audiences, especially after the documentary Jump London in 2003 [5, 6, 7]. Profiling the performance of athletes has been conducted in a variety of well established competitive sports such as artistic gymnastics [13, 21, 25], rugby league [8, 9] and sport rock climbing [17, 23, 26]. However, free-running is a fledgling sport with no official definition or classification. Free-running has only recently emerged from France through media exposure and has accelerated from a hobby based on military training to an official competitive sport. The concept of free-running is fluid, as are the movements and dynamics and therefore it is subject to much debate [6, 7]. Although as of 2008 competitions take place [1], many athletes participate in free-running at a non-competitive, amateur level. As it is a recently developed sport, there is limited peer-reviewed literature defining the biomechanical or physiological demands at either a professional competitive or amateur level. Subsequently, there is also no peer-reviewed literature defining physiological or anthropometric characteristics of free-running athletes. While profiling sports and athletes is advantageous to those involved, the benefits have not been reaped in all sports, especially in those less recognised. It is obvious that further investigation into newly evolving sports is required; clearly outlining the demands of an emerging sport and comparing the performance of the athletes to those of similar sports will help identify appropriate testing procedures. This will then enable quantification of the athletes’ performance in standardised quantitative measurements such as body fat 25
Warren et al.: A free-running case study
Serb J Sports Sci 7(1): 25-30
percentage, or standardise power output or power to weight ratio. Studies into free-running will identify the sport within the research community, exposing it to further, more detailed research and advancing its practice. Therefore, the aim of this case study was to a) clarify what free-running is and which characteristics the sport requires of the athletes who engage in its practice, and b) explore the metabolic demands the sport places on the athletes. This case study will be of huge value by bringing free-running and freerunners into the scientific research community as a sport and a population. It will provide general information on strength and power, anthropometry of the athletes, as well as intensity levels and energy demands within the sport. It will also form a platform on which to base future research studies, further profiling and cross-sectional studies of athletes and the sport, as well as encourage performance enhancement and injury prevention by comparisons to the profiles of other sports.
MATERIALS AND METHODS METHODS PARTICIPANTS Seven male amateur free-runners volunteered to take part in the study (Mean ± SD: age 21.70 ± 2.60 yrs, body mass 67.80 ± 3.57 kg, height 174.4 ± 6.36 cm). All were free from musculoskeletal pathology at the commencement of data collection and provided written informed consent in accordance with the declaration of Helsinki. The procedures were approved by the University of East London, School of Health, Sport and Bioscience ethics committee.
PROCEDURE ROCEDURE Six participants underwent testing on two occasions and one participant attended 6 sessions. All participants undertook anthropometric measurements and vertical jump performance. However, only one participant attended further strength testing and undertook training sessions with Geographical Positioning Software (GPS). On the first visit, participants’ body mass was determined by electronic scales (Ironman BC-558, Tanita, Tokyo, Japan) and height was measured using a stadiometer. Age and a brief training history were recorded. Skinfolds were measured across seven sites (triceps, biceps, subscapular, supraspinale, abdominal, thigh and calf) on the right side of the body using skinfold callipers (Harpenden, British Indicators, Luton, UK) in accordance with the ISAK standard measurement procedures [18]. Measurements were taken to the nearest 0.2 mm, four seconds after applying the callipers. The mean of three measurements within 10 % of each other were taken by the same assessor to improve accuracy [14]. The 1978 Jackson and Pollock equation was used to establish body fat percentage of the participants [12]. After demographics and anthropometric measures were taken, participants were familiarised with the jump mat and the protocol of how to jump, and how the vertical jump height was going to be measured. This was to improve the effectiveness of later testing procedure and improve and negate learning effects [11, 20] and was therefore a familiarisation session. The second testing session was conducted at least 48 hours after the initial session to increase the effectiveness of familiarisation. Peak vertical jump height was measured with an electronic cord displacement jump mat (Takei Scientific Instruments Co. Ltd.), measuring jump height by displacement to the nearest ± 0.5 cm. Participants were allowed to warm up in their own time as part of their standard training session. Each participant was allowed five attempts to obtain maximal vertical jump height. Two attempts were allowed as a warm up. Participants were instructed to take off with two feet, hip to shoulder width apart, and land back onto the mat with two feet. Countermovement depth was unstandardised and use of arms was allowed. Participants were asked to drop to a comfortable depth before explosively accelerating vertically with the free use of arm movement. This was to mimic the plyometric actions of the sport, and allow for differing limb length of the subjects. A passive rest of 30 seconds was given between jump attempts. Peak power output was calculated using the Sayers et al [22] equation cited in Carlock et al [2]. From this, power to weight ratio was calculated by dividing by body mass.
MORE DETAILED TESTING This was undertaken by one participant only. The first two of these sessions was protocol familiarisation, and testing of one repetition maximum back squat (Technogym, Gymcompany Ltd, Somerset, UK) and bench press (Technogym, Gymcompany Ltd, Somerset, UK). This was to measure maximal strength of the participant in kilograms of weight lifted. The protocol from Harman and Garhammer [10] was used and all attempts were performed to strict posture and technical failure to avoid injury. The final three occasions measured heart rates, speeds, and distances achieved during the participant’s training sessions. Data were averaged over three training sessions and measured via a Garmin Forerunner 305 GPS and heart rate monitor (Garmin, UK). The participant was free to conduct any warm up and training desired. GPS and heart rate data gave an estimate of the intensity of the training sessions. The sessions lasted 26.21 minutes and 37.46 minutes and were conducted at just one training ‘spot’ in the 26
Warren et al.: A free-running case study
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centre of Norwich, Norfolk, UK; however, it was noted that training was not limited to that one location. Training sessions involved jumps, vaults, and balances, in three dimensions. This included forwardbackward, lateral and vertical movement.
STATISTICAL ANALYSIS Data were analysed using SPSS statistics V 20.0. Means, standard deviations and coefficient of variations were calculated for height, body mass, body fat percentage, vertical jump heights, vertical jump power output, age and training age. Normal distribution of performance variables was tested using a KolomogorovSmirnov test. Descriptive statistics were calculated for the training sessions. Reflections whether the athletes’ physiological profiles met the observed demands of free-running were also made.
RESULTS DEMOGRAPHICS AND PERFORMANCE MEASURES A total of seven participants completed this study. The free-runners’ vertical jump performances and anthropometric tests are shown in Table 1. Table 1. Participant demographics and performance Variable Age (years) Training age (years) Height (cm) Body mass (kg) Body fat (%) Power (W) -1 Power per kg (W·kg )
Free-runners (n=7) [mean ± SD] 21.71 ± 2.60 4.46 ± 1.66 174.40 ± 6.36 67.80 ± 3.57 7.26 ± 1.32 5,100.58 ± 141.29 75.42 ± 2.59
GPS DATA The randomly selected participant (body mass 68.2 kg, height 168.2 cm, age 19 years) generated a maximal one repetition back squat of 120 kg and a maximal one repetition bench press of 90 kg; the kilograms lifted represented the maximal force that could be produced in that range of motion. No other subject participated in any maximal lifting protocols. Table 2. Mean GPS and heart rate data Performance Variable Distance covered (km) Time (min) Movement time (min) Percentage time moving (%) -1 Average speed (km·h ) -1 Max speed (km·h ) Elevation change (m) Average heart rate (bpm) Max heart rate (bpm)
Mean Value 0.54 ± 0.10 33.05 ± 5.58.8 10.45 ± 1.43.51 32.61 ± 1.94 1.00 ± 0.25 11.76 ± 2.66 2.33 ± 1.53 144.33 ± 5.77 175.00 ± 5.00
Heart rate data were established over three individual training sessions (Table 2). The sessions lasted between 26.21 minutes and 37.46 minutes, covering 0.44 km to 0.64 km. It was recorded that less than a third of this time was spent moving while for the rest of the time minimal to no movement was detected. Consequently, the average speed was only 1 km·h-1. Maximum speed attained was measured at 9 km·h-1 to 14.3 km·h-1. This converts to average and maximal speeds of 0.29 m·s-1 and 3.27 m·s-1 respectively. The intensity values monitored by the heart rate monitor gave average heart rate values of 141 to 151 beats·min-1 and maximal values of 170 to 180 beats·min-1.
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Warren et al.: A free-running case study
Serb J Sports Sci 7(1): 25-30
DISCUSSION This study aimed to clarify what free-running is and what it demands as a sport, by quantitatively profiling the athlete’s physiology and anthropometry. This investigation intended to evaluate and understand the metabolic demands of the sport by using heart rate and GPS measurements. The results of the study illustrated that the free-runner sample tested had high power output as the result of high vertical jump performance. They also displayed low levels of body fat in comparison to other sports (Table 1 and 3), and low body mass. When comparing the data to the study by Jemni et al [13] of national and international level gymnasts, involved in a sport with similar movement patterns, free-runners displayed a lower body fat percentage by a mean of -2.46%. Both the absolute and relative power output of free-runners in this study were higher than the power outputs observed in the male gymnasts in Marina et al [15] by a mean of 1525.58 W and 10.42 W·kg-1 respectively. However, Marina et al [15] used a ‘drop jump’ technique finding peak power output from a drop of 40 cm, as opposed to the countermovement jumps used in this study. Table 3. Comparison of Mean ± SD anthropometric and power output data of the present free-runners with gymnasts and climbers Variable Age (years) Training age (years) Height (cm) Body mass (kg) Body fat (%) Power (W) -1 Power per kg (W·kg )
Climbers (n=11) MacLeod et al [16]
Gymnasts (n=41) Marina et al [15]
Gymnasts Jemni et al [13]
23.2 ±3.2 5.3 ± 1.9 175.5 ±6.7 66.4 ± 6.8 11.3 ±3.6
18 ±4.3
21.8 ±2.4
161.0 ±11.9 55.0 ±12.5
168.2 ±6.0 67.5 ±8.0 10.3 ±1.5
3575* 65.0*
*values are estimated from the figure in Marina et al [15]
The ability to produce maximal force or ‘strength’ tests on an individual male free-runner elicited maximal lower body strength of 120 kg during a back squat exercise and maximal upper body strength of 90 kg during a bench press exercise when working to technical failure. Wilstøff et al [27] found maximal squat significantly negatively correlated with 10 m sprint, 30 m sprint, and positively correlated to vertical jump in elite soccer players. This highlights the importance of maximal level strength in the process of power production over short distances in minimal amounts of time in movements very similar to that of freerunning. Despite this, Cronin and Hansen [4] found no significant relationship between three repetition maximum squatting and sprint speeds or jumping power performance among part- and full-time professional rugby league players. However, they highlighted that a large degree of variability in their sample could have distorted the accuracy of their results. Three repetition maximum testing is also not a measure of true maximal strength due to the repetition of the movement. Changing from a multiple effort test to a single effort test may have elicited a relationship between ‘true’ maximal strength and sprinting or jump power performance. Although maximal strength is not the only performance determining factor, it could be
proposed that a an athlete with higher maximal strength could accelerate and decelerate a set mass, for example body mass, with greater ease. Despite large confidence intervals from a small sample, Stone et al [24] confirmed this by demonstrating maximally stronger subjects had greater power outputs across a range of loads. Thus, the stronger free-runners were, the greater was their ability to explosively jump or land at a set distance, which increased the efficiency and safety of the athlete. Despite the lack of available comparisons, GPS was trialled among free-runners in this study due to the outdoor nature of the sport with the aim of establishing suitability for future testing. GPS has been used successfully to measure intensities and workloads in sports like beach soccer [3]. Although an average freerunning session had reasonable length (33.05 ± 5.58.8 min), only 10.05 ± 5.58.8 min (less than a third) was spent moving. This reflects the intermittent high intensity burst of the sport, where large portions of time are spent resting between explosive bursts of activity thus having a causal affect, significantly lowering average speeds to a slow walking pace [3]. While remaining intermittent, the accuracy upon workload may be very poor due to the vertical component of movement where changes in latitude and longitude are negligible. Thus a 1:2 work to rest ratio may be inaccurate. Metabolically demanding sequences of vertical activity may be done with little to no horizontal momentum. Although this intensity may reflect in the heart rate, GPS does not effectively account for vertical momentum. Average maximal speed was only 11.76 ± 2.66 km·h-1 28
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Serb J Sports Sci 7(1): 25-30
-1
or 3.27 m·s . This is not particularly fast and was classified as ‘quick running’ by Castellano and Casamichana [3], falling between 7.0 km·h-1 and 12.9 km·h-1. Average heart rate (144.33 ± 5.77 beats·min-1) and maximal heart rates (175 ± 5 beats·min-1) were obtained. Castellano and Casamichana [3] profiled beach soccer using heart rate intensities whereby nearly 60 % of match play was spent at greater than 90 % maximal heart rate. This is not surprising as more time in beach soccer is spent moving and performance relies more on an aerobic component, although this could be skewed by the short play time compared to the time the free-runner spent training. However, blood lactate and heart rate have been used by authors to measure physiological capabilities of gymnasts [13]. Although this was during non-gymnastic lab tests, Jemni et al [13] found national and international gymnasts to have blood lactate levels of 16.89 mmol·L-1 and 11.42 mmol·L-1 and heart rates of 169.33 and 169.77 beats·min-1 at treadmill VO2max exhaustion, although blood lactate was lower during the Wingate test. While this gives an impression of physiological capabilities, more research is needed within the free-runner population to verify both their capabilities and the physiological characteristics elicited by training demands. Together the GPS and heart rate data reflect the intermittency of explosive bouts with long periods of rest within free-running. It is apparent that free-running relies heavily on the phosphogen energy systems for energy production, with a small demand of aerobic component while the athlete recovers for the next bout of activity. The findings of this study are limited to a very small population of free-runners, or even a case study of one free-runner’s abilities and characteristics of training. This gives a very low external validity and ability to transfer the findings to the free-running population. The population also varied greatly in their physiology and anthropometry. A more detailed study needs to be done on a much larger group of free-runners to gain accurate knowledge of both the athlete characteristics and the demands of the sport. A refinement of the testing procedures is needed and the knowledge of the test results obtained in this study and their applicability to the biomechanics and physiology of the sport is essential for providing an accurate profile of free-runners’ physiology most relevant to the sport.
CONCLUSION CONCLUSION AND PRACTICAL APPLICATION APPLICATION In conclusion, free-runners in the present study displayed high power output as result of high vertical jump performance. Free-runners also displayed low levels of body fat, and a low body mass. The GPS data illustrated that free-running is an intermittent sport relying heavily on the phosphagenic energy system, and therefore free-runners should focus their training on the utilisation of this energy system. The results also suggest that, due to the physical nature of free-running, future studies should trial different equipment to monitor the physiological demands and intensity of the sport.
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Address for correspondence: Dr Lindsay Bottoms School of Health, Sport and Bioscience, University of East London, Water Lane, Stratford, E15 4LZ, UK. Tel: 020 8223 3371 E-mail:
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