- Email: [email protected]
Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players
G Model JSAMS-2212; No. of Pages 5
ARTICLE IN PRESS Journal of Science and Medicine in Sport xxx (2019) xxx–xxx
Contents lists available at ScienceDirect
Journal of Science and Medicine in Sport journal homepage: www.elsevier.com/locate/jsams
Original research
Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players Fabian Garcia-Byrne a,b,∗ , Thomas P. Wycherley a , Chris Bishop a,c , Stephen Schwerdt b , Jonathon Porter b , Jonathan D. Buckley a a
University of South Australia, Alliance for Research in Exercise, Nutrition and Activity (ARENA), GPO Box 2471, Adelaide, South Australia 5001, Australia South Australian Cricket Association (SACA), Adelaide Oval, War Memorial Dr, North Adelaide, South Australia 5006, Australia c The Biomechanics Lab, 91 Kensington Rd, Norwood, South Australia 5067, Australia b
a r t i c l e
i n f o
Article history: Received 27 August 2019 Received in revised form 22 November 2019 Accepted 1 December 2019 Available online xxx Keywords: Fatigue Two kilometre time trial PlayerLoad
a b s t r a c t Objective: To identify whether movement patterns during a standardized submaximal running test (SSRT), assessed by accelerometry, were associated with improvements in endurance exercise performance. Design: A retrospective analysis of data collected from the 2018–2019 Australian cricket preseason. Methods: Thirty-nine high-performance male cricket players were studied (25 ± 3 years, 82 ± 6 kg, 183 ± 6 cm). SSRT was performed monthly prior to a two kilometre (km) running time trial (2 kmTT). SSRT involved running between markers, positioned twenty metres apart, for three minutes. Foot strikes were timed to a metronome (154 beats/min) to elicit a running speed of e˜ ight km/h. Triaxial accelerometers were worn in vests on the upper back and used to assess PlayerLoad medio-lateral vector (PL1Dside% ), vertical vector (PL1Dup% ) and anterior-posterior vector (PL1Dfwd% ) were assessed. Results: 2 kmTT performance improved over the study period (p < 0.05). PlayerLoad vectors during the first minute of SSRT were not related to 2 kmTT performance (p > 0.23). During the second and third minutes there were positive associations between 2 kmTT (run time) and PL1Dside% (SSRT2min , ˇ 2.12, p < 0.03, 95% CI: 0.22–4.01; SSRT3min , ˇ 2.30, p < 0.03, 95% CI:0.32–4.29), but not PL1Dup% (SSRT2min , ˇ −0.15, p = 0.77, 95% CI: −1.13–0.83; SSRT3min , ˇ −0.15, p = 0.77, 95% CI: −1.11–0.87) or PL1Dfwd% (SSRT2min , ˇ −0.45, p = 0.42, 95% CI: −1.49–0.62; SSRT3min , B−0.45, p = 0.40, 95% CI: −1.51–0.60). Conclusion: Assessment of PL1Dside% during the second or third minutes of SSRT may inform how an athlete’s endurance exercise performance is responding to changes in training load. © 2019 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Practical implications • The results from this study identified that the triaxial accelerometer variable PL1Dside%, assessed during SSRT, were linearly related to 2 kmTT performance improvements in elite male cricket players. • The submaximal intensity of the SSRT will minimise the possibility of exacerbating any underlying fatigue. • As triaxial accelerometer units function indoors and outdoors, and the SSRT is non-invasive and easy to perform, large groups
∗ Corresponding author. E-mail address: [email protected] (F. Garcia-Byrne).
could perform the test at the same time to determine how their endurance exercise capacity is responding to changes in training. 1. Introduction The quantification of training and competition loads is common within elite sport.1–3 The advent of wearable microtechnology such as Global Positioning Systems devices (GPS) has made the quantification of external training load (i.e. total distance and/or speeds) relatively simple and non-invasive.4,5 However, modern GPS devices are typically embedded with triaxial accelerometers, which also allow monitoring of changes of direction, deceleration and acceleration, in all three planes of motion (medio-lateral plane, anterior-posterior plane and vertical plane).6–8 An accelerometerderived external load variable that provides an index of total
https://doi.org/10.1016/j.jsams.2019.12.003 1440-2440/© 2019 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Garcia-Byrne F, et al.Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players. J Sci Med Sport (2019), https://doi.org/10.1016/j.jsams.2019.12.003
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movement, and the proportion of movement in each of the three planes,6,10,12 that is commonly assessed is PlayerLoad.6 PlayerLoad is quantified as the square root of the sum of the squared instantaneous rates of change in acceleration in the medio-lateral plane (PL1Dside% ), anterior-posterior plane (PL1Dfwd% ) and vertical plane (PL1Dup% ) divided by 100.6 Movement in each plane can also be assessed separately to examine changes in movement patterns. Recent evidence suggests that triaxial accelerometers can detect changes in movement patterns resulting from fatigue. In Australian Rules Football, players PlayerLoad per minute was shown to be reduced in fatigued individuals compared to non-fatigued individuals during competitive match play.13,14 Similarly, in elite Australian soccer players it was reported that when vertical jump performance was reduced due to neuromuscular fatigue, percentage movement was increased for PL1Dside% and decreased for PL1Dup% during standardised small-sided games,15 indicating the presence of more lateral sway and reduced vertical displacement. In contrast however, in semi-professional Australian Rules Football players, when countermovement jump performance was reduced due to neuromuscular fatigue, PL1Dside% and PL1Dup% were both reduced during 50 m high speed (>21 km/h) run throughs,16 indicating reductions in both lateral sway and vertical displacement. Therefore, to date triaxial accelerometers have been shown to detect changes in PlayerLoad-based movement patterns that are associated with reductions in muscular power due to neuromuscular fatigue. However, while muscular power is important for many sporting activities, endurance exercise performance is also important, but whether PlayerLoad-based movement patterns change in response to changes in endurance exercise performance is not known. The aim of this study was to determine whether changes in PlayerLoad-based movement patterns, assessed during standardized submaximal running, were associated with training-induced changes in endurance exercise performance in high-performance athletes during a preseason training program.
2. Methods Twenty-three professional and thirteen semi-professional male cricket players participated in the study (age; 25 ± 3 years, body mass; 82 ± 6 kg and height; 183 ± 6 cm). Testing was performed during routine training as part of the 2018–2019 Australian cricket preseason. The study was approved by the University of South Australia Human Research Ethics Committee (Approval 201214). On four occasions, at one-month intervals (Baseline, Month-1 [M-1], Month-2 [M-2] and Month-3 [M-3]), PlayerLoad variables were collected during a standardised submaximal running test (SSRT) that was performed during the warm-up at the start of each training session. This was followed by a two km maximal running time trial (2 kmTT), with the time to perform this test taken to represent a measure of endurance exercise performance. SSRT was performed in an indoor training facility while the 2 kmTT was performed on a compacted outdoor running track. Data collection for the professional and semi-professional male cricket players took place on different occasions but no more than four days apart. Air temperature (◦ C), relative humidity (%) and wind speed (km/h) were record prior to 2 kmTT (Table 1). The SSRT required the athletes to run between markers positioned twenty metres apart for three minutes, with the timing of their footstrikes guided by a metronome set at 154-beats/min. In preliminary testing this protocol elicited a running speed of 8˜ km/h.
Triaxial accelerometers embedded in GPS devices (model S5, Catapult Sports, Catapult Innovations, Melbourne Australia) sampling at 100 Hz were worn in specialized vests, positioned on the upper back between the scapulae. Participants wore the same device at all testing sessions to minimise any effect of bias between difference devices.17 Accelerometer variables used for analysis were PlayerLoad medio-lateral vector (PL1Dside% ), PlayerLoad vertical vector (PL1Dup% ) and PlayerLoad anterior-posterior vector (PL1Dfwd% ). All accelerometer data collected during the SSRT were downloaded using Catapult OpenField for analysis (Catapult OpenField, Catapult Innovations, Melbourne Australia) and manually cut down into the first (SSRT1min ) second (SSRT2min ) and third minute (SSRT3min ) of the test. Ten individuals who were not involved in the primary study performed the SSRT on two occasions separated by ten minutes to determine reliability for assessment of each vector. Reliability, expressed as a percent coefficient of variation, was 2.8% for PL1Dside% , 1.4% for PL1Dup% and 1.6% for PL1Dfwd% . Statistical analysis was completed using Stata 15.0 (Stata Corp., Texas, USA). Random effects mixed models were used to assess relationships between the PlayerLoad vectors and 2 kmTT (run time). Relationships between variables are reported as non-standardized ˇ values (with 95% Confidence Intervals). Data are reported as mean ± SD. Statistical significance was set at p < 0.05. 3. Results Climate conditions, 2 kmTT and PlayerLoad metrics at baseline, M-1, M-2 and M-3 are provided in Table 1. Climate conditions were cool on all testing days. 2 kmTT was significantly faster at M-2 and M-3 compared with baseline (p < 0.05). There were variable and transient changes in PL1Dup% assessed during the first minute of SSRT (SSRT1min ), PL1Dup% and PL1Dfwd% assessed during the second minute of SSRT (SSRT2min ) and PL1Dup% and PL1Dfwd% assessed during the third minute of SSRT (SSRT3min ) (Table 1). There were no relationships between PlayerLoad vectors and 2 kmTT during SSRT1min (PL1Dside% , ˇ 1.17, p = 0.23, 95% CI: 0.74–3.08 [Fig. 1, Panel A]; PL1Dup% , ˇ1.10e−4 , p > 0.99, 95% CI: −0.95–0.95; PL1Dfwd% , ˇ −0.35, p = 0.51, 95% CI: −1.39–0.69). However, 2 kmTT was positively related to PlayerLoad vectors during SSRT2min and SSRT3min for PL1Dside% (SSRT2min , ˇ 2.12, p < 0.03, 95% CI: 0.22–4.01 [Fig. 1, Panel B]; SSRT3min , ˇ 2.30, p < 0.03, 95% CI: 0.32–4.29 [Fig. 1, Panel C), but not PL1Dup% (SSRT2min , ˇ −0.15, p = 0.77, 95% CI: −1.130.83; SSRT3min , ˇ −0.15, p = 0.77, 95% CI: −1.11–0.87) or PL1Dfwd% (SSRT2min , ˇ −0.45, p = 0.42, 95% CI: −1.49–0.62; SSRT3min , B-0.45, p = 0.40, 95% CI: −1.51–0.60). 4. Discussion This study found that PL1Dside% during the second and third minutes of the SSRT was positively associated with 2 kmTT performance over a pre-season training period in elite male cricket players. Thus, reduced PL1Dside% during standardised submaximal running, indicating less lateral sway, was associated with a shorter time to complete the 2 kmTT. This suggests that monitoring PL1Dside% during SSRT might be useful for identifying how athletes are responding to training and inform changes in training load to optimise endurance exercise performance. This study was performed during a pre-season training phase which was designed to improve 2 kmTT running performance leading into the competitive season, and this was achieved, as 2 kmTT performance improved from baseline to M-3 as the athletes were gradually exposed to greater training loads (Table 1). Therefore, while this study provides evidence that reductions
Please cite this article in press as: Garcia-Byrne F, et al.Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players. J Sci Med Sport (2019), https://doi.org/10.1016/j.jsams.2019.12.003
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Table 1 Two kilometre running time trial performance, PlayerLoad vectors assessed during a standardised submaximal running test, GPS-derived load parameters and Climate conditions at various timepoints during preseason training in high-performance male cricket players. Variable
2 km TT (s) PL1Dup% 1 min (%) PL1Dside% 1 min (%) PL1Dfwd% 1 min (%) PL1Dup% 2 min (%) PL1Dside% 2 min (%) PL1Dfwd% 2 min (%) PL1Dup% 3 min (%) PL1Dside% 3 min (%) PL1Dfwd% 3 min (%) Total Distance (km) Total PlayerLoad (AU) Total Distance 21–26 km/h (m) Total Distance 26 km/h + (m) Air Temperature (◦ C) Relative humidity (%) Wind Speed (km/h)
Assessment timepoints Baseline
Month 1
Month 2
Month 3
439 ± 29 52 ± 4 22 ± 3 26 ± 4 52 ± 4 22 ± 3 25 ± 4 52 ± 4 23 ± 3 25 ± 4
430 ± 26 47 ± 11* 23 ± 5 29 ± 8 47 ± 11* 24 ± 5 29 ± 8* 47 ± 11* 24 ± 5 29 ± 8* 43.8 ± 9.1 5782 ± 1512 4390 ± 1944 245 ± 155 14 ± 4 43 ± 9 8±2
429 ± 50* 49 ± 8 23 ± 5 27 ± 5 50 ± 6 24 ± 4 27 ± 4 49 ± 6 24 ± 5 27 ± 4 35.9 ± 6.2 4749 ± 861 6326 ± 1897 363 ± 183 13 ± 2 70 ± 8 16 ± 5
425 ± 27** 53 ± 4 22 ± 3 25 ± 4 52 ± 4 23 ± 3 25 ± 4 51 ± 4 24 ± 3 25 ± 4 115.5 ± 11.1 8936 ± 3249 5543 ± 2870 953 ± 429 18 ± 2 28 ± 5 13 ± 0
14 ± 4 66 ± 31 18 ± 5
Significantly different from baseline *p < 0.05, ** p < 0.01. Data are mean ± SD. PlayerLoad = PL1D; Medio-Lateral = side; Vertical = up; Anterior-Posterior = fwd.
in PL1Dside% were associated with 2 kmTT performance, this finding must be interpreted in the context of 2 kmTT performance improving over the pre-season training period. It is unclear whether changes in PL1Dside% would be associated with decreases in 2 kmTT performance following cessation of training, or induction of fatigue. Future studies are required to evaluate this. The mechanisms underlying the observed positive association between PL1Dside% and 2 kmTT are not clear. However, a recent analysis of the effects of fatigue on movement patterns in ballet dancers18 showed that the lateral displacement of the centre of mass during the performance of standardised movements was increased when fatigued. This increased lateral movement may be due to impaired muscular strength and loss of postural control,19 with the loss of postural control being a result of altered proprioceptive feedback from the fatigued muscles.20,21 Thus, in the present study a greater PL1Dside% during the second and third minutes of the SSRT at the start of pre-season, when 2 kmTT performance was slower, may have been a result of poorer muscular strength and postural control while running at 8˜ km/h. As the training load in the current study was increased from baseline to M-3 the athletes may have adapted positively to the increased training load, resulting in improvements not only in their 2 kmTT running performance, but also increasing their muscular strength and postural control. Irrespective of the mechanism by which PL1Dside% was reduced when 2 kmTT performance was improved, the present finding is consistent with previous work which investigated the effects of neuromuscular fatigue on PlayerLoad vectors during standardized small sided games in high performance soccer players.22 In that study it was found that when a standardized small sided game was performed weekly, PL1Dside% during those small sided games was increased when neuromuscular fatigue was present. Neuromuscular fatigue was identified by a decrease in flight time to contact time ratio during a maximal countermovement jump. The data from the present study extended those findings to show that a similar change in movement pattern occurred with changes in endurance running performance, but also that there was a linear relationship between PL1Dside% assessed during SSRT and 2 km TT performance. Previous research also found a reduction in the PL1Dup% when neuromuscular fatigue was present.15,16 However, no relationship between running performance changes and PL1Dup% was evident
in the present study. During running, vertical displacement is influenced by a range of factors, including running velocity, stride frequency and length, contact time and flight time,23 with reductions in vertical displacement occurring as running speed increases in an effort to maintain running efficiency as muscle force production and energy expenditure increase.24,25 These reductions in vertical displacement to maintain running efficiency have been interpreted as representing vertical stiffness,26 a key characteristic of high intensity running performance that has been shown to be reduced in the presence of fatigue,27,28 with it being suggested that this reduces impact force transmission through the body to protect anatomical structures from damage.25 Thus, the lack of change in PL1Dup%, and the lack of any relationship with 2 kmTT in the present study, may be due to the submaximal nature of the running during SSRT, which was performed at 8˜ km/h. The previous studies which identified changes in PL1Dup% found these when performing 50 m run through at an average speed of 22.5 km/h,16 or during the performance of small-sided soccer games15 which would have included passages of high speed running. Thus, the difference in findings of these studies may be related to differences in running speed. However, the submaximal nature of the SSRT is an important advantage as it is unlikely to exacerbate any underlying fatigue,29 and could therefore be performed during a pre-training warm-up without disruption to the training program. The results could then be used to inform changes to training based on how an athlete had been responding to the training load. While PL1Dside% during the second and third minutes of SSRT was positively related to 2 kmTT as running performance improved across the preseason, no such relationship was found with PL1Dside% during the first minute of the SSRT. This may be because, during the first minute of SSRT, the athletes accelerated from a standing start to running at 8˜ km/h, and the acceleration may have resulted in greater variation in movement that might have masked any subtle overall change in movement pattern. However, by the second and third minutes of the SSRT the athletes had likely reached a steady-state in terms of running gait, thus reducing movement variation and making it possible to detect subtle but consistent changes in movement pattern. Due to the positive associations between PL1Dside% and 2 kmTT performance being similar during both the second and third minutes of the SSRT, the SSRT could be performed over as little as a two-minute period to minimise disruption to training.
Please cite this article in press as: Garcia-Byrne F, et al.Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players. J Sci Med Sport (2019), https://doi.org/10.1016/j.jsams.2019.12.003
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Fig. 1. Relationships between PlayerLoad Medio-lateral vector (PlayerLoad medio-lateral 1D) and two kilometre time trial run time assessed during the first (Panel A), second (Panel B) and third (Panel C) minutes of a standardized submaximal running test. Different symbols represent different athletes.
5. Conclusion Changes in endurance exercise performance were associated with changes in movement patterns during the second and third minutes of the SSRT. PL1Dside% was positively related to 2 kmTT such that as 2 kmTT performance improved across the
preseason, PL1Dside% reduced. This indicated that as athletes performed better in the 2 kmTT they exhibited less lateral sway when running at 8˜ km/h. The SSRT could be used to assess how endurance exercise performance is responding to changes in training load without the necessity of asking athletes undertake a 2 kmTT.
Please cite this article in press as: Garcia-Byrne F, et al.Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players. J Sci Med Sport (2019), https://doi.org/10.1016/j.jsams.2019.12.003
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Acknowledgement The author would like to acknowledge the South Australian Cricket Association for their support of this research. References 1. Borresen J, Lambert M. The quantification of training load, the training response and the effect on performance. Sports Med 2009; 39(9):779–795. 2. Halson S. Monitoring training load to understand fatigue in athletes. Sports Med 2014; 44(Supplement 2):139–147. 3. Cardinale M, Varley M. Wearable training-monitoring technology: applications, challenges, and opportunities. Int J Sports Physiol Perform 2017; 12(s2):55–62. 4. Aughey RJ. Applications of GPS technologies to field sports. Int J Sports Physiol Perform 2011; 6(3):295. 5. Cummins C, Orr R, O’Connor H et al. Global positioning systems (GPS) and microtechnology sensors in team sports: a systematic review. Sports Med 2013; 43(10):1025–1042. 6. Boyd L, Ball K, Aughey R. The reliability of minimaxX accelerometers for measuring physical activity in Australian football. Int J Sports Physiol Perform 2011; 6(3):311–321. 7. Twist C, Highton J. Monitoring fatigue and recovery in rugby league players. Int J Sports Physiol Perform 2013; 8(5):467–474. 8. Barrett S, Midgley A, Reeves M et al. The within-match patterns of locomotor efficiency during professional soccer match play: implications for injury risk? J Sci Med Sport 2016; 19(10):810–815. 10. Jennings D, Cormack S, Coutts AJ et al. The validity and reliability of GPS units for measuring distance in team sport specific running patterns. Int J Sports Physiol Perform 2010; 5(3):328. 12. Varley M, Fairweather I, Aughey R. Validity and reliability of GPS for measuring instantaneous velocity during acceleration, deceleration, and constant motion. J Sports Sci 2012; 30(2):121–127. 13. Cormack S, Mooney M, Morgan W et al. Influence of neuromuscular fatigue on accelerometer load in elite Australian football players. Int J Sports Physiol Perform 2013; 8(4):373. 14. Mooney GMitchell, Cormack JStuart, O’brien MBrendan et al. Impact of neuromuscular fatigue on match exercise intensity and performance in elite australian football. J Strength Conditioning Res 2013; 27(1):166–173.
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15. Rowell AE, Aughey RJ, Clubb J et al. A standardized small sided game can be used to monitor neuromuscular fatigue in professional a-league football players. Frontiers Physiol 2018; 9. Article number 1011. 16. Garrett J, Graham S, Eston R et al. A novel method of assessment for monitoring neuromuscular faitgue within Australian Rules football players. Int J Sports Physiol Perform 2018:1–25. 17. Johnston RJ, Watsford ML, Kelly SW, Pine M, Spurrs R. Validity and interunit reliability of 10 Hz and 15 Hz GPS units for assessing athlete movement demands. J Strength and Conditioning Res 2014; 28(6):1649–1655. 18. Lin CF, Lee WC, Chen YA et al. Fatigue-induced changes in movement pattern and muscle activity during ballet releve on demi-pointe. J Appl Biomech 2016; 32(4):350–358. 19. Vuillerme N, Pinsault N. Experimental neck muscle pain impairs standing balance in humans. Exp Brain Res 2009; 192(4):723–729. 20. Corbeil P, Blouin J-S, Bégin F et al. Perturbation of the postural control system induced by muscular fatigue. Gait Posture 2003; 18(2):92–100. 21. Bisson E, Lajoie Y, Bilodeau M. The influence of age and surface compliance on changes in postural control and attention due to ankle neuromuscular fatigue. Exp Brain Res 2014; 232(3):837–845. 22. Rowell AE, Aughey RJ, Clubb J et al. A standardized small sided game can be used to monitor neuromuscular fatigue in professional a-league football players. Frontiers Physiol 2018; 9(1011). 23. Hobara H, Inoue K, Gomi K et al. Continuous change in spring-mass characteristics during a 400 m sprint. J Sci Med Sport 2010; 13(2):256–261. 24. McMahon TA, Valiant G, Frederick EC. Groucho running. J Appl Physiol 1987; 62(6):2326–2337. 25. Dalleau G, Belli A, Bourdin M et al. The spring-mass model and the energy cost of treadmill running. Eur J Appl Physiol 1998; 77(3):257–263. 26. Buchheit M, Gray A, Morin J. Assessing stride variables and vertical stiffness with GPS-embedded accelerometers: preliminary insights for the monitoring of neuromuscular fatigue on the field. J Sports Sci Med 2015; 14(4):698–701. 27. Girard O, Micallef J-P, Millet G. Changes in spring-mass model characteristics during repeated running sprints. Eur J Appl Physiol 2011; 111(1):125–134. 28. Morin JB, Dalleau G, Kyröläinen H et al. A simple method for measuring stiffness during running. J Appl Biomech 2005; 21(2):167. 29. Nelson M, Thomson R, Rogers D et al. Maximal rate of increase in heart rate during the rest-exercise transition tracks reductions in exercise performance when training load is increased. J Sci Med Sport 2014; 17(1):129–133.
Please cite this article in press as: Garcia-Byrne F, et al.Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players. J Sci Med Sport (2019), https://doi.org/10.1016/j.jsams.2019.12.003
ARTICLE IN PRESS Journal of Science and Medicine in Sport xxx (2019) xxx–xxx
Contents lists available at ScienceDirect
Journal of Science and Medicine in Sport journal homepage: www.elsevier.com/locate/jsams
Original research
Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players Fabian Garcia-Byrne a,b,∗ , Thomas P. Wycherley a , Chris Bishop a,c , Stephen Schwerdt b , Jonathon Porter b , Jonathan D. Buckley a a
University of South Australia, Alliance for Research in Exercise, Nutrition and Activity (ARENA), GPO Box 2471, Adelaide, South Australia 5001, Australia South Australian Cricket Association (SACA), Adelaide Oval, War Memorial Dr, North Adelaide, South Australia 5006, Australia c The Biomechanics Lab, 91 Kensington Rd, Norwood, South Australia 5067, Australia b
a r t i c l e
i n f o
Article history: Received 27 August 2019 Received in revised form 22 November 2019 Accepted 1 December 2019 Available online xxx Keywords: Fatigue Two kilometre time trial PlayerLoad
a b s t r a c t Objective: To identify whether movement patterns during a standardized submaximal running test (SSRT), assessed by accelerometry, were associated with improvements in endurance exercise performance. Design: A retrospective analysis of data collected from the 2018–2019 Australian cricket preseason. Methods: Thirty-nine high-performance male cricket players were studied (25 ± 3 years, 82 ± 6 kg, 183 ± 6 cm). SSRT was performed monthly prior to a two kilometre (km) running time trial (2 kmTT). SSRT involved running between markers, positioned twenty metres apart, for three minutes. Foot strikes were timed to a metronome (154 beats/min) to elicit a running speed of e˜ ight km/h. Triaxial accelerometers were worn in vests on the upper back and used to assess PlayerLoad medio-lateral vector (PL1Dside% ), vertical vector (PL1Dup% ) and anterior-posterior vector (PL1Dfwd% ) were assessed. Results: 2 kmTT performance improved over the study period (p < 0.05). PlayerLoad vectors during the first minute of SSRT were not related to 2 kmTT performance (p > 0.23). During the second and third minutes there were positive associations between 2 kmTT (run time) and PL1Dside% (SSRT2min , ˇ 2.12, p < 0.03, 95% CI: 0.22–4.01; SSRT3min , ˇ 2.30, p < 0.03, 95% CI:0.32–4.29), but not PL1Dup% (SSRT2min , ˇ −0.15, p = 0.77, 95% CI: −1.13–0.83; SSRT3min , ˇ −0.15, p = 0.77, 95% CI: −1.11–0.87) or PL1Dfwd% (SSRT2min , ˇ −0.45, p = 0.42, 95% CI: −1.49–0.62; SSRT3min , B−0.45, p = 0.40, 95% CI: −1.51–0.60). Conclusion: Assessment of PL1Dside% during the second or third minutes of SSRT may inform how an athlete’s endurance exercise performance is responding to changes in training load. © 2019 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Practical implications • The results from this study identified that the triaxial accelerometer variable PL1Dside%, assessed during SSRT, were linearly related to 2 kmTT performance improvements in elite male cricket players. • The submaximal intensity of the SSRT will minimise the possibility of exacerbating any underlying fatigue. • As triaxial accelerometer units function indoors and outdoors, and the SSRT is non-invasive and easy to perform, large groups
∗ Corresponding author. E-mail address: [email protected] (F. Garcia-Byrne).
could perform the test at the same time to determine how their endurance exercise capacity is responding to changes in training. 1. Introduction The quantification of training and competition loads is common within elite sport.1–3 The advent of wearable microtechnology such as Global Positioning Systems devices (GPS) has made the quantification of external training load (i.e. total distance and/or speeds) relatively simple and non-invasive.4,5 However, modern GPS devices are typically embedded with triaxial accelerometers, which also allow monitoring of changes of direction, deceleration and acceleration, in all three planes of motion (medio-lateral plane, anterior-posterior plane and vertical plane).6–8 An accelerometerderived external load variable that provides an index of total
https://doi.org/10.1016/j.jsams.2019.12.003 1440-2440/© 2019 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Garcia-Byrne F, et al.Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players. J Sci Med Sport (2019), https://doi.org/10.1016/j.jsams.2019.12.003
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movement, and the proportion of movement in each of the three planes,6,10,12 that is commonly assessed is PlayerLoad.6 PlayerLoad is quantified as the square root of the sum of the squared instantaneous rates of change in acceleration in the medio-lateral plane (PL1Dside% ), anterior-posterior plane (PL1Dfwd% ) and vertical plane (PL1Dup% ) divided by 100.6 Movement in each plane can also be assessed separately to examine changes in movement patterns. Recent evidence suggests that triaxial accelerometers can detect changes in movement patterns resulting from fatigue. In Australian Rules Football, players PlayerLoad per minute was shown to be reduced in fatigued individuals compared to non-fatigued individuals during competitive match play.13,14 Similarly, in elite Australian soccer players it was reported that when vertical jump performance was reduced due to neuromuscular fatigue, percentage movement was increased for PL1Dside% and decreased for PL1Dup% during standardised small-sided games,15 indicating the presence of more lateral sway and reduced vertical displacement. In contrast however, in semi-professional Australian Rules Football players, when countermovement jump performance was reduced due to neuromuscular fatigue, PL1Dside% and PL1Dup% were both reduced during 50 m high speed (>21 km/h) run throughs,16 indicating reductions in both lateral sway and vertical displacement. Therefore, to date triaxial accelerometers have been shown to detect changes in PlayerLoad-based movement patterns that are associated with reductions in muscular power due to neuromuscular fatigue. However, while muscular power is important for many sporting activities, endurance exercise performance is also important, but whether PlayerLoad-based movement patterns change in response to changes in endurance exercise performance is not known. The aim of this study was to determine whether changes in PlayerLoad-based movement patterns, assessed during standardized submaximal running, were associated with training-induced changes in endurance exercise performance in high-performance athletes during a preseason training program.
2. Methods Twenty-three professional and thirteen semi-professional male cricket players participated in the study (age; 25 ± 3 years, body mass; 82 ± 6 kg and height; 183 ± 6 cm). Testing was performed during routine training as part of the 2018–2019 Australian cricket preseason. The study was approved by the University of South Australia Human Research Ethics Committee (Approval 201214). On four occasions, at one-month intervals (Baseline, Month-1 [M-1], Month-2 [M-2] and Month-3 [M-3]), PlayerLoad variables were collected during a standardised submaximal running test (SSRT) that was performed during the warm-up at the start of each training session. This was followed by a two km maximal running time trial (2 kmTT), with the time to perform this test taken to represent a measure of endurance exercise performance. SSRT was performed in an indoor training facility while the 2 kmTT was performed on a compacted outdoor running track. Data collection for the professional and semi-professional male cricket players took place on different occasions but no more than four days apart. Air temperature (◦ C), relative humidity (%) and wind speed (km/h) were record prior to 2 kmTT (Table 1). The SSRT required the athletes to run between markers positioned twenty metres apart for three minutes, with the timing of their footstrikes guided by a metronome set at 154-beats/min. In preliminary testing this protocol elicited a running speed of 8˜ km/h.
Triaxial accelerometers embedded in GPS devices (model S5, Catapult Sports, Catapult Innovations, Melbourne Australia) sampling at 100 Hz were worn in specialized vests, positioned on the upper back between the scapulae. Participants wore the same device at all testing sessions to minimise any effect of bias between difference devices.17 Accelerometer variables used for analysis were PlayerLoad medio-lateral vector (PL1Dside% ), PlayerLoad vertical vector (PL1Dup% ) and PlayerLoad anterior-posterior vector (PL1Dfwd% ). All accelerometer data collected during the SSRT were downloaded using Catapult OpenField for analysis (Catapult OpenField, Catapult Innovations, Melbourne Australia) and manually cut down into the first (SSRT1min ) second (SSRT2min ) and third minute (SSRT3min ) of the test. Ten individuals who were not involved in the primary study performed the SSRT on two occasions separated by ten minutes to determine reliability for assessment of each vector. Reliability, expressed as a percent coefficient of variation, was 2.8% for PL1Dside% , 1.4% for PL1Dup% and 1.6% for PL1Dfwd% . Statistical analysis was completed using Stata 15.0 (Stata Corp., Texas, USA). Random effects mixed models were used to assess relationships between the PlayerLoad vectors and 2 kmTT (run time). Relationships between variables are reported as non-standardized ˇ values (with 95% Confidence Intervals). Data are reported as mean ± SD. Statistical significance was set at p < 0.05. 3. Results Climate conditions, 2 kmTT and PlayerLoad metrics at baseline, M-1, M-2 and M-3 are provided in Table 1. Climate conditions were cool on all testing days. 2 kmTT was significantly faster at M-2 and M-3 compared with baseline (p < 0.05). There were variable and transient changes in PL1Dup% assessed during the first minute of SSRT (SSRT1min ), PL1Dup% and PL1Dfwd% assessed during the second minute of SSRT (SSRT2min ) and PL1Dup% and PL1Dfwd% assessed during the third minute of SSRT (SSRT3min ) (Table 1). There were no relationships between PlayerLoad vectors and 2 kmTT during SSRT1min (PL1Dside% , ˇ 1.17, p = 0.23, 95% CI: 0.74–3.08 [Fig. 1, Panel A]; PL1Dup% , ˇ1.10e−4 , p > 0.99, 95% CI: −0.95–0.95; PL1Dfwd% , ˇ −0.35, p = 0.51, 95% CI: −1.39–0.69). However, 2 kmTT was positively related to PlayerLoad vectors during SSRT2min and SSRT3min for PL1Dside% (SSRT2min , ˇ 2.12, p < 0.03, 95% CI: 0.22–4.01 [Fig. 1, Panel B]; SSRT3min , ˇ 2.30, p < 0.03, 95% CI: 0.32–4.29 [Fig. 1, Panel C), but not PL1Dup% (SSRT2min , ˇ −0.15, p = 0.77, 95% CI: −1.130.83; SSRT3min , ˇ −0.15, p = 0.77, 95% CI: −1.11–0.87) or PL1Dfwd% (SSRT2min , ˇ −0.45, p = 0.42, 95% CI: −1.49–0.62; SSRT3min , B-0.45, p = 0.40, 95% CI: −1.51–0.60). 4. Discussion This study found that PL1Dside% during the second and third minutes of the SSRT was positively associated with 2 kmTT performance over a pre-season training period in elite male cricket players. Thus, reduced PL1Dside% during standardised submaximal running, indicating less lateral sway, was associated with a shorter time to complete the 2 kmTT. This suggests that monitoring PL1Dside% during SSRT might be useful for identifying how athletes are responding to training and inform changes in training load to optimise endurance exercise performance. This study was performed during a pre-season training phase which was designed to improve 2 kmTT running performance leading into the competitive season, and this was achieved, as 2 kmTT performance improved from baseline to M-3 as the athletes were gradually exposed to greater training loads (Table 1). Therefore, while this study provides evidence that reductions
Please cite this article in press as: Garcia-Byrne F, et al.Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players. J Sci Med Sport (2019), https://doi.org/10.1016/j.jsams.2019.12.003
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Table 1 Two kilometre running time trial performance, PlayerLoad vectors assessed during a standardised submaximal running test, GPS-derived load parameters and Climate conditions at various timepoints during preseason training in high-performance male cricket players. Variable
2 km TT (s) PL1Dup% 1 min (%) PL1Dside% 1 min (%) PL1Dfwd% 1 min (%) PL1Dup% 2 min (%) PL1Dside% 2 min (%) PL1Dfwd% 2 min (%) PL1Dup% 3 min (%) PL1Dside% 3 min (%) PL1Dfwd% 3 min (%) Total Distance (km) Total PlayerLoad (AU) Total Distance 21–26 km/h (m) Total Distance 26 km/h + (m) Air Temperature (◦ C) Relative humidity (%) Wind Speed (km/h)
Assessment timepoints Baseline
Month 1
Month 2
Month 3
439 ± 29 52 ± 4 22 ± 3 26 ± 4 52 ± 4 22 ± 3 25 ± 4 52 ± 4 23 ± 3 25 ± 4
430 ± 26 47 ± 11* 23 ± 5 29 ± 8 47 ± 11* 24 ± 5 29 ± 8* 47 ± 11* 24 ± 5 29 ± 8* 43.8 ± 9.1 5782 ± 1512 4390 ± 1944 245 ± 155 14 ± 4 43 ± 9 8±2
429 ± 50* 49 ± 8 23 ± 5 27 ± 5 50 ± 6 24 ± 4 27 ± 4 49 ± 6 24 ± 5 27 ± 4 35.9 ± 6.2 4749 ± 861 6326 ± 1897 363 ± 183 13 ± 2 70 ± 8 16 ± 5
425 ± 27** 53 ± 4 22 ± 3 25 ± 4 52 ± 4 23 ± 3 25 ± 4 51 ± 4 24 ± 3 25 ± 4 115.5 ± 11.1 8936 ± 3249 5543 ± 2870 953 ± 429 18 ± 2 28 ± 5 13 ± 0
14 ± 4 66 ± 31 18 ± 5
Significantly different from baseline *p < 0.05, ** p < 0.01. Data are mean ± SD. PlayerLoad = PL1D; Medio-Lateral = side; Vertical = up; Anterior-Posterior = fwd.
in PL1Dside% were associated with 2 kmTT performance, this finding must be interpreted in the context of 2 kmTT performance improving over the pre-season training period. It is unclear whether changes in PL1Dside% would be associated with decreases in 2 kmTT performance following cessation of training, or induction of fatigue. Future studies are required to evaluate this. The mechanisms underlying the observed positive association between PL1Dside% and 2 kmTT are not clear. However, a recent analysis of the effects of fatigue on movement patterns in ballet dancers18 showed that the lateral displacement of the centre of mass during the performance of standardised movements was increased when fatigued. This increased lateral movement may be due to impaired muscular strength and loss of postural control,19 with the loss of postural control being a result of altered proprioceptive feedback from the fatigued muscles.20,21 Thus, in the present study a greater PL1Dside% during the second and third minutes of the SSRT at the start of pre-season, when 2 kmTT performance was slower, may have been a result of poorer muscular strength and postural control while running at 8˜ km/h. As the training load in the current study was increased from baseline to M-3 the athletes may have adapted positively to the increased training load, resulting in improvements not only in their 2 kmTT running performance, but also increasing their muscular strength and postural control. Irrespective of the mechanism by which PL1Dside% was reduced when 2 kmTT performance was improved, the present finding is consistent with previous work which investigated the effects of neuromuscular fatigue on PlayerLoad vectors during standardized small sided games in high performance soccer players.22 In that study it was found that when a standardized small sided game was performed weekly, PL1Dside% during those small sided games was increased when neuromuscular fatigue was present. Neuromuscular fatigue was identified by a decrease in flight time to contact time ratio during a maximal countermovement jump. The data from the present study extended those findings to show that a similar change in movement pattern occurred with changes in endurance running performance, but also that there was a linear relationship between PL1Dside% assessed during SSRT and 2 km TT performance. Previous research also found a reduction in the PL1Dup% when neuromuscular fatigue was present.15,16 However, no relationship between running performance changes and PL1Dup% was evident
in the present study. During running, vertical displacement is influenced by a range of factors, including running velocity, stride frequency and length, contact time and flight time,23 with reductions in vertical displacement occurring as running speed increases in an effort to maintain running efficiency as muscle force production and energy expenditure increase.24,25 These reductions in vertical displacement to maintain running efficiency have been interpreted as representing vertical stiffness,26 a key characteristic of high intensity running performance that has been shown to be reduced in the presence of fatigue,27,28 with it being suggested that this reduces impact force transmission through the body to protect anatomical structures from damage.25 Thus, the lack of change in PL1Dup%, and the lack of any relationship with 2 kmTT in the present study, may be due to the submaximal nature of the running during SSRT, which was performed at 8˜ km/h. The previous studies which identified changes in PL1Dup% found these when performing 50 m run through at an average speed of 22.5 km/h,16 or during the performance of small-sided soccer games15 which would have included passages of high speed running. Thus, the difference in findings of these studies may be related to differences in running speed. However, the submaximal nature of the SSRT is an important advantage as it is unlikely to exacerbate any underlying fatigue,29 and could therefore be performed during a pre-training warm-up without disruption to the training program. The results could then be used to inform changes to training based on how an athlete had been responding to the training load. While PL1Dside% during the second and third minutes of SSRT was positively related to 2 kmTT as running performance improved across the preseason, no such relationship was found with PL1Dside% during the first minute of the SSRT. This may be because, during the first minute of SSRT, the athletes accelerated from a standing start to running at 8˜ km/h, and the acceleration may have resulted in greater variation in movement that might have masked any subtle overall change in movement pattern. However, by the second and third minutes of the SSRT the athletes had likely reached a steady-state in terms of running gait, thus reducing movement variation and making it possible to detect subtle but consistent changes in movement pattern. Due to the positive associations between PL1Dside% and 2 kmTT performance being similar during both the second and third minutes of the SSRT, the SSRT could be performed over as little as a two-minute period to minimise disruption to training.
Please cite this article in press as: Garcia-Byrne F, et al.Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players. J Sci Med Sport (2019), https://doi.org/10.1016/j.jsams.2019.12.003
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Fig. 1. Relationships between PlayerLoad Medio-lateral vector (PlayerLoad medio-lateral 1D) and two kilometre time trial run time assessed during the first (Panel A), second (Panel B) and third (Panel C) minutes of a standardized submaximal running test. Different symbols represent different athletes.
5. Conclusion Changes in endurance exercise performance were associated with changes in movement patterns during the second and third minutes of the SSRT. PL1Dside% was positively related to 2 kmTT such that as 2 kmTT performance improved across the
preseason, PL1Dside% reduced. This indicated that as athletes performed better in the 2 kmTT they exhibited less lateral sway when running at 8˜ km/h. The SSRT could be used to assess how endurance exercise performance is responding to changes in training load without the necessity of asking athletes undertake a 2 kmTT.
Please cite this article in press as: Garcia-Byrne F, et al.Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players. J Sci Med Sport (2019), https://doi.org/10.1016/j.jsams.2019.12.003
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Please cite this article in press as: Garcia-Byrne F, et al.Accelerometer detected lateral sway during a submaximal running test correlates with endurance exercise performance in elite Australian male cricket players. J Sci Med Sport (2019), https://doi.org/10.1016/j.jsams.2019.12.003