Energetic Analysis of Running Demands in Australian Football using Global Positioning Systems Technology

Adrian Gray (2011). Energetic Analysis of Running Demands in Australian Football using Global Positioning Systems Technology PhD Thesis, School of Human Movement Studies, The University of Queensland.

       
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Author Adrian Gray
Thesis Title Energetic Analysis of Running Demands in Australian Football using Global Positioning Systems Technology
School, Centre or Institute School of Human Movement Studies
Institution The University of Queensland
Publication date 2011-09
Thesis type PhD Thesis
Supervisor Associate Professor David Jenkins
Professor Dennis Taaffe
Total pages 158
Total black and white pages 158
Language eng
Subjects 11 Medical and Health Sciences
Abstract/Summary Global positioning system (GPS) technology is used in Australian football and other field based team sports to assess player movement. The overarching aims of the studies in this thesis were to evaluate the accuracy and reliability of GPS technology for use in field based team sports and to derive greater physiological meaning from GPS technology used to describe the demands of Australian football competition. Study One assessed the effects of movement intensity and path linearity on the validity and reliability of GPS distance data. One participant wore eight 1 Hz GPS receivers while walking, jogging, running and sprinting over linear and non-linear 200 m courses. Five trials were performed at each movement intensity on each 200 m course. The results showed the mean (± SD) and percent bias of the GPS distance values on the 200 m linear course were 205.8 ± 2.4 m (2.8%), 201.8 ± 2.8 m (0.8%), 203.1 ± 2.2 m (1.5%) and 205.2 ± 4 m (2.5%) for the walk, jog, run and sprint trials respectively. Walk and sprint distances were significantly different from jogging and running distances (p<0.05). GPS distance values from the 200 m non-linear course were 198.9 ± 3.5 m (-0.5%), 188.3 ± 2 m (-5.8%), 184.6 ± 2.9 m (-7.7%) and 180.4 ± 5.7 m (-9.8%) for the walk, jog, run and sprint trials respectively; these were significantly lower than data for corresponding speeds on the linear course (p<0.05). Differences were significant between all non-linear movement intensities (p<0.05). Overall coefficients of variation were 2.6% and 2.8% within and between receivers, respectively. Study Two assessed and compared the accuracy and reliability of 1 and 5 Hz non-differential GPS Doppler velocity data in response to variations in path linearity and movement intensity. Timing gates were arranged along one straight and three circular paths of varying radii. Four participants completed 20 trials on each path at four intensities (walk, jog, run and sprint) whilst wearing 8 GPS receivers of the same model (1 Hz or 5 Hz). Individual Doppler velocity samples (i.e. GPS) were compared with velocity determined by chronometry. Inter-receiver reliability was also assessed. GPS velocity was most accurate when walking (~88% within ± 0.2 m∙s-1 of actual velocity) and least accurate when sprinting (~44%), with all paths combined (1 and 5 Hz). Over straight paths, 1 Hz receivers were more accurate than 5 Hz receivers (74% within ± 0.2 m∙s-1 vs. 60% respectively). Over circular paths with both 1 and 5 Hz receivers, velocity error tended to increase as path radius reduced. Path and intensity were independent predictors (p < 0.001) of velocity error, accounting for 8.2% and 7.0% of the error for 1 and 5 Hz receivers, respectively. There was greater variation among 1 Hz receivers (~4.2% to ~30%) than among 5 Hz receivers (< 10%). The purpose of Study Three was to present a new method to estimate energy cost and metabolic power during overground running, with particular reference to the mechanical determinants of energy expenditure during constant velocity, accelerated and decelerated running. On flat terrain, running mechanics are largely dependent on movement velocity (v). Relationships between cyclic mechanical aspects of running and forward running velocity were used to model the mechanical work of brief running bouts tracked using 5 Hz GPS receivers. Energy cost and metabolic power were then derived. In simulated steady state running, the model predicted energy cost and metabolic power to increase curvilinearly with running velocity. At 3 m⋅s-1, the cost of supporting body weight and swinging the limbs were 61% and 36% respectively. The energetic cost of swinging the limbs predominated at higher velocities. Energy cost per unit distance was found to be greatest at the onset of maximal sprint efforts (~20 J·m-1·kg-1), with metabolic power peaking at ~70 W⋅kg-1 prior to reaching maximal velocity. Peak energy cost per unit distance and peak metabolic power were much lower during deceleration (~10 J·m-1·kg-1 and ~45 W⋅kg-1, respectively). The energy cost attributable to changing the horizontal velocity of the centre of mass (COM) is > 1/3 of the total energy cost during short, intense running bouts. Study Four used GPS technology to model the energy cost and metabolic power of Australian football competition. The aim was to describe the metabolic demands of different playing positions in elite Australian football competition; and to evaluate the utility of energy expenditure as a monitoring tool. The model introduced in Study Three was used to estimate energy expenditure and metabolic demands of 24 elite Australian football players tracked during the 2010 AFL season using 5 Hz GPS receivers. Players were allocated to 4 positional groups: midfielders (n= 74 files), ruckmen (n= 24 files), small forwards/backs (n= 78 files) and key forwards/backs (n= 76 files). Total energy expenditure ranged from ~46-63 kJ·kg-1 equivalent to running 11.5- 15.7 km at a steady aerobic pace. Time on-field, distance travelled, total energy expenditure and the rates of energy expenditure varied between playing positions. Midfielders were found to expend the most energy between moderate aerobic and light anaerobic metabolic rates (10- 35 W⋅kg-1). Ruckmen expended the least energy overall, and ranked lower on energetic indices of running intensity. Key and small forwards/backs had more intermittent running profiles. Small forwards/backs expended the most energy at high exercise intensities (>55 W⋅kg-1) followed by key forwards/backs. Key forwards/backs expended the most energy at low intensities (<10 W⋅kg-1). Changing forward running velocity accounted for ~24%, of the total energy expenditure for all positions. Collectively the four studies presented in this thesis provide new insight into the application of GPS technology in Australian football and other field based team sports. Study One identified that path linearity and movement intensity influence the accuracy of GPS distance measurements. These were attributed to inherent positioning errors within the GPS system and update rate. The reliability of GPS distance measures decreases with movement intensity. Variations in movement intensity and path linearity were also found to influence the accuracy of GPS velocity measurement in both 1 and 5 Hz non-differential GPS receivers. An increased update rate resulted in only marginal improvements in velocity accuracy during non linear movement. Users of this technology must consider these inherent limitations of the GPS system when interpreting GPS data collected during field based team sports. The findings in Study Three suggest the proposed energetic model provides reasonable estimates of energy expenditure at changing and constant running velocities. When evaluating intermittent running profiles, metabolic power derived using GPS modelling provides a useful index of running intensity as it reflects the interaction between absolute running velocity and the rate of change in velocity. The energy cost of changing forward velocity contributes largely to the total energy cost of brief intense running efforts and should be considered when evaluating the running demands of field based team sports. Study Four demonstrated that the energy cost of Australian football is similar to that found for soccer, and the demands are position specific. The routine use of energy expenditure and energetically derived indices of running intensity appears a valid approach to match analysis as trends identified using these methods revealed findings consistent with recent analyses of Australian football match play.
Keyword energy cost
match analysis
athlete monitoring
GPS
work
power
locomotion
Additional Notes Pages to print in colour: None Pages to print in landscape: 50, 75, 79, 115, 116, 117, 152 & 153.

 
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Created: Tue, 17 Jan 2012, 14:20:12 EST by Adrian Gray on behalf of Library - Information Access Service