Rapid Directional Change Degrades GPS Distance
Measurement Validity during Intermittent Intensity
Running
Jonathan C. Rawstorn1, Ralph Maddison2, Ajmol Ali3, Andrew Foskett3, Nicholas Gant1*
1 Exercise Metabolism Laboratory, Department of Sport and Exercise Science, The University of Auckland, Auckland, New Zealand, 2 National Institute for Health
Innovation, School of Population Health, The University of Auckland, Auckland, New Zealand, 3 School of Sport and Exercise, Massey University, Auckland, New Zealand
Abstract
Use of the Global Positioning System (GPS) for quantifying athletic performance is common in many team sports. The effect
of running velocity on measurement validity is well established, but the influence of rapid directional change is not well
understood in team sport applications. This effect was systematically evaluated using multidirectional and curvilinear
adaptations of a validated soccer simulation protocol that maintained identical velocity profiles. Team sport athletes
completed 90 min trials of the Loughborough Intermittent Shuttle-running Test movement pattern on curvilinear, and
multidirectional shuttle running tracks while wearing a 5 Hz (with interpolated 15 Hz output) GPS device. Reference total
distance (13 200 m) was systematically over- and underestimated during curvilinear (2.6160.80%) and shuttle
(23.1762.46%) trials, respectively. Within-epoch measurement uncertainty dispersion was widest during the shuttle trial,
particularly during the jog and run phases. Relative measurement reliability was excellent during both trials (Curvilinear
r = 1.00, slope = 1.03, ICC = 1.00; Shuttle r = 0.99, slope = 0.97, ICC = 0.99). Absolute measurement reliability was superior
during the curvilinear trial (Curvilinear SEM = 0 m, CV = 2.16%, LOA 6 223 m; Shuttle SEM = 119 m, CV = 2.44%, LOA 6
453 m). Rapid directional change degrades the accuracy and absolute reliability of GPS distance measurement, and caution
is recommended when using GPS to quantify rapid multidirectional movement patterns.
Citation: Rawstorn JC, Maddison R, Ali A, Foskett A, Gant N (2014) Rapid Directional Change Degrades GPS Distance Measurement Validity during Intermittent
Intensity Running. PLoS ONE 9(4): e93693. doi:10.1371/journal.pone.0093693
Editor: Dylan Thompson, University of Bath, United Kingdom
Received January 5, 2014; Accepted March 7, 2014; Published April 14, 2014
Copyright:  2014 Rawstorn et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was funded by The University of Auckland. The funders had no role in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: n.gant@auckland.ac.nz
Introduction
Use of Global Positioning System (GPS) technology as a
performance analysis tool is increasingly common in a number of
team sports [1–15]. Several studies have been dedicated to
assessing the validity of GPS devices for this purpose, although
newer devices have also been used without prior validation [13–
15].
Despite
considerable
variation
in
experimental
design
previous investigations report small relative distance and velocity
measurement uncertainties, and prevailing conclusions support the
use of GPS devices during team sport activities [16–25].
While GPS devices appear acceptably valid for quantifying
performance across entire bouts of exercise, sport scientists,
coaches and governing bodies have shown particular interest in
quantifying the high intensity activity demands of match-play
[6,7,10,26,27]. The utility of GPS for monitoring performance is
contingent on accurate and reliable measurement of these
activities, which play a critical role in determining athletes’
physiological load, and competitive match outcomes [28–31].
Sprinting and rapid acceleration are consistently associated with
increased GPS measurement uncertainty, particularly over short
distances [16,19,22,23,32,33]. Thus it appears likely that GPS
devices underestimate some movement patterns that are of critical
importance during training and match-play.
While the effect of running velocity on GPS measurement
validity is well established little attention has been directed toward
determining the effect of rapid directional change. As athletes may
execute ,550–730 turning movements during match-play [28,34]
it is important to determine whether rapid directional change
affects GPS measurement validity. One investigation has com-
pared GPS measurement validity during linear and non-linear
running, and rapid directional change was associated with reduced
measurement validity [18]. However, differing self-selected veloc-
ity profiles between the linear and non-linear protocols make it
difficult to determine whether this effect was caused by differing
directional demands, velocity demands, or a combination of both.
Thus there remains a need to systematically determine whether
rapid directional change effects GPS distance measurement
validity during exercise protocols with equivalent velocity profiles,
but differing directional demands.
The Loughborough Intermittent Shuttle-running Test (LIST) is
a precisely controlled intermittent intensity shuttle-running proto-
col designed to simulate the activity patterns of soccer [35]. The
LIST is representative of the total distance, number of sprints and
number of turns common to match-play, and induces similar
physiological responses [35,36]. Furthermore, precise control over
velocity throughout the LIST facilitates systematic evaluation of
the effect rapid directional change exerts on GPS measurement
PLOS ONE | www.plosone.org
1
April 2014 | Volume 9 | Issue 4 | e93693
validity by allowing modification of directional demands without
altering the velocity profile.
Many early investigations evaluated GPS devices featuring a
1 Hz sampling frequency, yet more recent devices with faster
sampling frequencies have demonstrated improved measurement
validity during linear and multidirectional running [19,22,33]. A
novel device comprising a 5 Hz GPS microcontroller and an
interpolation algorithm that outputs positional data at a 15 Hz
frequency was recently utilised to investigate the movement
demands of soccer, rugby union and rugby sevens [13–15];
however, the distance measurement validity of this device has yet
to be evaluated. Therefore, the aim of this study was to
systematically assess the effect of rapid directional change on the
distance measurement validity of a previously untested GPS
device. It was hypothesised that rapid directional change would
reduce distance measurement validity.
Materials and Methods
Ethics statement
This study received approval from the University of Auckland
Human Participants Ethics Committee. All volunteers provided
written informed consent prior to participation.
Participants
Six amateur club and provincial level team sport athletes
(age = 24.161.6 y,
body
mass = 72.56610.33 kg,
height = 1.7960.09 m,
_VO2 max~54:46+4:19 ml:kg)
volun-
teered to participate in this study.
Experimental protocol
During a preliminary trial participants completed a multi-stage
fitness test to estimate maximal oxygen consumption ( _VO2max),
and determine running velocities for each phase of the LIST, as
previously described [37]. Participants also completed a 15 min
bout of the LIST while wearing the GPS device to familiarise
themselves with the movement pattern, and device operation.
Participants completed two experimental trials in random order,
within 7 days. Participants completed <90 min of the LIST
movement pattern on shuttle or curvilinear running tracks. The
movement pattern comprised sequential walk (60 m, veloci-
ty = 1.54 m?s21), sprint (15 m, maximal velocity; 5 m decelera-
tion), run (60 m, velocity eliciting 95% _VO2max) and jog (60 m,
velocity eliciting 55% _VO2max) phases, as previously described
[35,38]. This cycle was repeated 11 times (<15 min) during each
of six exercise blocks. Exercise blocks were separated by 3 min rest
periods. Reference cycle, block and trial distances were 200 m,
2 200 m, and 13 200 m, respectively. Identical regulation of
movement velocity during both trials, via standardised auditory
commands, ensured movement demands differed only in the
presence (shuttle) or absence (curvilinear) of rapid directional
change. Moreover, velocity regulation controlled for potential
disruptive effects of environment or other extraneous variables on
participants’ performance and, therefore, on reference measures.
Schematic and satellite representations of the shuttle and
curvilinear protocols are displayed in Figure 1. Briefly, the shuttle
protocol was completed on a marked 20 m shuttle-running track
similar to that described by Nicholas et al. [35], and the curvilinear
protocol was completed on a marked oval track on a level athletic
playing surface. The curvilinear track was designed such that one
lap represented one 200 m movement cycle, the 20 m sprint
followed a linear path and turn radii (25.5 m) were optimised to
minimise rapid directional change. Markings at 20 m intervals
along the curvilinear track facilitated adherence to velocity
regulation commands as per the shuttle protocol. A foam impact
mat precluded excess displacement following sprint phases during
both trials. The mat was temporarily withdrawn after impact
during the curvilinear trial to prevent participant deviation from
the marked track. Participants who chose not to use the impact
mat to aid deceleration were instructed to proceed to the mat after
deceleration to ensure the correct distance was covered. A
researcher monitored adherence to marked running tracks in
order to prevent deviation. The shuttle and curvilinear tracks were
located away from large buildings to minimise multi-pathing error
and ensure clear line of sight to orbiting satellites. Track lengths
were measured with a calibrated surveyor’s wheel.
GPS Device
A non-differentially corrected GPS device (SPI Pro X, GPSports
Systems, Australia) was worn in a harness between the scapulae, as
per manufacturer’s instructions. The device comprises a 5 Hz
GPS microcontroller and a proprietary interpolation algorithm
that outputs positional data at a 15 Hz frequency. The 15 Hz
interpolation is suggested to enhance measurement accuracy
compared to the raw 5 Hz data; however, technical specifications
regarding this algorithm were unavailable and it is not possible to
determine its effect on distance measurement validity. GPS devices
do not directly measure distance; however, researchers and
practitioners in the team sport domain are frequently interested
in assessing distance rather than positional coordinates. Therefore
terms related to ‘distance measurement’ are used throughout this
paper, in preference to ‘distance calculation’, as they hold intuitive
relevance in this field.
Raw 15 Hz GPS data were downloaded using the manufactur-
er’s proprietary software (Team AMS v2.1), and exported for
manual analysis. Data recorded outside the six exercise blocks
were excluded from analyses. Distances were calculated within the
proprietary software and no post processing was applied to raw
GPS data. Precise velocity regulation allowed calculation of
reference distances at the same frequency as the GPS data. The
15 Hz output frequency was expected to yield <80 000 observa-
tions per trial. Consistent with the aim of this study, additional
variables calculated by the proprietary software (e.g. speed,
acceleration, impact, body load) were not analysed.
Data Analysis
Statistical analyses were performed using PASW (v18.0, SPSS
Inc., USA). Measurement validity was considered to constitute
accuracy and reliability, and a multifaceted statistical approach
was implemented to assess these. Measurement accuracy was
evaluated by calculating total, and within-epoch biases between
GPS and reference distance measures. Two-tailed paired t-tests
were performed to test the null hypothesis H0: distanceGPS = dis-
tancereference for each protocol. These tests determined whether
GPS measures differed systematically from reference distances;
however, they cannot be used as the sole indicators of agreement
[39]. Factorial analysis of variance was also performed to detect
effects of TRIAL (i.e. Shuttle and Curvilinear) and MOVEMENT PHASE
(i.e. Walk, Jog, Run and Sprint) on GPS distance measurement
biases. That is, the null hypotheses H0: biascurvilinear = biasshuttle,
and
H0:
biaswalk = biasjog = biasrun = biassprint
were
tested
to
determine whether GPS uncertainties were systematically affected
by the presence of rapid directional change and/or differing
movement velocities. Statistically significant interactions were
explored using Bonferroni corrected paired comparisons. Previous
data indicate 99 observations will provide 95% statistical power to
detect a 5% difference between GPS and reference distance
GPS Validity during Multidirectional Running
PLOS ONE | www.plosone.org
2
April 2014 | Volume 9 | Issue 4 | e93693
measures, assuming a standard deviation (SD) of 13.6% (Cohen’s
d = 0.37) [25]. Data were subjected to Levene’s test for equality of
error variances. Data displayed heteroscedastic error variance
(Shuttle p = 0.001; Curvilinear p,0.001) and were logarithmically
transformed and reanalysed. To aid interpretation data are
reported in the unit of measurement, or relative to reference
measures.
Relative measurement reliability was evaluated by calculating
Pearson’s correlation coefficients (r), regression coefficients (slope)
and two-way random-effects intraclass correlation coefficients
(ICC) [39,40]. These statistics describe the reliability with which
GPS distance increases as a function of reference distance, but are
not indicative of agreement between measurement tools [41].
Absolute measurement reliability was evaluated by calculating the
standard error of measurement
SEM:SD|
ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ
1{ICC
p


, coef-
ficient of variation
ðCV~100  (SD=x)
Þ and 95% limits of
agreement
ðLOA~x+1:96  SD
Þ [39,41]. These statistics indi-
cate total measurement uncertainty (i.e. systematic+random error),
and facilitate comparisons between experiments using different
designs [42]. In-text data are reported as mean 6 SD. Statistical
significance for all calculations was set at a,0.05.
Results
Satellite acquisition during curvilinear (8.1961.82 satellites) and
shuttle (8.4461.57 satellites) trials was consistent with several
previous
studies
evaluating
GPS
measurement
validity
[18,19,21,23,33].
Measurement accuracy
Compared to the 13 200 m reference, distance was statistically
significantly
overestimated
during
the
curvilinear
trial
(13 543.926105.45 m; T431 870 = 772.40, p,0.001) and underes-
timated
during
the
shuttle
trial
(12 780.686325.61 m;
T460 226 = 2403.35, p,0.001). The between-trial bias was also
statistically significant (F1, 892 090 = 386 116.42, p,0.001).
Statistically significant effects of MOVEMENT PHASE on measure-
ment bias were detected during the curvilinear (F3, 431 867 = 31.23,
p,0.001) and shuttle trials (F3, 460 223 = 15.42, p,0.001), although
these differences were small (Table 1). Within-epoch biases during
each movement phase are depicted graphically in Figure 2. The
dispersion of within-epoch biases was widest during the shuttle
trial. This effect was particularly evident during the Jog and Run
phases, when bias dispersion approximated that of the sprint
phase.
Measurement Reliability
Table 2 summarises the relative and absolute reliability of GPS
distance measures. GPS and reference distance were strongly
correlated during curvilinear and shuttle trials (Table 2), indicating
excellent relative measurement reliability. Moreover, regression
coefficients approximated 1 during both trials (Table 2). Absolute
reliability metrics (SEM, LOA and CV) were larger during the
shuttle trial (Table 2) indicating superior absolute measurement
reliability during the curvilinear protocol.
Discussion
This study utilised a movement pattern that is representative of
key aspects of high level team sport match-play to systematically
evaluate the effect of rapid directional change on the distance
measurement validity of a previously untested GPS device. The
main finding is that rapid directional change degrades GPS
Figure 1. Schematic and satellite representations of shuttle and curvilinear running tracks. Satellite representations comprise typical
positional data from one shuttle and curvilinear trial. IR = Infrared.
doi:10.1371/journal.pone.0093693.g001
GPS Validity during Multidirectional Running
PLOS ONE | www.plosone.org
3
April 2014 | Volume 9 | Issue 4 | e93693
distance measurement accuracy and absolute reliability, and this
effect is independent of movement velocity.
The systematic positive bias between GPS and reference
distances during the curvilinear trial is consistent with previous
investigations employing running protocols with similarly low
directional demands [18,24]. Multidirectional running protocols
are also associated with systematic distance measurement biases,
but the magnitude and direction of uncertainty is inconsistent
[16,18,25,33]. The negative distance measurement bias during the
shuttle trial is consistent with uncertainties reported during
simulated court sports, team sports and non-linear running
[18,33]; however, positive biases have been reported during field
hockey and team sport simulations [16,25].
Consistent with the present results, the only previous study to
evaluate the effect of multidirectional demands on GPS distance
measurement validity reported positive and negative biases during
linear and multidirectional running, respectively, with the largest
absolute bias during non-linear running [18]. However, the self-
selected velocity profiles differed between trials and it is unclear
whether measurement validity was affected by differing directional
demands, velocity demands, or a combination of these. Identical
velocity regulation during the curvilinear and shuttle trials in the
present study controlled for any effect of movement velocity on
distance measurement validity. Thus the present findings indicate
rapid multidirectional movement patterns degrade GPS distance
measurement validity, and that this effect is independent of
movement velocity.
Excellent relative measurement reliability during curvilinear
and shuttle trials are consistent with previous investigations
[16,25,32]. Nonetheless, larger absolute reliability metrics during
the shuttle trial demonstrate reduced distance measurement
validity during rapid multidirectional movement patterns.
The magnitude of shuttle trial distance measurement uncer-
tainty was 3.17%. Uncertainties of similar magnitudes have
previously underpinned support for the use of GPS technology
during team sport-related activities [16,18–25]. Indeed, when
applied to a time-motion analysis of elite soccer match-play this
uncertainty indicates match distance (10 627–12 027 m) may be
underestimated by just 340–380 m, depending upon playing
position [43]. In addition to the magnitude of uncertainty;
however, it is also important to consider which movement patterns
will be most affected by this inaccuracy. As rapid multidirectional
movements are an important determinant of physiological load
and match outcomes [28–31] the present results suggest GPS
devices are likely to misrepresent some critical aspects of match-
play. This has important implications for the way in which GPS
technology is used in the team sport domain. As GPS measure-
ment
validity
is
also
reduced
during
sprinting
and
rapid
acceleration [16,19,22,23,32,33] it appears GPS may not be an
appropriate tool for evaluating match-play activity profiles, or
monitoring athletes’ physiological load. Given that iterative device
development (i.e. newer hardware and software components) and
faster sampling frequencies are proposed to improve GPS
measurement validity [16,19,22,33], this is particularly pertinent
when utilising devices featuring older componentry and/or slower
sampling frequencies.
Body lean angle is proposed to account for a substantial
proportion of negative distance measurement bias during high
speed nonlinear running [18,44] and the proximal anatomical
position of the present device predisposes it to similar uncertainty.
This should be an important consideration when attempting to
evaluate the criterion validity of GPS devices; however, post-hoc
correction for lean angle would contrast the aim of this study by
reducing its ecological validity and misrepresenting the measure-
ment accuracy likely to be realised during real-world use. The
Figure 2. Within-epoch measurement uncertainty during shuttle and curvilinear trials. Solid reference lines = mean bias. Dashed reference
lines = 95% limits of agreement. Differing sample sizes reflect discrepant mean sampling frequencies (Shuttle = 14.1560.20 Hz; Curvili-
near = 13.2761.44 Hz), which were below the specified 15 Hz interpolation frequency.
doi:10.1371/journal.pone.0093693.g002
Table 1. Distance measurement biases during shuttle and curvilinear adaptations of the Loughborough Intermittent Shuttle-
running Test.
Protocol
Total (%)
Walk (%)
Jog (%)
Run (%)
Sprint (%)
Shuttle
22.1663.84*
22.1864.23j r s
22.2063.42w s
22.1663.41w s
21.9263.63w j r
Curvilinear
2.9962.96
2.9964.06j r s
2.9561.12w s
2.9561.33w s
3.1661.87w j r
Table reports mean (6 s) within-epoch measurement biases relative to reference measures.
*Statistically significantly different to the curvilinear trial (p,0.001).
w j r sStatistically significantly different to the Walk, Jog, Run or Sprint movement phases (p,0.001).
doi:10.1371/journal.pone.0093693.t001
GPS Validity during Multidirectional Running
PLOS ONE | www.plosone.org
4
April 2014 | Volume 9 | Issue 4 | e93693
effect of device position on measurement validity should be
addressed during product development, when it can be balanced
against other design constraints such as comfort, player safety and
device exposure to impact.
The reduction in distance measurement validity during the
shuttle trial may be explained by examining the interaction
between movement demands and GPS position sampling. As
intermittent GPS sampling partitions continuous movement paths
into discrete linear segments, GPS devices are constrained to
calculating cumulative device displacement across individual
sampling epochs. While distance may be accurately quantified
by displacement during linear movements, it will be underesti-
mated when non-linear movements occur within a sampling
epoch. Moreover, as rapid multidirectional movements will likely
cause frequent separation between distance and displacement, the
negative measurement uncertainty introduced by intermittent
GPS sampling is likely to be largest during many of the most
critical match-play activities.
While uncertainty induced by intermittent position sampling
will affect all GPS devices, this mechanism may also explain the
superior measurement validity of higher frequency devices during
multidirectional running [19,33]. Faster sampling frequencies
increase the resolution with which continuous movement paths are
partitioned into linear segments and, therefore, can be expected to
reduce the magnitude of separation between device distance and
displacement during non-linear movements. Nonetheless, sub-
optimal distance measurement validity during the shuttle trial
indicates the present device’s 5 Hz sampling frequency and/or
15 Hz interpolation algorithm are insufficient to accurately
quantify
distance
during
rapid
directional
change.
Further
research is required to determine the optimal sampling frequency
for quantifying performance during multidirectional movement
patterns, such as those common to many team sports.
The proposed mechanism underlying distance measurement
uncertainty cannot account for the positive distance bias recorded
during curvilinear trials. This uncertainty is consistent with
previous investigations [18,24] yet its source remains unclear.
Participant deviation outside the marked curvilinear running
track, perhaps due to intentional protocol non-adherence or the
neuromuscular fatigue induced by the LIST [45], would manifest
positive measurement bias. However, adherence to marked
running tracks and the precisely controlled velocity profile were
monitored throughout all trials to preclude these confounds.
Device-specific software components are proposed to affect
measurement validity [16], but proprietary protection of these
components makes evaluation of their contribution to measure-
ment uncertainty problematic. Indeed, the contribution of the
present device’s 15 Hz interpolation algorithm to the observed
measurement uncertainty remains unclear. Nonetheless, software
components cannot account for the between-trial differences in
measurement validity as device configuration remained identical
throughout the study.
It is important to note that, although the LIST movement
pattern is representative of several key aspects of match-play [35]
and offers advantages for validating GPS devices compared to
previous methodologies, it remains difficult to accurately simulate
the complexity of match-play within a controlled environment.
This limitation is common to all similar investigations, and should
be considered when attempting to generalise these findings to
match-play.
As multiple units of the present device were not simultaneously
compared it remains unclear whether inter-unit variability will
preclude interchangeable use of devices among multiple athletes,
and caution should be taken when comparing data between
devices.
This study used the movement pattern of a precisely controlled
exercise protocol that is representative of several key aspects of
soccer match-play to systematically assess the effect of rapid
multidirectional
movements
on
GPS
distance
measurement
validity. Rapid directional change degrades GPS distance mea-
surement validity, and this effect is independent of movement
velocity. Caution is recommended when relying on GPS to
quantify team sport athletes’ performance as current device
technology appears unable to accurately quantify movements that
play a critical role in determining physiological load and
competitive match outcomes.
Author Contributions
Conceived and designed the experiments: JR RM AA AF NG. Performed
the experiments: JR NG. Analyzed the data: JR NG. Contributed
reagents/materials/analysis tools: JR RM AA AF NG. Wrote the paper:
JR RM AA AF NG.
References
1. Coughlan GF, Green BS, Pook PT, Toolan E, O’Connor SP (2011) Physical
game demands in elite rugby union: a global positioning system analysis and
possible implications for rehabilitation. Journal of Orthopaedic and Sports
Physical Therapy 41: 600–605.
2. Hiscock D, Dawson B, Heasman J, Peeling P (2012) Game movements and
player performance in the Australian Football League. International Journal of
Performance Analysis in Sport 12: 531–545.
3. Jennings DH, Cormack SJ, Coutts AJ, Aughey RJ (2012) International field
hockey players perform more high-speed running than national-level counter-
parts. Journal of Strength & Conditioning Research 26: 947–952.
4. Brewer C, Dawson B, Heasman J, Stewart G, Cormack S (2010) Movement
pattern comparisons in elite (AFL) and sub-elite (WAFL) Australian football
games using GPS. Journal of Science and Medicine in Sport 13: 618–623.
5. Coutts AJ, Quinn J, Hocking J, Castagna C, Rampinini E (2010) Match running
performance in elite Australian Rules Football. J Sci Med Sport 13: 543–548.
6. Cunniffe B, Proctor W, Baker JS, Davies B (2009) An evaluation of the
physiological demands of elite rugby union using Global Positioning System
tracking software. J Strength Cond Res 23: 1195–1203.
7. Macutkiewicz D, Sunderland C (2011) The use of GPS to evaluate activity
profiles of elite women hockey players during match-play. Journal of Sports
Sciences 29: 967–973.
8. Gabbett TJ (2010) GPS analysis of elite women’s field hockey training and
competition. J Strength Cond Res 24: 1321–1324.
9. Wisbey B, Montgomery PG, Pyne DB, Rattray B (2010) Quantifying movement
demands of AFL football using GPS tracking. J Sci Med Sport 13: 531–536.
10. MacLeod H, Bussell C, Sunderland C (2007) Time-motion analysis of elite
women’s field hockey, with particular reference to maximum intensity
movement patterns. Int J Perf Analysis Sport 7: 1–12.
11. McLellan CP, Lovell DI, Gass GC (2011) Performance analysis of elite Rugby
League match play using global positioning systems. Journal of Strength &
Conditioning Research 25: 1703–1710.
Table 2. GPS measurement reliability during shuttle and
curvilinear adaptations of the Loughborough Intermittent
Shuttle-running Test.
Protocol
r
Slope
ICC
SEM (m)
LOA (m)
CV (%)
Shuttle
0.99*
0.97
0.99*
119
6453
2.44
Curvilinear
1.00*
1.03
1.00*
0
6223
2.16
Table reports comparisons of GPS and reference distance measurement for
Pearson’s product-moment correlation (r), linear regression coefficient (Slope)
intraclass correlation coefficient (ICC), standard error of measurement (SEM),
Bland Altman’s absolute limits of agreement (LOA), and the coefficient of
variation (CV).
*p,0.001.
doi:10.1371/journal.pone.0093693.t002
GPS Validity during Multidirectional Running
PLOS ONE | www.plosone.org
5
April 2014 | Volume 9 | Issue 4 | e93693
12. Waldron M, Twist C, Highton J, Worsfold P, Daniels M (2011) Movement and
physiological match demands of elite rugby league using portable global
positioning systems. Journal of Sports Sciences 29: 1223–1230.
13. Del Coso J, Munoz-Fernandez VE, Munoz G, Fernandez-Elias VE, Ortega JF,
et al. (2012) Effects of a caffeine-containing energy drink on simulated soccer
performance. PLoS ONE [Electronic Resource] 7: e31380.
14. Del Coso J, Portillo J, Mun˜oz G, Abia´n-Vice´n J, Gonzalez-Milla´n C, et al. (2013)
Caffeine-containing energy drink improves sprint performance during an
international rugby sevens competition. Amino Acids: 1–9.
15. Del Coso J, Ramı´rez JA, Mun˜oz G, Portillo J, Gonzalez-Milla´n C, et al. (2012)
Caffeine-containing energy drink improves physical performance of elite rugby
players during a simulated match. Applied Physiology, Nutrition, and
Metabolism: 1–7.
16. Coutts AJ, Duffield R (2010) Validity and reliability of GPS devices for
measuring movement demands of team sports. J Sci Med Sport 13: 133–135.
17. Waldron M, Worsfold P, Twist C, Lamb K (2011) Predicting 30 m timing gate
speed from a 5 Hz Global Positioning System (GPS) device. International
Journal of Performance Analysis in Sport 11: 575–582.
18. Gray AJ, Jenkins D, Andrews MH, Taaffe DR, Glover ML (2010) Validity and
reliability of GPS for measuring distance travelled in field-based team sports.
Journal of Sports Sciences 28: 1319–1325.
19. Jennings D, Cormack S, Coutts AJ, Boyd L, Aughey RJ (2010) The validity and
reliability of GPS units for measuring distance in team sport specific running
patterns. International journal of sports physiology & performance 5: 328–341.
20. Johnston RJ, Watsford ML, Pine MJ, Spurrs RW, Murphy AJ, et al. (2012) The
validity and reliability of 5-Hz global positioning system units to measure team
sport movement demands. Journal of Strength & Conditioning Research 26:
758–765.
21. Portas MD, Harley JA, Barnes CA, Rush CJ (2010) The validity and reliability of
1-Hz and 5-Hz global positioning systems for linear, multidirectional, and
soccer-specific activities. International journal of sports physiology & perfor-
mance 5: 448–458.
22. Varley MC, Fairweather IH, Aughey RJ (2012) Validity and reliability of GPS
for measuring instantaneous velocity during acceleration, deceleration, and
constant motion. Journal of Sports Sciences 30: 121–127.
23. Waldron M, Worsfold P, Twist C, Lamb K (2011) Concurrent validity and test-
retest reliability of a global positioning system (GPS) and timing gates to assess
sprint performance variables. Journal of Sports Sciences 29: 1613–1619.
24. Edgecomb SJ, Norton KI (2006) Comparison of global positioning and
computer-based tracking systems for measuring player movement distance
during Australian football. J Sci Med Sport 9: 25–32.
25. MacLeod H, Morris J, Nevill A, Sunderland C (2009) The validity of a non-
differential global positioning system for assessing player movement patterns in
field hockey. J Sports Sci 27: 121–128.
26. Gray AJ, Jenkins DG (2010) Match analysis and the physiological demands of
Australian football. Sports Med 40: 347–360.
27. Wisbey B, Rattray B, Pyne DB (2009) Quantifying changes in AFL player game
demands using GPS tracking: 2009 AFL Season. AFL Research Board Report.
Melbourne: Australian Football League.
28. Carling C, Bloomfield J, Nelsen L, Reilly T (2008) The role of motion analysis in
elite soccer: contemporary performance measurement techniques and work rate
data. Sports Med 38: 839–862.
29. Dellal A, Keller D, Carling C, Chaouachi A, Wong del P, et al. (2010)
Physiologic effects of directional changes in intermittent exercise in soccer
players. Journal of Strength & Conditioning Research 24: 3219–3226.
30. Rampinini E, Bishop D, Marcora SM, Bravo DF, Sassi R, et al. (2007) Validity
of simple field tests as indicators of match-related physical performance in top-
level professional soccer players. Int J Sports Med 28: 228–235.
31. Spencer M, Lawrence S, Rechichi C, Bishop D, Dawson B, et al. (2004) Time-
motion analysis of elite field hockey, with special reference to repeated-sprint
activity. J Sports Sci 22: 843–850.
32. Barbero-Alvarez JC, Coutts A, Granda J, Barbero-Alvarez V, Castagna C (2010)
The validity and reliability of a global positioning satellite system device to assess
speed and repeated sprint ability (RSA) in athletes. J Sci Med Sport 13: 232–235.
33. Duffield R, Reid M, Baker J, Spratford W (2010) Accuracy and reliability of
GPS devices for measurement of movement patterns in confined spaces for
court-based sports. J Sci Med Sport 13: 523–525.
34. Bloomfield J, Polman R, O’Donoghue P (2007) Physical demands of different
positions in FA Premier League soccer. Journal of Sports Science and Medicine
6: 63–70.
35. Nicholas CW, Nuttall FE, Williams C (2000) The Loughborough Intermittent
Shuttle Test: A field test that simulates the activity pattern of soccer. Journal of
Sports Sciences 18: 97–104.
36. McGregor SJ, Nicholas CW, Drawer S, Grayson A, Williams C (1999)
Metabolic responses to fluid ingestion during prolonged intermittent high
intensity shuttle running. Proceedings of the Fourth Science and Football
Conference. Sydney University of Technology. pp. 54.
37. Ramsbottom R, Brewer J, Williams C (1988) A progressive shuttle run test to
estimate maximal oxygen uptake. British Journal of Sports Medicine 22: 141–
144.
38. Nicholas CW, Williams C, Lakomy HK, Phillips G, Nowitz A (1995) Influence
of ingesting a carbohydrate-electrolyte solution on endurance capacity during
intermittent, high-intensity shuttle running. J Sports Sci 13: 283–290.
39. Atkinson G, Nevill AM (1998) Statistical methods for assessing measurement
error (reliability) in variables relevant to sports medicine. Sports Medicine 26:
217–238.
40. Gant N, Atkinson G, Williams C (2006) The validity and reliability of intestinal
temperature during intermittent running. Medicine and Science in Sports and
Exercise 38: 1926–1931.
41. Bland JM, Altman DG (1986) Statistical methods for assessing agreement
between two methods of clinical measurement. Lancet 1: 307–310.
42. Atkinson G, Nevill AM (1998) Statistical methods for assessing measurement
error (reliability) in variables relevant to sports medicine. Sports Med 26: 217–
238.
43. Di Salvo V, Baron R, Tschan H, Calderon Montero FJ, Bachl N, et al. (2007)
Performance characteristics according to playing position in elite soccer.
Int J Sports Med 28: 222–227.
44. Townshend AD, Worringham CJ, Stewart IB (2008) Assessment of speed and
position during human locomotion using nondifferential GPS. Med Sci Sports
Exerc 40: 124–132.
45. Magalha˜es J, Rebelo A, Oliveira E, Silva JR, Marques F, et al. (2010) Impact of
Loughborough Intermittent Shuttle Test versus soccer match on physiological,
biochemical and neuromuscular parameters. Eur J Appl Physiol 108: 39–48.
GPS Validity during Multidirectional Running
PLOS ONE | www.plosone.org
6
April 2014 | Volume 9 | Issue 4 | e93693

Rapid directional change degrades GPS distance measurement validity during intermittent intensity running.
Rawstorn, Jonathan C,Maddison, Ralph,Ali, Ajmol,Foskett, Andrew,Gant, Nicholas