Validity of an ultra-wideband local positioning system to assess specific movements in handball

Abstract

The aim of this study was to examine the concurrent validity of the Kinexon local positioning
system (LPS) in comparison with the Vicon motion capture system used as the reference. Five recreationally
active men performed ten repetitions of linear sprints, medio-lateral side-to-side and handball-specific movements
both in the centre and on the side of an indoor field. Validity was assessed for peak speed, peak acceleration
and peak deceleration using standardised biases, Pearson coefficient of correlation (r), and standardised typical
error of the estimate. With the exception of peak decelerations during specific movements in the centre and
peak acceleration and deceleration during linear sprints on the side of the field, the standardised typical error
of the estimate (TEE) values were all small to moderate (0.06–0.48), standardised bias ranged between 0.01
and 2.85 and Pearson coefficient values were all > 0.90 for all variables in all conditions. Peak acceleration
and deceleration during linear sprints on the side of the field showed the largest TEEs and the greatest differences
between the two systems. The ultra-wideband based (UWB) local positioning system had acceptable validity
compared with Vicon to assess players’ movements in handball with the exception of high accelerations and
decelerations during linear sprints on the side of the field.

Full text

Biology of Sport, Vol. 37 No4, 2020 351
Validity of the local positioning system Kinexon
INTRODUCTION
In elite team sports, daily monitoring of aplayer’s physical load is
needed to optimize the periodization of training, prevent injuries and
organize the player’s return to play[1,2]. Over the past two decades,
the use of Global Positioning Systems (GPS) has grown exponen-
tially to measure players’ external load using mainly locomotion-re-
lated variables (e.g. distance travelled, speed and acceleration of
locomotion)[2–5]. However, while GPS systems offer the great ad-
vantage of being portable and non-invasive, they remain unusable
in indoor conditions.
For indoor sports, many other technological solutions are now
available to monitor player ’s movements using for example local
positioning systems (LPS). Many of them (e.g., radio frequency iden-
tication, wireless local area network or Bluetooth) are unfortunate-
ly not suitable for precise position measurements due to alack of
accuracy, instability or interference issues[6]. Recently, new tools
based on ultra-wideband technology (UWB) have been developed
specically to track players’ position indoor. However, the validity of
the different tools using this technology is still questionable. Two
groups of researchers examined, in indoor conditions, the concurrent
Validity of an ultra-wideband local positioning system
to assess specic movements in handball
AUTHORS: Antoine Fleureau1,2, Mathieu Lacome1,2, Martin Buchheit1,2, Antoine Couturier2,
Giuseppe Rabita2
1 Performance Department, Paris Saint Germain, Saint-Germain-En-Laye, France
2 Research Department, Laboratory Sport, Expertise and Performance (EA 7370), French Institute of Sport (INSEP),
Paris, France
ABSTRACT: The aim of this study was to examine the concurrent validity of the Kinexon local positioning
system (LPS) in comparison with the Vicon motion capture system used as the reference. Five recreationally
active men performed ten repetitions of linear sprints, medio-lateral side-to-side and handball-specic movements
both in the centre and on the side of an indoor eld. Validity was assessed for peak speed, peak acceleration
and peak deceleration using standardised biases, Pearson coefcient of correlation (r), and standardised typical
error of the estimate. With the exception of peak decelerations during specic movements in the centre and
peak acceleration and deceleration during linear sprints on the side of the eld, the standardised typical error
of the estimate (TEE) values were all small to moderate (0.06–0.48), standardised bias ranged between 0.01
and 2.85 and Pearson coefcient values were all>0.90 for all variables in all conditions. Peak acceleration
and deceleration during linear sprints on the side of the eld showed the largest TEEs and the greatest differences
between the two systems. The ultra-wideband based (UWB) local positioning system had acceptable validity
compared with Vicon to assess players’ movements in handball with the exception of high accelerations and
decelerations during linear sprints on the side of the eld.
CITATION: Fleureau A, Lacome M, Buchheit M et al. Validity of an ultra-wideband local positioning system
to assess specic movements in handball. Biol Sport. 2020;37(4):
351
–357.
Received: 2020-04-01; Reviewed: 2020-05-11; Re-submitted: 2020-06-09; Accepted: 2020-06-12; Published: 2020-07-05.
validity of the ClearSky LPS based on UWB technology (using 10 or
20Hz sampling frequency) using amotion capture device (100Hz
motion capture system, Vicon or Qualisys) as the reference criteri-
on[7, 8]. The system was assessed during linear movements at
different speeds and successive 45° changes of direction. The main
results of the Serpiello et al. study[7] were that the LPS had accept-
able validity for evaluating locomotor patterns of indoor sports com-
pared to motion capture systems. Differences vs. the Vicon were in
the range of 0.2–12.0%, with atypical error of the estimate (TEE)
between 1.2 and 9.3% for distance, mean/peak speed, and mean/
peak acceleration. Luteberget et al.[8] showed LPS measurements
to be more representative of the player’s position and displacements
in the centre of the playing eld than on the sides. There were sub-
stantial differences in comparison to the criterion for both distances
travelled and average speed, which were greater on the side of the
court (15–30%) than in the centre (1–3%). However, it was con-
cluded that the ClearSky system could be considered as valid from
those later studies. Another LPS system, Kinexon (Kinexon GMBH,
Munich, Germany) may be preferred for various reasons including
Original Paper
DOI: https://doi.org/10.5114/biolsport.2020.96850
Key words:
Ultra-wideband
Concurrent validity
Kinexon
Vicon
Indoor sport
Corresponding author:
Antoine Fleureau
Performance Department, Paris
Saint Germain, Saint-Germain-
En-Laye, France
E-mail: antoineeureau@live.fr

352
Antoine Fleureau et al.
Therefore, the purpose of this study was to examine the concurrent
validity of the UWB Kinexon positioning system during arange of
handball-specic movements in comparison to the Vicon motion
capture system used as the reference. The effect of the eld location
(centre vs. side) was also examined.
MATERIALS AND METHODS
Participants and experimental overview
Five recreationally active male subjects (age: 29.2±4.1 years,
height: 1.76±0.11m, and body mass: 77.0±8.0kg) volunteered
to participate in this study. The participants were informed of the
purposes, procedures, and potential risks of the study and provided
its supposed better ability to measure acceleration and decelerations
and the reduced size of the chips worn by the athletes in comparison
with the ClearSky system. The validity of the Kinexon LPS UWB-
based system, studied by Hoppe et al.[9], was in fact shown to be
better than that of two other GPS systems, which were previously
considered as ‘valid’[5,10–13]. The main result of this study was
aTEE for the distance covered of 1.0–6.0% for the LPS system
versus 1.6–8.0% and 3.0–12.9% for the two GPS systems. Unfor-
tunately, in this latter study, locomotor patterns (including maximal
velocity, acceleration, or deceleration) were only examined using
overall distance covered and timing gates. Furthermore, they did not
test the effect of the eld location (centre vs. side) on this validity.
FIG. 1. A: Position of the Vicon camera on conguration for sprints (̶ ̶ ̶); B: Position of the Vicon camera on conguration for lateral
and specic movements (̶̶ ·· ̶); C: Schematic position of the Kinexon antennas and position of testing zones on the eld; D: Position
of Kinexon antennas; E: Position of the Vicon reective marker on the Kinexon tag

Biology of Sport, Vol. 37 No4, 2020
353
Validity of the local positioning system Kinexon
consent of their approval to participate. All the procedures were
conducted in accordance with the Declaration of Helsinki.
Experimental protocol
Arst session was carried out in the centre of an indoor handball
playing eld during which the participants performed three types of
movements, as described below. Two days after, asecond session
was carried out with the same protocol located on the side of the
eld.
Locomotion activities
Participants performed three different activities repeated ten times
in the following order:
– S: Maximal acceleration over alinear course of 25mwith astand-
ing start. After 20m of running, participants had to decelerate
over 5mand stand still (Figure 1.A).
– L: Lateral movements in the form of medio-lateral side-to-side
movement over 3m(Figure 1.B)
– H: Handball-specic movement in the form of engagement-disen-
gagement in an interval of 2m, followed by areengagement out
this interval nished by aone-legged jump (Figure 1.B)
Materials
The validity of the Kinexon (Kinexon GMBH, Munich, Germany) was
examined while comparing the raw data collected with those obtained
using the Vicon. For each test session, two congurations of the Vicon
were used, one for lateral and specic movements (Figure 1.A) and
one for the sprints (Figure 1.B). In all trials, participants wore simul-
taneously both areceiver tag connected to the Kinexon antennas and
apassive reective marker to be detected by the motion Vicon cap-
ture system.
Kinexon Ultrawide band system
The system used in this study consisted of 14antennas positioned
around the handball playing eld (i.e., Coubertin Indoor Stadium,
Paris) at three different heights, as shown in Figure 1.C&D. The tag
was placed in the centre of the upper back using the manufacturer
harness. The data were collected at 20Hz and processed via the
specic Kinexon Software. The signals were transmitted to the anten-
nas using UWB technology in afrequency range of 4.25–7.25GHz.
The eld position of the tag was calculated by aproprietary algorithm
based on acombination of different methods such as Time Difference
of Arrival, Two-Way Ranging and Angle of Arrival[14].
Vicon motion capture system
A12-camera Vicon motion analysis system (Vicon Nexus T40, Vicon
Motion Systems, Oxford Metrics, UK) was implemented in the two
congurations shown in Figure 1.A&B. Data were collected at 250Hz.
Only one 14mm reective marker (B&L Engineering, Santa Ana,
USA) was placed on the Kinexon tag as shown in Figure 1.E.
FIG. 2. Synchronized position data of the two systems (Kinexon and Vicon) both in the centre and on the side of the court, for each
type of movement.

354
Antoine Fleureau et al.
of position data. Peaks in speed, acceleration and deceleration were
calculated from the raw data and utilised for the analysis. They were
respectively computed as the maximum mean speed, acceleration
and deceleration over a500ms window[10,15,16].
Statistical analysis
The Hopkins spreadsheet[17] was used to compare the agreement
between the two systems by linear regression. We compared the
Kinexon system (practical) with the Vicon (criterion) while computing
the mean and standardised bias, the Pearson correlation coefcient
and the typical error of the estimate (TEE) expressed rst as the
absolute value, then normalized and as acoefcient of variation (CV),
provided together with a 90% condence interval. The following
criteria were adopted to interpret the magnitude of the correla-
tions:≤ 0.01, trivial; >0.1, small; > 0.3, moderate;>0.5,
large;>0.7, very large; and>0.9, almost perfect. Half the thresh-
old of the modied Cohen scale was used to interpret the standardised
TEE:> 0.01 (trivial)> 0.1 (small),> 0.3 (moderate),> 0.6
(large),>1.0 (very large), and>2.0 (extremely large)[17]. Regard-
ing standardised bias interpretation, threshold values were the
modied Cohen scale: 0.01 (trivial);>0.2 (small);>0.6 (moder-
ate);>1.2 (large);>2.0 (very large);>4.0 (extremely large)[17].
The data obtained from the three-dimensional marker position
were used for further analysis. The loss of the marker signal was
never longer than 25successive images (i.e., 0.1s) and automati-
cally extrapolated with the Vicon 3D software using the marker po-
sition immediately before and after the loss.
The average Vicon calibration errors (Image and World Error, re-
spectively) for the two test sessions were 0.09 and 0.17mm for
data collected in the centre of the eld, and 0.08 and 0.16mm for
those collected on the side of the eld.
Data processing
Figure 2illustrates, for one trial, the position signal obtained from
both systems. The original datasets from Kinexon were oversampled
from 20 to 250Hz for subsequent ne synchronization with Vicon
data. Signals from both systems were then ltered using a3rd order
zero phase shifting low pass Butterworth lter with a10Hz cut-off.
Each pair of Kinexon and Vicon data sets for each movement repeti-
tion was manually synchronized to determine acommon start and
end. The distance travelled was then calculated as the sum of the
instantaneous positions in the horizontal plane (x, y). Velocity and
acceleration data were obtained by successive derivation and low
pass ltering (10Hz, 3rd order zero phase shifting Butterworth lter)
TABLE 1. Comparison of peak speed, peak acceleration, and peak deceleration between Kinexon and Vicon during three different
locomotion activities performed in the centre of an indoor court.
Movement
Mean
±SD
Vicon
Mean
±SD
Kinexon
Mean Bias
±CI
Standard-
ised Bias
±CI
TEE
±CI
Standard-
ised TEE
±CI
TEE as CV
(%) ± CI
Pearson
correlation
(r) ± CI
Centre of the eld
Peak Speed
(m·s-1)
Sprint
Lateral
Specic
7.0
±0.4
2.1
±0.1
2.6
±0.2
7.2
±0.4
2.0
±0.1
2.7
±0.2
0.15
±0.01
-0.09
±0.02
0.12
±0.02
0.38
±0.03
-1.14
±0.21
0.63
±0.10
0.02
±0.01
0.03
±0.01
0.05
±0.03
0.06
±0.02
0.44
±0.18
0.25
±0.11
0.3
±0.1
1.6
±0.4
1.9
±0.6
1.00
±0.00
0.92
±0.06
0.97
±0.03
Peak Acceleration
(m·s-2)
Sprint
Lateral
Specic
3.5
±0.3
3.7
±0.1
3.7
±0.5
3.6
±0.3
3.6
±0.2
4.0
±0.4
0.19
±0.02
-0.14
±0.03
0.27
±0.04
0.60
±0.05
-1.10
±0.27
0.60
±0.09
0.05
±0.01
0.06
±0.01
0.10
±0.03
0.15
±0.05
0.48
±0.18
0.23
±0.10
1.4
±0.3
1.5
±0.4
2.8
±0.9
0.99
±0.01
0.90
±0.06
0.97
±0.02
Peak Deceleration
(m·s-2)
Sprint
Lateral
Specic
4.1
±0.6
3.9
±0.1
2.5
±0.2
4.4
±0.7
3.7
±0.2
2.5
±0.1
0.22
±0.04
-0.14
±0.02
0.00
±0.05
0.39
±0.07
-0.99
±0.17
0.01
±0.34
0.08
±0.02
0.06
±0.01
0.12
±0.04
0.14
±0.05
0.44
±0.16
1.29
±1.26
2.0
±0.5
1.5
±0.4
5.0
±1.6
0.99
±0.01
0.92
±0.05
0.61
±0.26
Note: SD: Standard deviation, CI: 90% Condence Interval, TEE: Typical Error of the Estimate, CV: Coefcient of Variation

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Validity of the local positioning system Kinexon
RESULTS
Table 1presents mean and standard deviation of peak speed, peak
acceleration and peak deceleration in the centre of the playing eld
during sprints, lateral and handball-specic movements, as well as
the respective bias, TEE and correlations between values obtained
from practical (Kinexon) and criterion (Vicon) systems. Standardised
biases were small to moderate for all variable for all movements and
trivial for deceleration during the specic movement. The standardised
TEEs were small to moderate for all variables during all movements,
except for peak deceleration during specic movement, which was
only very large. The magnitude of the correlations was almost perfect
for all analyses except for peak deceleration during specic move-
ments, which was only large.
Table 2presents the results from the data recorded on the side
of the eld. Standardised biases were also small to moderate for all
variables (peaks in speed, acceleration, and deceleration) during
lateral movement. During specic movements biases were small to
moderate only for acceleration and deceleration peaks and large for
peak speed. During the sprint, standardised biases were extremely
large for peak deceleration and moderate for peak speed and ac-
celeration. Standardised TEEs were small to moderate for all variables
for lateral and specic movements and for peak speed during sprints.
They were very large for peak acceleration and deceleration during
sprints. In the same way, the magnitude of the correlations was almost
perfect for all variables during lateral and specic movements and
for peak speed in sprints. The correlation was only small for accel-
eration and deceleration during sprint.
DISCUSSION
The purpose of this study was to assess the concurrent validity of
the Kinexon LPS UWB based system in comparison to the Vicon
motion capture system during sprints, lateral movements, and hand-
ball-specic drills. The present results suggest that the LPS Kinexon
validity may be considered as acceptable to assess indoor locomotor
movements. The magnitude of the correlations between the two
systems was almost perfect (>0.90) for all variables during all types
of movements, except in three particular cases: i) peak decelerations
during specic movements in the centre of the eld, ii) peak accel-
erations during linear sprints on the side of the eld and iii)peak
decelerations during linear sprints on the side of the eld.
As shown in Table 1, in the centre of the playing eld, the stan-
dardised TEEs of peak speed and peak acceleration for sprints, lat-
eral and specic drills were trivial to moderate (CV 0.3±0.1 to
2.8±0.9%). These results were similar to or even better than both
those reported by Serpiello et al. (2017) for LPS (CV<3.5%) and
Scott et al. (2016) for GPS (peak speed CV: 5.4 to 20.6%). Regarding
TABLE 2. Comparison of peak speed, peak acceleration, and peak deceleration between Kinexon and Vicon during three different
locomotion activities performed on the side of an indoor court.
Movement
Mean
±SD
Vicon
Mean
±SD
Kinexon
Mean Bias
±CI
Standard-
ised Bias
±CI
TEE
±CI
Standard-
ised TEE
±CI
TEE as CV
(%) ± CI
Pearson
correlation
(r) ± CI
Side of the eld
Peak Speed
(m·s-1)
Sprint
Lateral
Specic
7.1
±0.2
1.9
±0.3
2.4
±0.1
7.3
±0.2
1.9
±0.3
2.6
±0.1
0.17
±0.02
-0.07
±0.01
0.23
±0.02
0.84
±0.08
-0.24
±0.05
2.85
±0.24
0.05
±0.01
0.04
±0.01
0.04
±0.01
0.26
±0.09
0.16
±0.06
0.47
±0.25
0.7
±0.2
2.1
±0.6
1.5
±0.5
0.97
±0.02
0.99
±0.01
0.91
±0.09
Peak Acceleration
(m·s-2)
Sprint
Lateral
Specic
4.4
±0.4
3.2
±0.7
3.5
±0.2
4.0
±0.3
2.8
±0.9
3.7
±0.3
-0.38
±0.15
-0.38
±0.06
0.25
±0.05
-0.91
±0.35
-0.51
±0.09
1.10
±0.23
0.39
±0.10
0.08
±0.02
0.08
±0.02
2.56
±21.15
0.11
±0.04
0.34
±0.15
9.4
±2.6
2.7
±0.7
2.3
±0.7
0.36
±0.30
0.99
±0.00
0.95
±0.04
Peak Deceleration
(m·s-2)
Sprint
Lateral
Specic
3.2
±0.2
3.4
±0.6
2.6
±0.5
4.5
±0.3
3.2
±0.6
2.4
±0.5
1.24
±0.11
-0.27
±0.03
-0.16
±0.05
6.73
±0.61
-0.45
±0.04
-0.33
±0.11
0.18
±0.05
0.06
±0.02
0.14
±0.04
3.96
±3.81
0.10
±0.04
0.29
±0.13
5.7
±1.6
1.9
±0.5
5.5
±1.7
0.25
±0.33
0.99
±0.00
0.96
±0.03
Note: SD: Standard deviation, CI: 90% Condence Interval, TEE: Typical Error of the Estimate, CV: Coefcient of Variation

356
Antoine Fleureau et al.
suring peak acceleration and deceleration in sprints (CV>5%)[18,20].
In comparison to the ClearSky system examined by Luteberget et
al.[8], the Kinexon system is likely more accurate to measure peak
speed anywhere on the eld (r: 0.91–1.00 versus 0.37–0.98 and
standardised TEE: 0.06–0.47 versus 0.19–2.54). Everywhere on the
eld, Kinexon measurement of peak speed and acceleration is likely
as effective as the LPS system examined by Serpiello et al.[7], and
better for measuring peak decelerations. Moreover, our results dem-
onstrated that changes of direction, including handball-specic move-
ments, were correctly detected and measured by the Kinexon system
for all variables in all conditions in comparison to Vicon (CV: 0.3–2.8%),
with the exception of peak deceleration in the centre of the eld (CV:
5.0%). These results were better than those observed by Serpiello et
al.[7] for LPS (CV: 2.1–5.3%) and by Vickery et al. (2014) for GPS
(CV: 20.0%) during successive 45° and 90° change of direction and
random movements including change of direction.
Limitations
The results of the present study reect the specic conguration of
the UWB-based LPS Kinexon in our indoor stadium (i.e., Coubertin
Indoor Stadium, Paris). In fact, the effect of the position of the anten-
nas in the stadium is important, particularly when distances between
the eld of play and the walls are small. It seems that when the
heterogeneity in the distance between the receiver tag and some of
the antennas is too great (i.e., very close to the tag for some anten-
nas, very far for others), the quality of peak acceleration and decel-
eration measurement is impaired.
This study did not investigate the validity of the Kinexon system
near the penalty spot even though some players spend more time
near this position than anywhere else on the playing eld. However,
for medio-lateral side-to-side and specic movement, our results did
not show asignicant difference between the centre and the side of
the playing eld. In consequence, it could be assumed that the valid-
ity would have been similar in this specic spot in comparison to the
one calculated for the two tested areas.
Practical applications
This study demonstrated that 20Hz LPS Kinexon units can measure
the fundamental handball movement demands in terms of peak
speed, peak acceleration and peak deceleration with an acceptable
level of error, especially in the centre of the eld. Practitioners may
however need to treat some of the data with more care, such as peak
accelerations and decelerations of wing players, which were shown
to have alower level of precision.
CONCLUSIONS
To conclude, the UWB-based Kinexon system has an acceptable
validity compared with the Vicon to assess handball-specic locomo-
tor patterns. Care should however be taken when monitoring ac-
celerations and decelerations on the side of the playing eld during
linear sprints (e.g., wingers’ counterstrike).
peak deceleration in both linear sprints and lateral movements, stan-
dardised TEEs were also small to moderate (1.5 ± 0.4 and
2.0±0.5%). Those results were better than those obtained by Ser-
piello et al. (2017) (CV>10%). For peak deceleration during spe-
cic movements, however, the standardised TEE was very large
(5.0±1.6%). There were also almost perfect correlations of the data
between the two systems (r>0.9) during both multidirectional (spe-
cic movements) and unidirectional movements (sprints and lateral
movements), except for peak decelerations during specic movements
(r: 0.61±0.26). In comparison with the results obtained in the
various GPS or LPS validity studies[5,7,9], the Kinexon system
seems to be more effective for measuring peak speed, accelerations
and decelerations during handball-specic movements. It also seems
more effective at measuring high acceleration and deceleration peaks
during sprints performed in the centre of the playing eld (CV<5%)
than the other positioning system already tested (CV>5%)[7,18].
As shown in Table 2, on the side of the playing eld, peak speed
standardised TEEs were small to moderate regardless of the type of
movement (0.7±0.2 to 2.1±0.6%); in contrast however, stan-
dardised TEEs for peak accelerations and decelerations were small
to moderate for lateral and handball-specic movements (1.9±0.5
to 5.5 ±0.7%). During the sprint, extremely large standardised
TEEs could be found for peak accelerations and decelerations
(5.4±2.6 to 9.4±2.6%). The large TEE reported and the mea-
surements errors of the Kinexon system on the side of the playing
eld mirrored the poor correlations observed in terms of peak ac-
celerations and decelerations during linear sprint (r: 0.36±0.30
and 0.25 ±0.33). This measurement error may be due to the
method used to obtain the acceleration signal, which was derived
twice from the position signal. However, deriving the signal likely
multiplies the possible measurement errors. For this reason, even if
speed measurement was very precise (r: 0.97±0.02, standardised
TEE: 0.26± 0.09), it still contained some errors that were likely
increased by the derivation process. This problem did not occur in
the centre of the playing eld since the agreement was almost perfect
for sprinting speed (r: 1.00±0.00, standardised TEE: 0.06±0.02);
the measurement error was too small to affect the correlation after
derivation. Moreover, the standardised bias was greater on the side
of the eld (0.84±0.08) than in the centre of the eld (0.38±0.03).
These results were similar to or even better than those presented by
Luteberget et al.[8] when examining the ClearSky system on the
side of the eld. The current results demonstrated that when the
distance between the receiver tag and the antennas is not homoge-
neous, the accuracy of acceleration and deceleration measurements
decreases. GPS validity studies also showed an overall inability to
correctly measure accelerations and decelerations on the side of the
playing eld in a stadium covered with aroof, but this was more
likely here due to alimited number of connected satellites[19].
The Kinexon system seems to be more accurate than GPS, which
is generally less reliable for measuring multidirectional movements
(CV>10%) than unidirectional movement (CV<5%), and for mea-

Biology of Sport, Vol. 37 No4, 2020
357
Validity of the local positioning system Kinexon
1. Buchheit M, Allen A, Poon TK, Modonutti
M, Gregson W, Di Salvo V. Integrating
different tracking systems in football:
multiple camera semi-automatic system,
local position measurement and GPS
technologies. J Sports Sci.
2014;32(20):1844-57.
2. Carling C. Interpreting physical
performance in professional soccer
match-play: should we be more
pragmatic in our approach? Sports Med.
2013;43(8):655-63.
3. Larsson P. Global Positioning System and
Sport-Specic Testing. Sports Med.
2003;33(15):1093-101.
4. Schutz Y, Chambaz A. Could a
satellite-based navigation system (GPS)
be used to assess the physical activity of
individuals on earth? Eur J Clin Nutr.
1997;51(5):338-9.
5. Scott MTU, Scott TJ, Kelly VG. The
Validity and Reliability of Global
Positioning Systems in Team Sport: A
Brief Review. J Strength Cond Res.
2016;30(5):1470-90.
6. Alari A, Al-Salman A, Alsaleh M,
Alnafessah A, Al-Hadhrami S, Al-Ammar
MA, et al. Ultra Wideband Indoor
Positioning Technologies: Analysis and
Recent Advances. Sensors (Basel).
2016;16(5).
7. Serpiello FR, Hopkins WG, Barnes S,
Tavrou J, Duthie GM, Aughey RJ, et al.
Validity of an ultra-wideband local
positioning system to measure
locomotion in indoor sports. J Sports Sci.
2017:1-7.
8. Luteberget LS, Spencer M, Gilgien M.
Validity of the Catapult ClearSky T6 Local
Positioning System for Team Sports
Specic Drills, in Indoor Conditions. Front
Physiol. 2018;9:115.
9. Hoppe MW, Baumgart C, Polglaze T,
Freiwald J. Validity and reliability of GPS
and LPS for measuring distances covered
and sprint mechanical properties in team
sports. PLoS One.
2018;13(2):e0192708.
10. Aughey RJ. Application of GPS
Technologies to eld Sports. Int J Sports
Physiol Perform. 2011.
11. Cloe Cummins RO, Helen O’Connor,
Cameron West. Global Positioning
Systems (GPS) and Microtechnology
Sensors in Team Sports: A Systematic
Review. Sports Med. 2013.
12. Varley MC, Fairweather IH, Aughey RJ.
Validity and reliability of GPS for
measuring instantaneous velocity during
acceleration, deceleration, and constant
motion. J Sports Sci. 2012;30(2):121-7.
13. Ryu Nagahara AB, Enrico Rejc, Masaaki
Koido, Takeshi Shimizu, Pierre Samozino,
and Jean-Benoit Morin. Concurrent
Validity of GPS for Deriving Mechanical
Properties of Sprint Acceleration. Int J
Sports Physiol Perform. 2016.
14. Kinexon. Real-time athlete tracking—
Precise. Simple. Smart. In: Munich,
editor. Kinexon Precision Technologies
2016.
15. Buchheit M, Simpson BM. Player-
Tracking Technology: Half-Full or
Half-Empty Glass? Int J Sports Physiol
Perform. 2017;12(Suppl 2):S235-S41.
16. Malone JJ, Lovell R, Varley MC, Coutts
AJ. Unpacking the Black Box:
Applications and Considerations for Using
GPS Devices in Sport. Int J Sports Physiol
Perform. 2017;12(Suppl 2):S218-S26.
17. Hopkins WG, Marshall SW, Batterham
AM, Hanin J. Progressive Statistics for
Studies in Sports Medicine and Exercise
Science. Med Sci Sports Exerc.
2009;41(1):3-12.
18. Vickery WM, Dascombe BJ, Baker JD,
Higham DG, Spratford WA, Dufeld R.
Accuracy and Reliability of GPS Devices
for Measurement of Sports-Specic
Movement Patterns Related to Cricket,
Tennis, and Field-Based Team Sports. J
Strength Cond Res. 2014;28(6):1697-
705.
19. Williams M, Morgan S. Horizontal
positioning error derived from stationary
GPS units: A function of time and
proximity to building infrastructure. Int J
Perform Anal Sport.. 2017;9(2):275-80.
20. Waldron M, Worsfold P, Twist C, Lamb K.
Concurrent validity and test-retest
reliability of a global positioning system
(GPS) and timing gates to assess sprint
performance variables. J Sports Sci.
2011;29(15):1613-9.
REFERENCES