Citation: Martinez-Torremocha, G.;
Sanchez-Sanchez, J.; Alonso-Callejo,
A.; Martin-Sanchez, M.L.; Serrano, C.;
Gallardo, L.; Garcia-Unanue, J.;
Felipe, J.L. Physical Demands in the
Worst-Case Scenarios of Elite Futsal
Referees Using a Local Positioning
System. Sensors 2023, 23, 8662.
https://doi.org/10.3390/s23218662
Academic Editors: John Komar and
Ludovic Seifert
Received: 3 October 2023
Revised: 19 October 2023
Accepted: 20 October 2023
Published: 24 October 2023
Copyright:
© 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed
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conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
sensors
Article
Physical Demands in the Worst-Case Scenarios of Elite Futsal
Referees Using a Local Positioning System
Gemma Martinez-Torremocha 1
, Javier Sanchez-Sanchez 2,*
, Antonio Alonso-Callejo 1,
Maria Luisa Martin-Sanchez 2, Carlos Serrano 2
, Leonor Gallardo 1
, Jorge Garcia-Unanue 1
and Jose Luis Felipe 1
1
IGOID Research Group, Physical Activity and Sport Sciences Department, University of Castilla-La Mancha,
45071 Toledo, Spain; gemma.martinez@uclm.es (G.M.-T.); antonio.alonso@uclm.es (A.A.-C.);
leonor.gallardo@uclm.es (L.G.); jorge.garciaunanue@uclm.es (J.G.-U.); joseluis.felipe@uclm.es (J.L.F.)
2
School of Sport Sciences, Universidad Europea de Madrid, 28670 Villaviciosa de Odón, Spain;
marialuisa.martindesanpablo@universidadeuropea.es (M.L.M.-S.);
carlos.serrano2@universidadeuropea.es (C.S.)
*
Correspondence: javier.sanchez2@universidadeuropea.es
Abstract: The aim of this study is to analyze the worst-case scenarios of professional futsal referees
during the ﬁrst and second half of ofﬁcial matches in the Spanish Futsal Cup using a Local Posi-
tioning System (LPS) for monitoring their movement patterns. Eight professional futsal referees
(40 ± 3.43 years; 1.80 ± 0.03 m; 72.84 ± 4.01 kg) participated in the study. The external load (total
distance, high-speed running distance and efforts, sprint distance and efforts, and accelerations
and decelerations distances) of the referees was monitored and collected using an LPS. The results
revealed signiﬁcant differences in the worst-case scenarios of the futsal referees during the match
according to the time window analyzed (p < 0.05). The longest time windows (120 s, 180 s, and
300 s) showed lower relative total distances in the worst-case scenarios (p < 0.05). The high-speed
running distances were signiﬁcatively higher in the ﬁrst half for the 120 s (+2.65 m·min−1; ES: 1.25),
180 s (+1.55 m·min−1; ES: 1.28), and 300 s (+0.95 m·min−1; ES: 1.14) time windows (p < 0.05). No
differences were found between the ﬁrst and second half for the high-intensity deceleration distance
(p > 0.05). These results will serve to prepare the referees in the best conditions for the competition
and adapt the training plans to the worst-case scenarios.
Keywords: team sport; competition; endurance; game analysis; physical performance
1. Introduction
Team sports have a referee who must regulate the rules so that matches can be carried
out correctly. Referees have an essential task since they must pay attention and perform
precise control over the game’s every single moment [1]. For that reason, the physical
demands of referees have been studied for some years thanks to Global Positioning Systems
(GPS) which are easy to transport and use [2].
Throughout the years, the physical demands in football referees have been stud-
ied [1,3,4]. However, football has different characteristics than futsal [5]. Futsal is a
high-intensity, intermittent team sport which is played indoors and involves short actions
of high intensity with a short recovery time between efforts such as changes of direction,
sprints, accelerations (Acc), and decelerations (Dec) [6]. It is a team sport with two times of
20 min each per game, at a standstill time. So, every time the ball comes out of the ﬁeld,
time stops until the game resumes [7]. Moreover, in futsal there are two main referees on
the court, who have different functions and must have extraordinary positions on the futsal
ﬁeld to observe the possible infractions [5].
Football referees cover between 10 km and 12 km per game and about 15% of the
total distance at a high speed (>18 km·h−1) [3,4]. Furthermore, they reach a maximum
Sensors 2023, 23, 8662. https://doi.org/10.3390/s23218662
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speed of 28.76 km·h−1 and cover 212.98 m at sprint speed [1]. Weston et al. [8] showed
that the distance covered at a high intensity and the total distance travelled in the ﬁrst
15 min of the ﬁrst half of the match are higher than the distance covered in the ﬁrst 15 min
of the second half. This indicates that referees are subjected to high loads, which may cause
injuries if they do not train at optimal levels that are equivalent to the physical demands
that they have in ofﬁcial matches [9]. Nevertheless, in reference to futsal, Rebelo et al. [5]
demonstrated that referees perform intermittent endurance, of moderate–high intensity,
during a match, with several periods of running and sprints, while also performing long
recovery periods of low intensity.
There are several studies conducted on the proﬁles of futsal players [7,10], but there
is very little research about futsal referees [5,11,12]. It has been demonstrated that futsal
players from the 1st division of the Portuguese, Spanish, and Russian leagues perform
high-intensity efforts every 43 s, medium-intensity efforts every 37 s, and low-intensity
efforts every 14 s during futsal playoffs’ matches [13]. In addition, a recent study published
that futsal players perform around 70 Acc and Dec at a high intensity and, approximately,
170 changes of direction during ofﬁcial matches [14]. Also, players cover 3749 m in a
match, of which 134.9 m are carried out at a high speed (>18 km·h−1) [10]. Additionally,
Serrano et al. [12] showed that futsal referees cover 5719 m of long distance at slow and
moderate speeds, with a reduction in the second half of the games in the sprints’ distance
and high-speed running (HSR). Ahmed et al. [11] demonstrated that futsal referees have
150.9 beats per minute (bpm) and cover 161.1 m and 114.4 m at a high intensity in the ﬁrst
and second half, respectively.
For the analysis of the physical demands of the matches of indoor and outdoor
sports, different methods have been used, but GPS is the most common for providing
measurements with validity and accuracy [2]. Additionally, the physical demands have
been analyzed in different ways, as follows: with video for futsal referees [5,11]; via GPS for
ofﬁcial football referees [1,3,4]; and through a Local Positioning System (LPS) with Ultra-
Wide Band (UWB) technology for futsal referees [12] and players [10,15,16]. Therefore,
new methods have been used to detect worst-case scenarios (WCSs). This is the case for
professional football players, as using averages may underestimate peak requirements [17].
The WCS is the most intense time of a game or training [17] (e.g., 30 s). WCSs have
recently started to be included in different studies [15,17] to examine the peak physical
demands at different playing times during matches [18] in several team sports such as
rugby [19], football [17], and futsal [15]. As a result, it would be interesting to use it for
referees. However, although there is some information about the physical demands of
professional futsal referees [11,12], much more evidence is needed to accurately establish
their activity. Furthermore, there is no prior information on WCSs of professional futsal
referees collected using tracking technology devices during ofﬁcial matches.
Therefore, the aim of this study is to analyze the WCSs of professional futsal referees
in the ﬁrst and second half of ofﬁcial matches in the Spanish Futsal Cup using a LPS for
monitoring their movement patterns. The results of this study will facilitate the design of
training plans according to the physical demands of a match.
2. Materials and Methods
2.1. Experimental Approach to the Problem
The data from seven ofﬁcial Spanish Futsal Cup 2020 matches (ﬁrst division teams of
the National Spanish Futsal League (LNFS)) were gathered using an UWB technology sys-
tem. This allowed for the quantiﬁcation of the absolute and relative external training loads,
which were then divided into the ﬁrst and second halves of the games. The competition
was organized over 4 days divided into four quarterﬁnals’ games, two semi-ﬁnals’ games,
and a ﬁnal game.
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2.2. Participants
Eight professional Spanish futsal referees (age 40 ± 3.43 years; height 1.80 ± 0.03 m;
weight 72.84 ± 4.01 kg), with similar characteristics and the same number of training
sessions per week, were monitored during this study. They were studied over seven
games, which were spread across the quarterﬁnals, semiﬁnals, and championship game
over four days. The referees were selected by the National Committee of Referees (CTA) for
participating in the Spanish Futsal Cup 2020. All of them had at least 6 years of experience
in the ﬁrst division of the National Spanish Futsal League, and they must pass different
physical tests each year. Informed written consent was obtained from each participant
after being informed of the study’s requirements. The project was approved and followed
the guidelines established by the local institution—the Bioethics Committee for Clinical
Research of the Virgen de la Salud Hospital in Toledo (Ref.: 2551;17/02/2021).
2.3. Equipment
The referees’ movement patterns throughout each game were tracked using WIMU
PROTM LPS (RealTrack Systems SL, Almería, Spain) with an UWB technology. The reference
technology and the WIMU PROTM inertial device (which the referees transported) are the
two components that make up this technology. The WIMU PROTM has shown an accuracy
(bias: 0.57–5.85%), test–retest reliability (%TEM: 1.19), and inter-unit reliability (bias: 0.18)
in Bastida Castillo et al. [20], as well as a large ICC for the x-coordinate (0.65) and a
very large ICC for the y-coordinate (0.88), with a good 2%TEM [21]. For data recording,
storage, and uploading, each device has a dedicated internal microprocessor with a fast USB
interface [21]. The devices are made up of a variety of sensors, including an UWB chipset
with a signal frequency of 18 Hz, a gyroscope, four accelerometers, a magnetometer, and a
Global Navigation Satellite System (GNSS) [22]. Six antennas make up the reference system,
each of which can transmit and receive radio-frequency signals. The radio-frequency signal
works almost exactly like the GPS system, with the antennas (mainly the master antenna)
calculating the position of the devices in their range as they receive the calculation [21].
In terms of calculating the distance traveled, speed, mean velocity, ACC, and DEC for
intermittent activities, LPS has proven to be accurate and reliable [23,24].
2.4. Procedures
The LPS was installed on the futsal pitch where the games were played, and the
individual WIMU PROTM devices (RealTrack Systems SL, Almería, Spain) were used to
register the physical parameters’ data of external load. The LPS was activated after the
warmup of the referees with an autocalibration of the antennas lasting 5 min [21]. The
placement of the six antennas (Figure 1) was set 5 m apart, forming a hexagon, except for
those positioned at the ﬁeld’s middle line, which were set 7 m from the perimeter. The
hexagonal shape of the antennas improved signal transmission and reception. The antennas
were then self-calibrated for ﬁve minutes, while the master antenna synchronized all the
antennas to a single clock after they had been installed. They were then switched on, one at
a time, with the master antenna being turned on last.
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Figure 1. Antenna distribution of the Local Positioning System and distance reference from the fut-
sal pitch. The arrows indicate the distance from the antennas to the court and the black lines indicate 
the communication between the antennas [16]. 
2.5. Data Processing 
The physical activity variables were considered in line with previous futsal studies 
[12,16]. A speciﬁc software (SPROTM v.990) was used to analyze each match’s referees’ 
performance data. The WCSs were assessed using the WIMU SPROTM software version 
990 (RealTrack Systems SL, Almería, Spain), with a rolling average method over each 
physical variable selected using ﬁve diﬀerent time windows (30, 60, 120, 180, and 300 s). 
This method had been used in previous futsal investigation [15] and other team sports’ 
[17,25,26]. The physical variables examined were the following: the total distance covered 
(TD); the HSR distance (distance covered above 15 km·h−1); the HSR eﬀorts (number of 
eﬀorts above 15 km·h−1); the sprint distance (distance covered above 18 km·h−1); the sprint 
eﬀorts (number of eﬀorts above 15 km·h−1); and the number (n) and distance (m) of high-
intensity ACC (>3 m·s−2) and DEC (<−3 m·s−2). All the speed variables and Acc and Dec 
thresholds selected were in line with previous referee futsal research [12]. 
2.6. Statistical Analysis 
The Shapiro–Wilk test was used to test for the normality of each variable and time 
window, resulting in a non-normal distribution (p < 0.05). The non-parametric Wilcoxon 
test for paired samples was run for each variable and time window. The same method was 
used for comparing values between half-times. The conﬁdence level was set to 95%, and 
the p-values < 0.05 were considered signiﬁcant. The standardized eﬀect size was calculated 
for each comparison and classiﬁed as negligible (Eﬀect Size (ES) < 0.2), small (ES between 
0.2 and 0.6), moderate (ES between 0.6 and 1.2), and large (ES > 1.2). The statistical analysis 
was carried out and the ﬁgures were created using the RStudio software (R version 4.2.2, 
RStudio 2022.12.0, © 2009–2022 Posit Software, PBC). 
3. Results 
The results revealed signiﬁcant diﬀerences in the WCS of futsal referees during the 
match according to the time window analyzed (p < 0.05). The longest time windows (120 
s, 180 s, and 300 s) showed lower relative distances in the WCS in comparison to the short-
est intervals (Table 1; p < 0.05). According to the diﬀerences between the ﬁrst and the sec-
ond half in the WCS (Table 2), the HSR distance was signiﬁcatively higher in the ﬁrst half 
for the 120 s (+2.65 m·min−1; ES: 0.38), 180 s (+1.55 m·min−1; ES: 0.29), and 300 s (+0.95 
m·min−1; ES: 0.27) time windows (p < 0.05). The WCS for the total distance was only 
Figure 1. Antenna distribution of the Local Positioning System and distance reference from the futsal
pitch. The arrows indicate the distance from the antennas to the court and the black lines indicate the
communication between the antennas [16].
2.5. Data Processing
The physical activity variables were considered in line with previous futsal stud-
ies [12,16]. A speciﬁc software (SPROTM v.990) was used to analyze each match’s referees’
performance data. The WCSs were assessed using the WIMU SPROTM software version 990
(RealTrack Systems SL, Almería, Spain), with a rolling average method over each physical
variable selected using ﬁve different time windows (30, 60, 120, 180, and 300 s). This method
had been used in previous futsal investigation [15] and other team sports’ [17,25,26]. The
physical variables examined were the following: the total distance covered (TD); the HSR
distance (distance covered above 15 km·h−1); the HSR efforts (number of efforts above
15 km·h−1); the sprint distance (distance covered above 18 km·h−1); the sprint efforts
(number of efforts above 15 km·h−1); and the number (n) and distance (m) of high-intensity
ACC (>3 m·s−2) and DEC (<−3 m·s−2). All the speed variables and Acc and Dec thresholds
selected were in line with previous referee futsal research [12].
2.6. Statistical Analysis
The Shapiro–Wilk test was used to test for the normality of each variable and time
window, resulting in a non-normal distribution (p < 0.05). The non-parametric Wilcoxon
test for paired samples was run for each variable and time window. The same method was
used for comparing values between half-times. The conﬁdence level was set to 95%, and
the p-values < 0.05 were considered signiﬁcant. The standardized effect size was calculated
for each comparison and classiﬁed as negligible (Effect Size (ES) < 0.2), small (ES between
0.2 and 0.6), moderate (ES between 0.6 and 1.2), and large (ES > 1.2). The statistical analysis
was carried out and the ﬁgures were created using the RStudio software (R version 4.2.2,
RStudio 2022.12.0, © 2009–2022 Posit Software, PBC).
3. Results
The results revealed signiﬁcant differences in the WCS of futsal referees during the
match according to the time window analyzed (p < 0.05). The longest time windows (120 s,
180 s, and 300 s) showed lower relative distances in the WCS in comparison to the shortest
intervals (Table 1; p < 0.05). According to the differences between the ﬁrst and the second
half in the WCS (Table 2), the HSR distance was signiﬁcatively higher in the ﬁrst half for the
120 s (+2.65 m·min−1; ES: 0.38), 180 s (+1.55 m·min−1; ES: 0.29), and 300 s (+0.95 m·min−1;
ES: 0.27) time windows (p < 0.05). The WCS for the total distance was only signiﬁcatively
Sensors 2023, 23, 8662
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lower in the second half for the 120 s time window (−7.29 m·min−1; ES: 1.44). Finally,
the high intensity Acc distance was also higher in the ﬁrst half, but only for the 120 s
(+3.71 m·min−1; ES: 0.87) and 180 s (+2.68 m·min−1; ES: 0.72) time windows (p < 0.05;
Figure 2). No differences were found between the ﬁrst and second half for the high
intensity Dec distance (p > 0.05).
Sensors 2023, 23, x FOR PEER REVIEW 
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signiﬁcatively lower in the second half for the 120 s time window (−7.29 m·min−1; ES: 1.44). 
Finally, the high intensity Acc distance was also higher in the ﬁrst half, but only for the 
120 s (+3.71 m·min−1; ES: 0.87) and 180 s (+2.68 m·min−1; ES: 0.72) time windows (p < 0.05; 
Figure 2). No diﬀerences were found between the ﬁrst and second half for the high inten-
sity Dec distance (p > 0.05). 
 
Figure 2. Worst-case scenarios of the elite futsal referees in the diﬀerent time windows in accelera-
tions and decelerations. * Signiﬁcant diﬀerences between halves. a,b,c Signiﬁcant diﬀerences between 
time windows [30 (a), 60 (b), 120 (c), 180 (d), 300 (e)]. 
Table 1. Worst-case scenarios of the elite futsal referees in the diﬀerent time windows. 
Time Window (s) 
30 (a) 
60 (b) 
120 (c) 
180 (d) 
300 (e) 
n = 28 
Mean 
SD 
Mean 
SD 
Mean 
SD 
Mean 
SD 
Mean 
SD 
Total distance (m·min−1) 
143.30 
14.61 
115.39 a 
9.28 
94.47 a,b 
6.21 
87.20 a,b,c 
4.76 
66.22 a,b,c,d 
3.22 
HSR Distance (m·min−1) 
66.44 
17.73 
40.23 a 
11.33 
24.21 a,b 
7.06 
18.90 a,b,c 
5.38 
12.89 a,b,c,d 
3.40 
HSR count (n·min−1) 
6.79 
2.27 
4.00 a 
1.12 
2.64 a,b 
0.61 
2.13 a,b,c 
0.55 
1.48 a,b,c,d 
0.27 
Sprint Distance (m·min−1) 
51.21 
15.81 
28.38 a 
10.90 
17.11 a,b 
6.67 
12.78 a,b,c 
4.80 
8.39 a,b,c,d 
3.06 
Sprint count (n·min−1) 
5.57 
2.13 
3.14 a 
1.35 
1.95 a,b 
0.70 
1.48 a,b,c 
0.57 
1.00 a,b,c,d 
0.36 
HI Acc Distance (m·min−1) 
42.46 
10.67 
26.20 a 
7.34 
17.21 a,b 
4.60 
13.63 a,b,c 
3.90 
9.48 a,b,c,d 
3.03 
HI Dec Distance (m·min−1) 
39.79 
10.83 
24.99 a 
6.30 
16.01 a,b 
4.20 
13.34 a,b,c 
3.53 
9.31 a,b,c,d 
2.56 
a,b,c,d Signiﬁcant diﬀerences between time windows [30 (a), 60 (b), 120 (c), 180 (d), 300 (e)]. 
 
 
Figure 2. Worst-case scenarios of the elite futsal referees in the different time windows in accelerations
and decelerations. * Signiﬁcant differences between halves. a,b,c Signiﬁcant differences between time
windows [30 (a), 60 (b), 120 (c), 180 (d), 300 (e)].
Table 1. Worst-case scenarios of the elite futsal referees in the different time windows.
Time Window (s)
30 (a)
60 (b)
120 (c)
180 (d)
300 (e)
n = 28
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Total distance (m·min−1)
143.30
14.61
115.39 a
9.28
94.47 a,b
6.21
87.20 a,b,c
4.76
66.22 a,b,c,d
3.22
HSR Distance (m·min−1)
66.44
17.73
40.23 a
11.33
24.21 a,b
7.06
18.90 a,b,c
5.38
12.89 a,b,c,d
3.40
HSR count (n·min−1)
6.79
2.27
4.00 a
1.12
2.64 a,b
0.61
2.13 a,b,c
0.55
1.48 a,b,c,d
0.27
Sprint Distance (m·min−1) 51.21
15.81
28.38 a
10.90
17.11 a,b
6.67
12.78 a,b,c
4.80
8.39 a,b,c,d
3.06
Sprint count (n·min−1)
5.57
2.13
3.14 a
1.35
1.95 a,b
0.70
1.48 a,b,c
0.57
1.00 a,b,c,d
0.36
HI Acc Distance (m·min−1) 42.46
10.67
26.20 a
7.34
17.21 a,b
4.60
13.63 a,b,c
3.90
9.48 a,b,c,d
3.03
HI Dec Distance (m·min−1) 39.79
10.83
24.99 a
6.30
16.01 a,b
4.20
13.34 a,b,c
3.53
9.31 a,b,c,d
2.56
a,b,c,d Signiﬁcant differences between time windows [30 (a), 60 (b), 120 (c), 180 (d), 300 (e)].
Sensors 2023, 23, 8662
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Table 2. Worst-case scenarios of the elite futsal referees in the different time windows by half-time.
Time Window (s)
30 (a)
60 (b)
120 (c)
180 (d)
300 (e)
n = 14
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
First Half
Total distance (m·min−1)
144.90
12.72
116.42
8.91
98.12 *,a
5.15
88.32 a,b
4.99
66.43 a,b,c
2.76
HSR Distance (m·min−1)
66.15
15.64
41.35
9.72
25.54 *,a
5.87
19.68 a,b
4.92
13.36 *,a,b,c 2.66
Sprint Distance (m·min−1)
51.93
15.01
29.08
10.27
17.59 a
6.10
13.38 a,b
4.45
8.71 a,b,c
2.63
HI Acc Distance (m·min−1) 45.44
11.99
28.24
8.49
19.06 *,a
5.30
14.97 *,a,b 4.59
10.39 a,b,c
3.72
HI Dec Distance (m·min−1) 42.32
11.88
27.43
6.33
17.38 a
4.07
14.03 a,b
3.62
10.06 a,b,c
2.72
Second Half
Total distance (m·min−1)
141.71
16.61
114.35
9.85
90.83 a
4.98
86.07 a,b
4.41
66.01 a,b,c
3.72
HSR Distance (m·min−1)
66.73
20.21
39.12
13.03
22.89 a
8.08
18.13 a,b
5.89
12.42 a,b,c
4.07
Sprint Distance (m·min−1)
50.49
17.11
27.68
11.85
16.62 a
7.40
12.18 a,b
5.21
8.07 a,b,c
3.51
HI Acc Distance (m·min−1) 39.48
8.59
24.17
5.57
15.35 a
2.90
12.29 a,b
2.58
8.58 a,b,c
1.88
HI Dec Distance (m·min−1) 37.25
9.40
22.55
5.44
14.62 a
4.00
12.64 a,b
3.43
8.56 a,b,c
2.23
* Signiﬁcant differences between halves. a,b,c Signiﬁcant differences between time windows [30 (a), 60 (b), 120 (c),
180 (d), 300 (e)].
4. Discussion
The ﬁndings of this study revealed interesting results which deserve further inves-
tigation. The aim of this research was to analyze the WCS in professional futsal referees
in the ﬁrst and second half of the match in the Spanish Futsal Cup using an LPS. To our
knowledge, this is the ﬁrst study that examined the WCS during ofﬁcial matches in the
Spanish Futsal Cup and futsal in general. The main ﬁndings of the study were that there
is an extreme inﬂuence on the time window analyzed, which conﬁrmed that the longer
the time analyzed, the lower the physical demands’ requirement is during the match.
Additionally, the referees covered longer high-intensity distances and more high-intensity
Acc in the ﬁrst half of the matches.
Previous studies have analyzed the physical demands of futsal referees [5,11,12,27]
and futsal players [15,16]. The results of this research determined the physical demands
without the time windows, except for the study of Illa et al. [15], which researched the
positional differences in the WCS of elite futsal players. Therefore, there are studies on the
physical demands of referees with similar results, although they do not analyze the WCS.
Our study highlights some interesting results. Curiously, all the variables obtained a
decreasing result among the different time windows in the ﬁrst and the second half of the
match. These results have important practical applications for training design, as referees
might have shown fatigue during the match. Nevertheless, this fatigue may have been
due to the contextual variables of the match, which should also be studied in the future to
determine whether they really interfere with the results.
In comparison to previous research, similarities were found in the total distance, as it
decreases with time over the course of the match. This study, in contrast with Illa et al.’s [15],
showed that, during the WCS of the match play, the futsal players cover more distance than
the futsal referees for each time window (30 s: 37%, 60 s: 34%, 120 s and 180 s: 31%, and
300 s: 43%). An explanation for these differences might be the continuous displacement
of the players as they are moving constantly or even the type and categories of the match,
although, in this case, it was the same division in the same country. Another possible reason
for the differences is substitutions: while a player can rest during the match, the referee
cannot; however, they do not start under the same circumstances. On the other hand, we
agree with Illa et al. [15] that the WCS decreases as the time window analyzed increases;
this may be due to fatigue occurring during the match. Moreover, Ahmed et al. [11], in the
comparison of performance between halves of a match, determined a decline in the total
distance cover by the Iraq Futsal Premier League referees (3093 m vs. 2850 m), while the
ﬁndings in this study reported a similar decrease in the relative total distances covered in
both halves in the different time windows. The total distance is also analyzed by Serrano
et al. [12] (2888.39 ± 122.55 vs. 2831.51 ± 150.26 m), showing similarities to this study in
Sensors 2023, 23, 8662
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the decrement of the variable and, also, with Ahmed et al. [11]. The physical demands
were monitored using different devices in Ahmed et al. [11], so this could explain the little
difference with the total results. Moreover, the competitions were different and, therefore,
the contextual demands were also dissimilar. In addition, there are studies that look at the
relative distances of elite futsal players in ofﬁcial matches, showing that they have similar
values between halves [16] or even experience an increase [10] compared to the results of
this research. The contextual variables during the matches might be the reason for these
differences, as well as the kind of competition, since the referees must cover the different
distances depending on the course of the match.
Furthermore, futsal referees cover more distance at sprint speed (>18 km·h−1) during
the WCS of the match play (30 s: +8%, +16%; 60 s: +5%, 15%; 120 s: +6%, +12%; 180 s:
+6%, +22%; and 300 s: +5%, +17%) than futsal defenders and pivots during the match in all
time windows, but cover less distance than wingers (30 s: −5%, 60 s: −13%, 120 s: −17%,
180 s: −17%, and 300 s: −31%) [15]. However, Illa et al. [15] only described the HSR as
>18 km·h−1, while in this study it is studied as >15 km·h−1 and the sprint as >18 km·h−1.
The differences in the distance covered at a high intensity by the referees and players may
be due to the speciﬁc nature of their individual roles during the matches. The referees must
always follow the game, as being too far away from fouls may result in incorrect decisions.
Even so, rugby union players [19] had lower values in the longest time window than the
futsal referees (−6%). The reason for the dissimilarity with rugby union players might be
due to the interruptions during the futsal matches (every action that stops the match clock),
in which the futsal referees and players continue moving even when the match is detained,
for example when there are outsides, corner-kicks, etc. [28]. Nevertheless, Serrano et al. [12]
did not study the WCS but showed that referees covered less distance at HSR (>15 km·h−1)
in the second half (235.06 ± 67.58 m vs. 207.78 ± 57.86 m, respectively). The same occurred
in this study, as the distance travelled at HSR decreased from the ﬁrst to the second half
based on the time windows. The speciﬁc situations of futsal matches may slow down the
action in the second half, which could have an impact on the referees’ ability to handle
these demands. Moreover, the number of actions over 18 km·h−1 during matches is higher
in the referees, in the lower windows (30 s, 60 s, and 120 s), than in the players in the
different positions; however, in the longer windows (180 s and 300 s), the wingers have
a higher number of such actions [15]. Nevertheless, the course of the match and the type
of competition of futsal matches might also explain the differences in the results. Another
possible explanation for this difference could be that they have a wider range of motion to
achieve a greater speed. Additionally, the sprint distance of the present results showed a
lower sprint distance (>18 km·h−1) in the second half from every time window, as occurred
in Serrano et al.’s study [12], although they did not study the WCS.
On the other hand, the Acc and Dec variables were barely discussed in this study.
However, these results can be discussed using previous studies. Acc and Dec are an impor-
tant part of the physical demands of futsal referees since the number of high-intensities Acc
and Dec is very high during the matches [12]. Other studies have analyzed stops, sideways
running, and turns during matches [5,11] to report these important actions, as they are one
of the causes of sport injuries. While previous studies have examined the results as whole,
without taking the WCS into account [5,11,12], the result of the present study shows values
of high-intensity Acc and Dec distances of the different time windows. In addition, the
high-intensity Acc and Dec values show a decrease in the second half; these results are
similar to the results of a previous futsal referees’ study [12]. Therefore, high-intensity Acc
and Dec require a high eccentric force which may produce muscular fatigue, so monitoring
them could be useful for designing strength training and injury-prevention programs.
Player performance was not examined in the current study, but player activity and
game development may affect compliance with these requirements because referee activity
is inﬂuenced by the match activity [11]. Regardless, based on the data obtained in this study,
training programs should be adjusted to the characteristics of the speciﬁc competition to
improve referees’ physical performance and prevent injuries. Illa et al. [15] had studied
Sensors 2023, 23, 8662
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the seasonal trend on all the dependent variables for the different positions, which may be
useful for developing training plans to prevent injuries. So, this could be a future, possible
focus for research on futsal referees.
This research had different limitations, as there was a low number of matches and
referees involved. Nevertheless, the study contains all the Spanish Futsal Cup matches.
Understanding the physical proﬁle and performance of the referees may be aided by
the potential correlation between the physical requirements placed on the players during
competitions and the referees’ physical parameters [11,29].
5. Conclusions
Finally, the use of LPS to monitor physical performances provides knowledge of the
speciﬁc activity proﬁles of futsal referees. This information could be useful for making
more accurate training programs and even for developing new physical tests. With all of
this, referees will know their workload requirements for each match during the different
seasons and, also, it will serve them to be able to have different references so that they can
be in the best physical conditions to face the different matches.
One of the most signiﬁcant ﬁndings to emerge from this study is the extreme effect
of the time window, which conﬁrmed that the longer the time analyzed, the lower the
requirement is during the matches. Therefore, time windows can be used in different ways,
depending on their length. Shorter time windows (30 s, 60 s and 120 s) are useful for
designing high-intensity tasks in short periods of time, while longer time windows (180 s
and 300 s) are effective for tasks that are performed over larger spaces where extensive,
high-intensity actions are to be performed.
In addition, the present study also identiﬁed that referees have their best results in
the ﬁrst half of the matches over the longer time windows. The decline in their physical
performance in the second half may be attributed to the referees’ need to keep up with
the players’ pace and the situations that arise during the futsal matches. This could lead
to a reduction in the intensity of the match in the second half, which would affect the
performance of the referees.
Finally, it should be considered that it could be helpful to study contextual variables
when carrying out future studies. Moreover, these results will serve to prepare referees
in the best conditions for the competition and allow to adapt the training plans to critical
match scenarios that may be accompanied by relevant decision making.
Author Contributions: Conceptualization, G.M.-T. and J.S.-S.; methodology, G.M.-T. and C.S.; soft-
ware, M.L.M.-S. and C.S.; validation, G.M.-T., J.S.-S. and J.L.F.; formal analysis, A.A.-C.; investigation,
G.M.-T.; resources, J.G.-U.; data curation, A.A.-C.; writing—original draft preparation, G.M.-T.;
writing—review and editing, G.M.-T., J.S.-S. and J.L.F.; visualization, G.M.-T.; supervision, L.G. and
J.S.-S.; project administration, J.L.F.; funding acquisition, J.G.-U. and L.G. All authors have read and
agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: The study was conducted in accordance with the Declaration
of Helsinki and approved by the Bioethics Committee for Clinical Research of the Virgen de la Salud
Hospital in Toledo (Ref.: 2551;17/02/2021).
Informed Consent Statement: Informed consent was obtained from all the subjects involved in
the study.
Data Availability Statement: Due to the privacy terms, the data are not available.
Acknowledgments: The authors would like to thank all the ofﬁcials and The National Commit-
tee of Referees from the Spanish Football Federation. G.M.-T. acknowledges the University of
Castilla-La Mancha and the “Fondo Social Europeo Plus (FSE+)” for funding the development of
her Ph.D. BDNS (identif.): 651201. (2022/9249). A.A.-C. acknowledges the Spanish Ministry of
Science, Innovation, and Universities for funding the development of his Ph.D (Grant Number: FPU
21/04332). This research has been developed with the help of Grant EQC2021-006804-P funded
Sensors 2023, 23, 8662
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by MCIN/AEI/10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR”,
Grant EQC2019-005843-P funded by MCIN/AEI/10.13039/50110001103 and ERDF ‘A way of making
Europe’.
Conﬂicts of Interest: The authors declare no conﬂict of interest.
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Physical Demands in the Worst-Case Scenarios of Elite Futsal Referees Using a Local Positioning System.
Martinez-Torremocha, Gemma,Sanchez-Sanchez, Javier,Alonso-Callejo, Antonio,Martin-Sanchez, Maria Luisa,Serrano, Carlos,Gallardo, Leonor,Garcia-Unanue, Jorge,Felipe, Jose Luis