Physical and physiological responses in Paddle

International Journal of Performance Analysis in Sport
2014, 14, 524-534.
45-344.
Physical and physiological responses in Paddle Tennis
competition
Castillo-Rodríguez, A.1, Alvero-Cruz, JR.2, Hernández-Mendo, A.3 and FernándezGarcía, JC.4
1
University of Malaga; Faculty of Sport Sciences, University of Pablo de Olavide,
Seville, Spain.
2
University of Malaga, Andalucía – Tech, IBIMA, Faculty of Medicine, Spain
3
Faculty of Psychology. University of Malaga, Spain.
4
University of Malaga, Andalucía – Tech, IBIMA, Faculty of Education Sciences,
Spain
Abstract
Paddle-tennis is a racket sport practised by 4.5 million people around the
world and it is increasing each year. The aim of this study was to analyse
physical responses, i.e., partial and total distances covered, and
physiological responses, i.e., mean heart rate (HR), rating of perceived
exertion (RPE) and lactate, during competition. Sixty sets were analysed on
twenty-four male paddle-tennis players. Differences in physical and
physiological variables were evaluated using one way ANOVA.High level
players (C1) covered lower distance than middle (C2) and lower level (C3)
players during set and match play (P<0.05). In addition, HR in C1 was
131.7±16.3 beats/min and versus 156.4±15.6 and 150.8±14.4 beats/min of
C2 and C3, respectively (P<0.05). Finally, C1 remained 43.7% and 12.9%
of the playing time in HR2 (50-70% of maximum HR) and HR4 (80-90%of
maximum HR) zones, respectively; while that C2 and C3 registered 15-20%
and 30-32% in HR2 and HR4 zone, respectively (P<0.05). RPE was also
significantly lower in C1 with regard to the one found in C2 and C3. These
results reveal that C1 shows lower physical and physiological responses
than C2 and C3, and these responses are similar to single tennis and tabletennis sports but lower than squash and badminton in match play.
Key words: Paddle-tennis, heart rate, lactate, rating of perceived exertion,
GPS devices and sprints.
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1. Introduction
Racket sports such as tennis, squash, badminton and paddle-tennis use intermittent
sprints determining differences in physiological responses (Alvero-Cruzet al., 2009;
Cabello Manrique and Gonzalez-Badillo, 2003; Faude et al., 2007; O.; Girard and
Millet, 2004; Novas et al., 2003). These responses, i.e., lactate (LA), mean heart rate
(HR), rating of perceived exertion (RPE), have frequently been used to assess exercise
intensity during training and match competition (Kindermann et al., 1981; Seliger et al.,
1973; Weberet al., 1978).The aim of these researches shows the game characteristics in
match play. That is the reason why tennis sport requires combining aerobic-anaerobic
trainings(Reid et al., 2008)and lots of experts of this sport also consider the speed and
agility as very important factors for the sport success (Ferrautiet al., 2002; Ferrando and
Schneider, 2013).
On the other hand, monitoring these physical and physiological responses in racket
sports has been the object of study for many studies in the last few years, either in
competition or in training, and in different modalities such as tennis (Bergeron et al.,
1991; Christmasset al., 1998; Fernandez-Fernandez et al., 2009; Martin et al., 2011;
Reid et al., 2008; Smekal et al., 2001),badminton(Cabello Manrique and GonzalezBadillo, 2003; Faude et al., 2007), squash(Alvero-Cruz et al., 2009; Girard et al., 2005;
Montpetit, 1990) and paddle-tennis (Carrascoet al., 2011).
According to the reviewed scientific literature, currently, there are not so many studies
dealing with the physiological, physical and psychological responses in high-level
paddle-tennis (Carrasco et al., 2011; Ruiz and Lorenzo, 2008).The intensity developed
in paddle-tennis is almost similar to the one of tennis. However, today there are not
researches describing the external load in competition or the differences among
categories.
The main aim of this study is to assess the physical responses (partial and total distances
covered and sprints carried out in speed intervals) and the physiological ones (mean HR
and HR in intervals, lactate levels and RPE) after sets, in paddle-tennis players during
official competitions and to determine the relationships among these variables.
2. Methods
2.1. Subjects
Twenty-four male paddle-tennis players belonging to first, second and third categories
according to the Spanish national ranking (C1, C2 and C3, respectively) participated
voluntarily in this study (mean age 28.70 ± 6.76 years; weight, 76.13 ± 9.55 kg; height,
175.38 ± 7.07 cm; BMI, 24.73 ± 2.70 kg/m2; and a training frequency of 12.0 ± 3.73
hours/week). All participants were previously informed about the characteristics of the
study, and signed an informed consent to this end.
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2.2. Instruments
Global Positioning System (GPS)
GPS technology was used in this study, particularly the SPI10 and WiSPI devices
(GPSports, Australia), and the Team AMS 1.2 software. Sixty sets were recorded, and
their time (expressed in minutes) is shown in Figure 1:
Figure 1.Time of sets in minutes according to the category.
Five categories were established in order to classify movements speed (game) adapting
the criteria set by others researches (Casamichana and Castellano, 2010): D1 and SPR1
(Standing: 0-2 km/h); D2 and SPR2 (Jogging: 2.1-7 km/h); D3 and SPR3 (Low-speed
running: 7.1-9 km/h); D4 and SPR4 (Moderate-speed running: 9.1-13.5 km/h) and D5
and SPR5 (High-speed running: 13.6-18 km/h).
Heart Rate (HR)
By means of the use of Polar S610i devices (Polar Electro Oy, Finland), HR values
were recorded every second. They were classified in six categories with regard to the
percentages of the predicted maximal HR (adapted from Gore) (Gore, 2000):HR1
(< 50%), HR2 (50-70%), HR3 (70-80%), HR4 (80-90%), HR5 (90-100%),and HR6
(100-120%). The graphical analysis allowed us to obtain the values of minimal, mean,
and maximal HR from each set (Polar Precision Performance 5.0 and Team AMS 1.2).
Rating of perceived exertion (RPE)
The perceived exertion was recorded after each set through the Borg CR-10 scale
(Foster, 1998)[18], during the first minute of recovery period. This scale was described
before the competition. In the 1-10 scale, the minimum value corresponds to “nothing at
all” and the maximum to “extremely strong” (Borg, 1998).
Lactate (La)
With regard to the analysis of lactate concentrations, 10 µl capillary blood samples from
ear lobe were collected after finishing each set, collected by means of the use of
heparinized capillaries (Deltalab 7401, Barcelona, Spain), with 100
µlLactatEncymatFarbtest PAP trays, EBP 006 model (© Dr. Lange Cuvette Test,
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Berlin, Germany) and measured through photometric technics (Miniphotometer 8/8
Plus, LP 20, Germany).
2.2. Procedures
This study took place during 2009-2010season. A pilot study was previously carried out
throughout friendly matches, whose analysis and subsequent treatment were correct.
Afterwards, three National Championships were randomly selected, one per category,
from three different Spanish cities, whose altitudes above the sea range between 15-106
metres. Climatology for the 60 sets was very similar, with a temperature between 19-23º
C and a mean humidity of 40-56%.
2.3. Statistical Analyses
The analyses were carried out through the software SPSS v. 17.0. All the variables were
analysed by means of the Kolmogorov-Smirnov test, giving normal results except the
ones collected in high-speed sprints (D5 and SPR5), in which Spearman´s correlation
coefficients and comparison of independent samples through Jonckheere-Terpstra test
were applied. Means (±SD) and the percentage of the distances covered in every speed
and HR interval were estimated. For normal variables, Pearson correlations coefficients
and ANOVA were analysed among the three categories with Bonferroni post hoc so as
to determine their differences. The level of significance was set at p≤0.05. Considering
a statistical power of 80%, a type 1 error or alpha of 0.05 and effect size of 0.82 (this is
the value equivalent to a R2 = 0.45, which was the maximum prediction coefficient
found in the literature for similar studies), we would need a minimum sample size of 21
subjects.
3. Results
The differences among the categories of physical variables of the competition are shown
in Table 1. The distances covered in sets and matches are higher in C2 and C3 with
regard to C1 (P<0.05).
Table 1.ANOVA test of physical variables for allcategories.
Variables
All
C1
C2
Vmean (km/h)
2.09 ± 0.3
1.93 ± 0.31
2.13 ± 0.25
DSet
(m)
852.7 ± 342.0
609.0 ± 113.2a,b
886.6 ± 214.0a
DMatch (m)
1813.7 ± 745.7 1117.2 ± 252.7a,b
1922.5 ± 641.4a
D1
(m)
198.6 ± 80.5
165.5 ± 90.08
204.9 ± 62.84
D2
(m)
572.6 ± 263.1
371.5 ± 132.6a,b
599.0 ± 149.7a
a,b
D3
(m)
45.21 ± 25.0
22.87 ± 11.82
49.89 ± 18.73a
D4
(m)
26.18 ± 22.8
14.42 ± 9.44
31.09 ± 27.14
D5
(m)
1.60 ± 2.7
0.99 ± 2.02
1.68 ± 2.80
a,b
SPR1
(%)
50.33 ± 6.4
55.32 ± 5.45
48.86 ± 5.57a
SPR2
(%)
46.84 ± 5.4
42.75 ± 4.88a,b
47.93 ± 4.70a
a,b
SPR3
(%)
1.97 ± 0.8
1.35 ± 0.54
2.19 ± 0.80a
SPR4
(%)
0.83 ± 0.7
0.56 ± 0.34
0.99 ± 0.91
SPR5
(%)
0.03 ± 0.06
0.02 ± 0.04
0.04 ± 0.08
Bonferroni post hoc (P<0.05); aC1–C2; bC1–C3; cC2–C3
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C3
2.18 ± 0.31
1043.4 ± 548.7b
2319.7 ± 755.3b
220.5 ± 98.45
733.3 ± 408.5b
59.29 ± 32.09b
28.29 ± 19.27
2.09 ± 3.14
48.13 ± 6.52b
48.90 ± 5.47b
2.16 ± 0.89b
0.77 ± 0.37
0.03 ± 0.05
Mean HR is lower in C1 (P<0.05) in comparison to C2 and C3 players. C1players
mainly develop their game in HR2 intervals (50-70%), while the percentages for C2 and
C3 players are between 80-100% (P<0.05). RPE is higher in C2 and C3 players than C1
(P<0.05). No significant differences in lactate levels have been found among the
categories (P>0.05; Table 2).
Table 2.ANOVA test of physiological variables among the categories.
Variables
All
C1
C2
(mmol/l)
LA
2.87 ± 1.48
2.64 ± 1.29
2.74 ± 1.38
PredMean HR
(%)
77.49 ± 8.88
Mean HR
HR1
HR2
HR3
HR4
(bpm)
149.1 ± 18.27
0.81 ± 1.7
25.2 ± 27.38
32.08 ± 19.89
26.53 ± 16.86
(< 50%)
(50-70%)
(70-80%)
(80-90%)
68.8 ± 6.89ª
,b
81.26 ± 7.74ª
C3
3.38 ±1.83
78.02 ±7.14b
131.7 ± 16.32ª,b 156.4 ± 15.63ª 150.8 ±14.35b
1.65 ± 2.55
0.49 ± 1.25
0.44 ±0.61
a
43.66 ± 36.65ª 15.22 ± 17.45 23.12 ±20.59
35.03 ± 25.33 27.86 ± 15.75 37.52 ±20.28
12.92 ± 13.58ª,b 32.8 ± 12.49a 30.41 ±20.00b
(90-100%) 14.32 ± 17.1
HR5
6.61 ± 14.76a
(100-120%) 1.06 ± 2.78
HR6
0.13 ± 0.3
(points)
Borg10
4.96 ± 2.09
3.21 ± 2.04ª,b
Bonferroni post hoc (P<0.05); aC1–C2; bC1–C3; cC2–C3
21.59 ± 17.66ª
2.05 ± 3.76
5.85 ± 1.71a
8.36 ±12.56
0.13 ±0.41
5.08 ±1.73b
A significant correlation coefficients were found between total and partial distances and
the playing time (r= 0.36 to 0.91, P<0.01), being the partial distance of the set and D2
variable the ones that show a stronger association(r= 0.91 and 0.88, P<0.01;
respectively). Besides, among physiological variables there is a correlation between
mean HR and its intervals (HR2, HR4 and HR5), with Borg scale (r= 0.37 to 0.58,
P<0.01). Mean HR and HR2 are the ones showing a stronger relationship (r= 0.58 and
0.54, P<0.01; respectively) with Borg scale. Furthermore, the time of play has a
medium relationship with LA, Mean HR and RPE (P<0.05). However, each category
features different relationships. In table 3, relationships between time, RPE and HR
(P<0.01) was observed in C1 players. Furthermore, relationship between LA, HR and
RPE (P<0.01) was developed in C3 players. Nevertheless, C2 players have not
relationship between physiological variables.
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Table 3.Spearmancorrelation coefficients of physiological variables in paddle-tennis
players.
Time Min HRMean HRMax HR RPE
LA
0.02
0.18
0.06
0.04 0.16
**
**
Time
0.43
0.47
0.56** 0.49**
C1 Min HR
0.84** 0.65** 0.36*
Mean HR
0.82** 0.42**
Max HR
0.41**
LA
0.07
0.15
0.09
0.12 -0.31
Time
-0.15
-0.35 -0.28 0.44
C2 Min HR
0.71*
0.57 -0.32
Mean HR
0.90** -0.33
Max HR
-0.30
LA
0.46*
0.13
0.40 0.54* 0.47*
Time
-0.08
0.19
0.33 0.13
C3 Min HR
0.85** 0.57** 0.23
Mean HR
0.79** 0.36
Max HR
0.39*
*P<0.05; **P<0.01; LA: Lactate; MinHR: HR
minimum; Mean HR: HR mean; Max HR: HR
maximum; RPE: Rating of Perceived Exertion.
4. Discussion
The analysis of the different physical responses of our study is one of the most relevant
contributions, since today there is a lack of research regarding this aspect of this sport.
Another contribution to be highlighted is the assessment of HR in intervals, which
determines with a greater precision this response among the players.
4.1. Global Positioning System
Monitoring the distances and high-performance sprints has been carried out by studies
in several sports, such as soccer (Casamichana and Castellano, 2010), orienteering
(Larsson and Henriksson-Larsen, 2001), athletics (Schutz and Herren, 2000; Terrier and
Schutz, 2003), cricket (Petersenet al., 2010), rugby(Cunniffeet al., 2009; SuarezArroneset al., 2012), tennis(Duffieldet al., 2010; Reid et al., 2008), accepting its
reliability and practical application in most of team sports since errors are relatively few
and predictable (Edgecomb and Norton, 2006).Petersen et al.(2010) confirm that
GPSSPI10 and WiSPI devices show a high reliability to measure total distance and the
distances covered both at low and medium speed. This reliability decreases when action
speeds are higher than 16 km/h (Petersenet al., 2010). As far as this study is concerned,
the number of sprints between 13.5 and 18 km/h was only 0.03 ± 0.06 %.
Also, a novel contribution was the results obtained with GPS in paddle-tennis. There are
not studies with these data in that sport. C1 paddle-tennis players finish the motor
actions for each set with less distance covered than others categories or levels. In C1 the
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SPR1 (55.32%) are higher than C2 and C3 (48.86 and 48.13%, P<0.05; respectively).
Furthermore, D2 and D3 distances are higher in C2 and C3, because their values are
higher in both set and match distances than in C1, too (Table 3). Therefore, we can
observe that if the player belongs to the first category, less distance are covered with
speeds higher than 7 km/h and, subsequently, less distance is covered in the set and the
match. The efficiency is a delimiting factor of the sport success, since measurements
reveal that high-level players (C1) show less physical and physiological responses.
4.2. Heart rate
Mean HR obtained in our study was different from the result obtained by Carrasco et
al.(2011) since in their study the players (n=12) belonging to the national category (C1)
showed a mean HR of 148.3 ± 13.73 beats/min, while in our study the mean HR is
131.7 ± 16.3 beats/min for C1 players. This might be due to the players’ age, since in
the study of Carrasco et al.(2011)the sample was represented by young players whose
mean age is 16.6 ± 1.5 years, while in our study the mean age is 27.8 ± 5.04 years.
However, the mean HR from the study of Carrasco et al.(2011) was similar to the C3
players of the present research (150.8 ± 14.35beats/min).
Nevertheless, while C1playeris most of the playing time (45.7%) in intervals of 50-70%
of his predicted HRmax, C2playersare in intervals of 80-100% (55.7%) and C3players
of 70-90% of their HRmax (67.9%), due to the fact that in C2, some players try not to
be downgraded from their category and others try to be promoted, which implies a
greater response; and in C3, because the main objective is to keep the category or to be
promoted, but never to be downgraded. In other rackets sports such as tennis, mean HR
in competition are ranging between 143-151 beats/min (Fernandez-Fernandezet al.,
2007; O.; Girard and Millet, 2004; Novas et al., 2003; Smekal et al., 2001),which is
similar to the rates found in our study (76-86%).
However, in badminton and squash, mean HR is higher than the collected HR for
paddle-tennis with 169-179 beats/min (Cabello Manrique and Gonzalez-Badillo, 2003;
Faude et al., 2007; Torreset al., 2004)and 167-175 beats/min (Alvero-Cruz et al.,
2009),respectively (80-88 and 88-93%, respectively).
4.3. Lactate
Mean lactate levels in singles tennis are similar to the values of paddle tennis between
1.53 and 4.0 mmol/l (Fernández-Fernández et al., 2008; Fernandez et al., 2006;
Ferrautiet al., 1998; Girard and Millet, 2004; Smekal et al., 2001). In badminton, lactate
levels are higher in many researches, although they range between 1.9 and 3.8 mmol/l
of lactate (Cabello Manrique and Gonzalez-Badillo, 2003; Faude et al., 2007; Torres et
al., 2004). Finally, in squash, lactate levels are very higher than the once assessed in our
study, with values ranging between 3.4-6.5 mmol/l (Alvero-Cruz et al., 2009) in
contrast to 2.9±1.5mmol/l of our study. Finally, in table-tennis competition, the players
get a 2.2mmol/l of mean lactate level (Zagatto et al., 2010).
4.4. Rating of perceived exertion
Several studies have used scales of RPE in order to measure intensities in training
sessions and competition(Borg, 1998; Chenet al., 2002; Green et al., 2005; MendezVillanuevaet al., 2010; Seiler and Sjursen, 2004).In racket sports the use of Borg scales
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has turned out to be useful so as to compare physiological responses in squash (AlveroCruz et al., 2009)and in tennis(Fernandez-Fernandez et al., 2009; Fernandez et al.,
2006; Girard et al., 2005; Mendez-Villanueva et al., 2010; Novas et al., 2003). In tennis
match, mean RPE was 4.29 ± 0.66 in Borg’s scale(Fernández-Fernández et al., 2008;
Mendez-Villanueva et al., 2010)in contrast to 4.96 ± 2.09 of RPE obtained in
paddle-tennis players. In squash, data are higher than the ones of tennis and
paddle-tennis sports with the following results: 5.5 ± 2.3 RPE in winners and 7.6 ± 2.43
RPE in losers (Alvero-Cruz et al., 2009).
Finally, the correlation coefficients of the physiological responses in different
racketsports, such as squash and tennis, are higher than paddle-tennis between RPE and
mean HR (rho: 0.73 and 0.62, p<0.05; respectively) (Alvero-Cruz et al., 2009; Redha,
2001).
5. Conclusions
Competition paddle-tennis sport has some physical and physiological responses (mean
HR, lactate and RPE) similar to tennis, although they are lower than the ones obtained
in other racket sports such as squash and badminton. Distances covered at low speed (09 km/h) and low intervals of HR (50-70%) are performed by C1 players. With regard to
the external load, we can highlight that in C1 distances covered are less than in C2 and
C3, and regarding the internal load, mean HR and RPE are very lower in C1 than in C2
and C3.
6. Acknowledgements
We would like to thank "Investigación Observación de la interacción en deporte y
actividad física: Avances técnicos y metodológicos en registros automatizados
cualitativos-cuantitativos” of Secretaría de Estado de Investigación, Desarrollo e
Innovación del Ministerio de Economía y Competitividad [DEP2012-32124], during
2012-2015.
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Corresponsal author:
Alfonso CASTILLO-RODRÍGUEZ
Degree: PhD. E-mail: [email protected]; Telephone: +34 620 397 897
Address: Ctra. Utrera Km1. Faculty of Sport. University of Pablo de Olavide (41013Seville) Spain.
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