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Metabolic Demand and Internal Training Load in Technical-Tactical Training Sessions of Professional Futsal Players

Wilke, Carolina F.1,2; Ramos, Guilherme P.1,3; Pacheco, Diogo A.S.1; Santos, Weslley H.M.1; Diniz, Mateus S.L.1; Gonçalves, Gabriela G.P.2; Marins, João C.B.3; Wanner, Samuel P.1; Silami-Garcia, Emerson1

Author Information
The Journal of Strength & Conditioning Research: August 2016 - Volume 30 - Issue 8 - p 2330-2340
doi: 10.1519/JSC.0000000000001321
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A fundamental pillar for sport performance enhancement is to achieve an adequate balance between training stimuli and athlete recovery. Within this context, monitoring the training load provides coaches and sports scientists with important information that enables adjustments in training sessions and recovery periods, thereby maximizing performance improvement (26). Although many studies have been conducted in sports with extended media coverage, including cycling (17,28), rugby (22,43) and soccer (16,24), fewer studies have focused on less-popular sports (41), such as futsal.

Several methods can be used to measure the internal load, which is defined as the individual response to the workload (external load) imposed on athletes during training or competition. The heart rate (HR) is indicative of the overall physiological strain during exercise (2,3) and can be used to calculate the training impulse (TRIMP), a training load index (35). TRIMP was originally calculated by multiplying the average intensity (expressed as the percentage of HR reserve) by the training duration and by a weighting factor, which was included to account for the nonlinear increase in the contribution of the anaerobic system on the energy supply with increasing exercise intensity (35). The concept of TRIMP was later developed by authors who proposed intensity zones based on HR and attributed different weights to the time spent on high-intensity and low-intensity exercises during a training session (18,28). Lucia et al. (28) used the ventilatory threshold (VT) and the respiratory compensation point (RCP) as criteria to determine 3 intensity zones, such as, the zones below the VT (considered to be low intensity), between the VT and RCP (moderate intensity), and above the RCP (high intensity). Using Lucia's method, Milanez et al. (32) described the training load of 8 on-court semiprofessional Brazilian futsal players during 78 training sessions performed before the main competition of the season. The authors observed that the players spent 73% of the duration of a technical-tactical training session below the VT, 20% between the VT and RCP, and only 7% above the RCP.

The session rating of perceived exertion (sRPE) is a simpler method than measuring the HR to quantify the internal training load and consists of assessing athletes' RPEs using Borg's 10-point scale 20–30 minutes after a training session and then multiplying the score by the session duration (21). To validate the use of this method in team sports, previous studies tested the correlation between sRPE and TRIMP and found moderate to very strong correlation coefficients (4,25,40). However, only one study has investigated the relationship between these variables to quantify the internal load during physical and technical-tactical training sessions in futsal (32). Milanez et al. (32) reported strong to very strong individual correlation coefficients between sRPE and TRIMP and concluded that sRPE is a valid method to measure the internal training load of futsal players.

Futsal is an intermittent, high-intensity sport (11,13,14,38) in which an unlimited number of player substitutions are allowed by official rules (20). To enable the athletes to achieve optimal physical, technical and tactical performance during competitive matches, coaches usually plan training activities with aspects similar to those of different match situations (e.g., small-sided games, specific exercises with the same number of players and court sizes as in official matches but with different rules and instructions, and match simulations [MS]) in an attempt to mimic both the physiological and cognitive demands of matches during the training sessions (42,44). Although previous studies have shown that some aspects of situational activities, such as the rules, pitch size and number of players, can influence exercise intensity in different sports (1,24), it remains unknown whether the existing information can be used to guide futsal-training prescription (11). Thus, based on the importance given to specific training as a determining factor for achieving optimal performance during competitive matches, the intensities of specific activities for futsal with different rules and number of players must be measured and compared.

Another aspect that deserves further investigation is the stress imposed on players of different tactical positions by training activities. A recent study showed that the concentrations of muscle damage and inflammation markers after matches are similar in defenders, wingers and pivots (15), suggesting similar physiological strain among players during the matches. However, to the best of our knowledge, no study has investigated whether physiological strain is also similar among athletes of different playing positions during technical-tactical training sessions.

Thus, considering the lack of information about training load in futsal, the general aim of this study was to characterize different aspects of training load in professional futsal technical-tactical training sessions. Four specific aims were established: (a) characterize the metabolic demands (estimated V[Combining Dot Above]O2) and intensity (percentage of HRmax; %HRmax) of professional futsal-training sessions, (b) characterize and compare the training intensity (%HRmax) and intensity distribution (percent of time spent at different intensity zones) among players of different positions (wingers, defenders, and pivots), (c) characterize and compare the intensity of typical exercises (4 × 4, 6 × 4, and MS) performed by professional futsal players, and (d) investigate the association between an objective method (TRIMP) and a subjective method (sRPE) of measuring the internal training load in futsal.


Experimental Approach to the Problem

This study followed a descriptive longitudinal approach. The internal load of professional futsal players was recorded in every technical-tactical training session over 8 weeks. These experiments were conducted between late September and early November, when the team was not participating in any competition and only participated in 2 friendly matches. The training sessions were planned and executed by the coaches; to ensure ecological validity, the researchers did not interfere with either the planning or execution of the training sessions.

Before the commencement of the study, all of the players performed an incremental maximal test to assess their maximal HR (HRmax) and their HR relative to the VT and to the RCP. To evaluate the internal training load, we measured the HR and RPE of each player in each session over the 8-week period. To assess whether the players' hydration status could affect the HR measurements during training sessions, the volume of fluid consumed, the body mass loss, and the environmental temperature were also measured over the entire study. Estimated oxygen consumption (V[Combining Dot Above]O2), energy expenditure, sweat loss, TRIMP, and sRPE were calculated for each player in each training session. To guarantee a deeper understanding of the observed data, the training intensity for the different playing positions (winger, defender, and pivot) and the intensities of 3 futsal-specific training activities were compared. Additionally, the correlation between 2 internal load indices (TRIMP and sRPE) and 2 measures of training intensity (HR and RPE) were tested.


Twelve top-level male futsal players from a first division Brazilian team participated in this study. At the time of the study, the players displayed the following characteristics (mean ± SD): 23.0 ± 4.3 years of age (18–32 years range), 70.7 ± 8.5 kg body mass and 54.2 ± 4.2 mlO2·kg−1·min−1 maximal oxygen consumption (V[Combining Dot Above]O2max). During the year of this investigation, the team won the second main national competition promoted by the Brazilian Futsal Confederation. The players were familiarized with the procedures for 4 weeks before the commencement of the study and were asked to maintain their habitual diet during the experimental period.

All of the procedures described in this study were approved by the Federal University of Minas Gerais Ethics Committee (14376413.0.0000.5149), and all volunteers provided their written consent after being informed of the procedures, potential risks, and benefits of their participation in this investigation.


Preliminary Tests

A maximal incremental test (adapted from Dittrich et al., 16) was performed to assess the players' V[Combining Dot Above]O2max, HRmax, VT, and RCP. The test was conducted on a treadmill (HPX 380; Total Health, Jaboticabal, SP, Brazil) with an initial speed of 9 km·h−1 and additional increments of 1.2 km·h−1 every 3 minutes until volitional fatigue. If the subject did not interrupt the exercise after finishing the stage corresponding to 16.2 km·h−1, this speed was kept constant, and the inclination was increased by 1% every 3 minutes until fatigue (this was the case for only one player). At least 2 of the following criteria had to be met to determine the V[Combining Dot Above]O2max: (a) no further increase in V[Combining Dot Above]O2 or HR despite an increase in exercise intensity; (b) RPE higher than 17 on the 6–20 scale; and (c) respiratory exchange ratio higher than 1.10. The highest HR and V[Combining Dot Above]O2 registered during the test were considered the subject's HRmax and V[Combining Dot Above]O2max.

V[Combining Dot Above]O2 and V[Combining Dot Above]CO2 were measured breath-by-breath using an open circuit gas analyzer (GasSys2; Biopac Systems, Goleta, CA, USA) calibrated before each test. Heart rate was continuously measured (Team System; Polar, Oulu, Finland) and was recorded every minute, and RPE (15 point scale—Borg, 12) was assessed immediately after the completion of each stage and at volitional fatigue. Average data from the last minute of each stage were used to determine the individual V[Combining Dot Above]O2 values. A linear regression equation was developed using individual HR and V[Combining Dot Above]O2 data to establish the association between these 2 variables.

The VT and RCP were visually identified by 2 independent investigators, and a consensus-derived value was used. The VT was defined as the HR value corresponding to the moment of increase in VE.V[Combining Dot Above]O2−1 without a concomitant increase in VE.V[Combining Dot Above]CO2−1, whereas RCP was defined as the moment of increase in both VE.V[Combining Dot Above]O2−1 and VE.V[Combining Dot Above]CO2−1 (6). Whenever there was a disagreement between the 2 investigators, a third researcher was asked to analyze the data. The point at which 2 of the 3 researchers agreed was used for subsequent analyses. Notably, disagreement only occurred for the RCP analysis of one player.

Training Sessions

In total, 37 technical-tactical training sessions were conducted and monitored over 8 weeks. The training routine comprised 1 to 2 daily technical-tactical training sessions performed on indoor futsal courts 6 days per week and 1 to 2 resistance training sessions per week. During the study, the researchers did not interfere with the training planning or execution, which were coordinated by the coaches of the team. Care was taken to not modify the training session routine to guarantee the ecological validity of the results.

All of the evaluated sessions were divided in the following 2 parts: (a) the first 15–30 minutes consisted of a warm-up that included general exercises such as jogging, low-intensity multidirectional movements and stretching; and (b) the next 60–90 minutes consisted of match simulations or activities specific for futsal, with varying instructions and numbers of players, which aimed to improve the technical and tactical skill of the athletes. The second part of each training session was termed the technical-tactical period. The training sessions were performed on courts with the following dimensions: 36 × 20 m (n = 23), 31 × 19 m (n = 11), and 25 × 15 m (n = 03). The court dimensions were selected by the coaching staff based on the space available in the multisport training center.

Before each training session, each player's seminude (wearing shorts only) body mass was measured. Then, each player received a HR monitor (Team System; Polar) that was used during the entire session. This monitor is reliable for measuring HR during continuous and intermittent exercises (3). Two bottles of water (WAT) and one bottle of a commercial carbohydrate beverage (CHO, 6%), filled with approximately 500 ml of fluid and previously weighed in a 0.02-kg precision balance (MF100; Filizola, São Paulo, Brazil), were provided for each athlete. They were instructed to consume these fluids ad libitum and not to use the fluids for purposes other than ingestion (such as applying to the skin for refreshment). If necessary, the researchers refilled the bottles with the respective drink during training, thereby guaranteeing ad libitum fluid ingestion. Water and carbohydrate beverage were offered to maintain the team's routine because both of these fluids were available during all of the previous training sessions throughout the year.

Heart rate was continuously measured, and training activities were recorded using a digital video camera (DCR SR87 HD; Sony, Tokyo, Japan). Wet and dry bulb temperatures were measured using a psychrometer (Alla France, Chemillé-Melay, France) every 15 minutes to calculate the average wet bulb globe temperature (WBGT) for indoor environments.

At the end of the training sessions, the players dried their sweat with a towel and then underwent a second body mass measurement. Within 15–20 minutes after the end of the session, RPE was assessed using a 10-point scale (CR-10; Foster et al., 21) by asking each player individually “how was your training?” Finally, all of the bottles were weighed to calculate the volumes of WAT, CHO, and total fluid ingested.

Total sweat was calculated as the difference between pretraining and post-training body mass corrected for the total volume of fluid ingested. Total sweat was divided by the duration of the training session to assess the sweat rate. The difference between post-training and pretraining body mass was divided by the pretraining body mass and multiplied by 100 to calculate the percent change in body mass (%BM). Body mass losses higher than 3% are associated with exaggerated exercise-induced increases in HR (23,39).

To estimate the V[Combining Dot Above]O2 during the training sessions, a linear regression analysis was performed using the individual V[Combining Dot Above]O2 and HR values obtained during the incremental test. The average HR measured in each training session for each athlete was then applied to the resultant regression equation to estimate the average V[Combining Dot Above]O2 of the training sessions. The energy expenditure was then estimated, considering that the uptake of 1 L of O2 corresponds to the expenditure of 4.8 kcal (9).

Training intensity was calculated as the average percentage (%) of HRmax and time (in minutes) spent in 3 HR zones, defined as follows: zone 1: HR values lower than the HR corresponding to the VT; zone 2: HR values between those corresponding to the VT and RCP; and zone 3: HR values higher than the HR corresponding to the RCP. The time spent in each zone was then multiplied by its corresponding score (zone 1 = 1; zone 2 = 2; zone 3 = 3), and the products were summed to calculate the individual TRIMP for each training session (28). The sRPE was also calculated by multiplying each player's RPE after the training session by the session duration in minutes (21).

To compare the training intensity between playing positions (i.e., wingers [n = 5], defenders [n = 2] and pivots [n = 5]), the average values for % HRmax and the time spent in the high-, moderate-, and low-intensity zones were calculated for each position in each session (i.e., n = 35 sessions for each of the 3 playing positions). The head coach was responsible for determining the playing position of each athlete.

Characterization of Different Training Activities

The results from 9 athletes were used to calculate the average %HR and intensity distribution (time spent in zones 1, 2, and 3) for 3 specific activities frequently performed during the training sessions. All of the selected activities included in the analysis met the following criteria: (a) performed in the morning; (b) held in a 36 × 20-m court; and (c) lasted for a minimum of 15 minutes. For data analysis, the 3 specific activities were as follows:

  • 6 versus 4 (6 × 4): Each team comprised 6 players on the court, though a numerical advantage was created for the offensive team (attack overload). The opposite team was allowed to maintain only 4 players on the defensive half of the court, and the other 2 players stayed in the attack half of the court, without participating in the defense. Furthermore, both teams had a substitute player who could replace one of the team players on the court at any time. The average duration of the 2 situations selected was 18 ± 4 minutes, and the complete HR recordings from the first 15 minutes were analyzed, including the time spent for instructions and substitutions. The main instruction provided by the coach was to maintain ball possession for as long as possible while attacking. Both teams had similar chances to attack during the activity, and the coach instructed the players whenever he felt necessary.
  • 4 versus 4 (4 × 4): Each team comprised 4 players and a goalkeeper on the court plus one substitute player who could replace one of the players on the court at any time. The average duration of the 4 situations selected was 21 ± 8 minutes, and the complete HR recordings from the first 15 minutes were analyzed, including the time spent for instructions and substitutions. The focus of the instruction provided to the athletes in these activities was the attack movement. Both teams had similar opportunities to attack during the activity, and the coach instructed the players whenever he felt necessary.
  • Match simulation (MS): This activity involved the same number of players as did the 4 × 4 activity (4 players and a goalkeeper on the court plus 1 substitute player). The differences between these 2 activities were mainly in the duration, rules, and instruction. The simulations that were analyzed comprised two 10-minute half periods separated by 5 minutes; each athlete was evaluated during the 20 minutes of MS, including the moments when they were playing and when they were substituted. The rules were the same as those of an official match, and there was no interruption for instructions. In addition, no specific instruction about the aim of MS was provided to the athletes by the coach.

Statistical Analyses

Kolmogorov–Smirnov tests were performed to test data normality. Because all data were normally distributed, they are presented as the mean ± SD. Comparisons of the weekly internal training load (TRIMP and sRPE) were performed using one-way analysis of variance (ANOVA). Post hoc differences in TRIMP were assessed using the Hochberg test, and differences in sRPE were assessed using the Games–Howell test; both used a Bonferroni correction. To compare the average training intensity (% HRmax) among the playing positions (wingers, defenders and pivots), a one-way ANOVA was performed. To compare the training intensity distribution (below LT, between LT and RCP, and above RCP) among the playing positions, a 2-way ANOVA ([3] time in each training intensity zone × [3] playing position) was performed followed by Tukey's post hoc test. Comparisons of the average intensity among the 3 training activities (4 × 4, 6 × 4, MS) were assessed by repeated measures one-way ANOVA, and comparisons of the intensity distribution among these 3 activities were assessed by repeated measures 2-way ANOVA ([3] time in training intensity zone × [3] activities). For these comparisons, data reliability was tested using both relative (intraclass correlation coefficient; ICC (3, 3); 45) and absolute (standard error of measurement; SEM) indices, and the effect size was calculated using the omega index (ω). The associations between HR and RPE and between TRIMP and sRPE were assessed using Pearson's correlation coefficients and classified according to Evans' criteria (0.00–0.19 – very weak; 0.20 to 0.39 – weak; 0.40 to 0.59 – moderate; 0.60 to 0.79 – strong; above 0.80 – very strong) (19). The difference in the volumes of CHO and WAT consumed was tested using Student's t-test. A significance level of p ≤ 0.05 was adopted. All of the analyses were performed using SPSS 17.0 software for Windows (SPSS, Inc.).


The exercise intensities that corresponded to the players' VT and RCP were 75.8 ± 4.8% of HRmax (53.7 ± 8.6% of V[Combining Dot Above]O2max) and 89.8 ± 5.1% of HRmax (78.2 ± 9.6% of V[Combining Dot Above]O2max), respectively.

Although the training sessions were not exclusively held on one court size, all of the training data were analyzed and presented together because no differences were found in the average intensities attained by the players on the different court sizes (36 × 20-m court: 74.1 ± 3.6% of HRmax; 31 × 19-m court: 73.7 ± 3.9% of HRmax and 25 × 15-m court: 70.5 ± 1.5% of HRmax; F(2,33) = 1.345, p = 0.274; ω = 0.269).

The average training intensity was 73.7 ± 3.6% of HRmax, which corresponded to an energy expenditure of 846 ± 129 kcal or 9.3 ± 1.0 kcal·min−1. Analysis of the intensity distribution showed that the athletes exercised at intensities above the RCP for 20.4 ± 7.8%, between the RCP and the VT for 28.2 ± 5.6% and below the VT for 51.4 ± 9.7% of the time during the training sessions. The number of monitored sessions per athlete was 23 ± 8, with a minimum of 13 and a maximum of 37 sessions per athlete. The average duration of the sessions was 90.8 ± 11.6 minutes, and the average environmental conditions were 27.3 ± 2.7° C and 23.0 ± 2.2° C for dry bulb temperature and WBGT, respectively.

The average daily and average weekly TRIMP values over the 8 weeks were 153 ± 21 arbitrary units (AU) and 531 ± 148 AU, respectively. As shown in Figure 1, no difference in the average daily TRIMP was found over the 8 weeks (minimum of 140 ± 20 AU in week 5 and maximum of 173 ± 21 AU in week 6; F(7,31) = 1.350; p = 0.261; ω = 0.48). However, the weekly TRIMP was lower in the sixth week than in the eighth week of training (266 ± 139 in week 6 vs. 695 ± 105 in week 8; F(7,63) = 3.597; p = 0.001; ω = 0.96). Additionally, no difference in the daily sRPE was found between the weeks (minimum of 359 ± 58 AU in week 5 and maximum of 514 ± 54 AU in week 6; F(7,31) = 1.477; p = 0.212; ω = 0.52), though the main effect for weekly sRPE was significant (F(7,67) = 6.184; p < 0.001; ω = 0.99). sRPE in week 6 (869 ± 416) was lower than in weeks 1, 4, 7 and 8 (2273 ± 423, 2183 ± 804, 2332 ± 845 and 2399 ± 351, respectively; p < 0.001). The lower weekly TRIMP and sRPE observed in week 6 are likely because the team played 2 friendly matches but performed no other training activities, resulting in fewer sessions compared with the other weeks.

Figure 1
Figure 1:
Average training loads during the 8 weeks of the study. A) Daily TRIMP; (B) weekly TRIMP; (C) daily sRPE; (D) weekly sRPE. *p ≤ 0.05 compared with week 6.

During the technical-tactical period, no difference was observed in the average training intensity (i.e., %HRmax) among players of different positions (wingers: 76.3 ± 4.9% of HRmax, defenders: 74.4 ± 4.9% of HRmax and pivots: 76.4 ± 4.0% of HRmax; F(2,100) = 2.032; p = 0.136; ω = 0.41). However, these similar average values resulted from different distributions within the intensity zones (Figure 2). The wingers spent more time in the high-intensity zone than the pivots (33.6 ± 15.6% vs. 19.1 ± 8.5%; F(2,100) = 12.122; p < 0.001; ω = 0.995) and defenders (25.1 ± 12.0%; p = 0.016; ω = 0.995). The pivots spent more time in the moderate-intensity zone than the wingers and defenders (pivots 37.4 ± 7.9% vs. wingers: 20.9 ± 8.7% vs. defenders 23.3 ± 7.2%; F(2,100) = 44.271; p < 0.001; ω = 1.00), and the defenders spent more time in the low-intensity zone than did the pivots (wingers: 45.7 ± 11.5% vs. defenders 51.6 ± 15.4% vs. pivots 43.5 ± 10.4%; F(2,100) = 3.975; p = 0.019; ω = 0.70).

Figure 2
Figure 2:
Intensity distribution in zones 1 (low intensity; below the VT), 2 (moderate intensity; between the VT and RCP) and 3 (high intensity; above the RCP) among different playing positions. *p ≤ 0.05 compared with the wingers; &p < 0.001 compared with the pivots; #p ≤ 0.05 compared with the defenders.

The 3 training activities (4 × 4, 6 × 4 and MS) yielded similar average intensity values (F(2,16) = 0.158; p = 0.855; ω = 0.07). The main effect for the 2-way ANOVA (activity × intensity zone) was not significant neither for activity (F(2,72) = 0.000047; p = 1.000; ω = 0.05) or the time spent in the different intensity zones (F(2,72) = 2.824; p = 0.066; ω = 0.54). There was also no interaction between the activity and intensity zone (F(4,72) = 0.876; p = 0.483; ω = 0.266) (Table 1).

Table 1
Table 1:
Average intensity and intensity distribution of 3 training activities frequently performed during the training sessions.*

A strong correlation was observed between TRIMP and sRPE (r = 0.70; r2 = 0.49; p < 0.001; ω = 0.98; Figure 3). However, when the correlation between these 2 parameters was assessed per athlete, only 4 of the 12 athletes presented significant correlation coefficients (Table 2). Additionally, only a very weak correlation was observed between the average training intensity (%HRmax) and the average RPE (r = 0.12; r2 = 0.01; p = 0.465; ω = 0.32; Figure 4).

Figure 3
Figure 3:
Correlation between the average TRIMP and average sRPE in each of the 37 training sessions (p < 0.001).
Table 2
Table 2:
Individual correlation coefficients between TRIMP and sRPE.*
Figure 4
Figure 4:
Correlation between the average RPE and the average intensity, measured as the %HRmax, in each of the 37 evaluated training sessions (p = 0.465).

The results regarding hydration showed that the volume of WAT consumed during training sessions was higher than the volume of CHO consumed (1.02 ± 0.23 L vs. 0.31 ± 0.16 L; T(35) = 12.223; p < 0.01; ω = 0.99). The estimated total sweat and sweat rate were 1.62 ± 0.25 L and 1.13 ± 0.53 L·h−1, respectively, resulting in a body weight reduction of 0.39 ± 0.15 kg at the end of the sessions, representing a body mass loss of 0.52 ± 0.19%. During the 37 training sessions, only one athlete exhibited a body mass loss of between 2 and 3% within an individual session, and none of the athletes presented a loss greater than 3%.


This study aimed to characterize different aspects of training load in professional futsal technical-tactical training sessions. The specific aims of the present study were as follows: (a) characterize the metabolic demands (estimated V[Combining Dot Above]O2) and intensity (%HRmax) of professional futsal-training sessions, (b) characterize and compare the training intensity (%HRmax) and intensity distribution (percent of time spent at different intensity zones) among players of different positions (wingers, defenders, and pivots), (c) characterize and compare the intensity of typical exercises (4 × 4, 6 × 4, and MS) performed by professional futsal players, and (d) investigate the association between an objective method (TRIMP) and a subjective method (sRPE) of measuring the internal training load in futsal. The average training intensity was 73.7 ± 3.6 %HRmax, which corresponded to an energy expenditure of 846 ± 129 kcal or 9.3 ± 1.0 kcal·min−1. No differences were observed in the intensity during the technical-tactical period among players of different positions. However, these similar average values for different playing positions resulted from different distributions within the intensity zones. There was also no difference in intensity among the 3 futsal-specific activities (4 × 4, 6 × 4, and MS). Finally, although a strong correlation was found between the average TRIMP and sRPE (when data were collectively analyzed), this relationship was significant for only 4 of 12 players.

The VT and RCP of the players were attained at 53.7 ± 8.6% and 78.2 ± 9.6% of the V[Combining Dot Above]O2max, respectively. These values are lower than those observed in previous studies with professional and semiprofessional futsal athletes (5,37), indicating that our athletes presented lower levels of physical fitness. These differences among studies can be partly attributed to the use of different maximal incremental exercise protocols for assessing physical fitness. Although they may have shown lower fitness levels, the athletes in our study played for a high-level professional team that won the second most important national championship in the year of the study, indicating that performance in futsal is multifactorial and depends not only on physical capacity but also on technical, tactical, and psychological abilities (11,42).

The average intensity and energy cost of the training sessions corresponded to 73.7 ± 3.6% HRmax and 9.3 ± 1.0 kcal·min−1, respectively, and the players trained for approximately half of the duration of each session at moderate (28.2 ± 5.6%) and high (20.4 ± 7.8%) intensities. These results are somewhat different from those of a previous study (32), in which futsal players spent 20% and 7% of the technical-tactical sessions at moderate and high intensities, respectively. The differences between the 2 studies may be at least partly attributed to the types of training exercises executed by each of the teams, though the activities performed were not described in the study by Milanez et al. (32).

The average intensity of the technical-tactical training sessions was lower than that previously reported for official matches (85–90% of HRmax) (10,38). This observation is in line with studies conducted in soccer and can be partly attributed to higher motivation levels during official matches than during training (8). Another possible explanation for this result is the decrease in the players' HRs that occurs while players are receiving the coach's feedback or being substituted during the activities; such moments were not accounted for in previous studies that investigated official matches (10,38). This hypothesis is supported by the observation that our players spent similar percentages of time at high and moderate intensities during MS (when there was no interruption for instructions) compared with official matches (10).

The average intensity did not differ among players of different tactical positions. However, wingers had longer periods at high intensity than players in other positions, whereas the pivots spent more time at moderate intensity (Figure 2). Additionally, the defenders had longer periods at low intensity than the pivots. Based on the type of activities mainly executed during the technical-tactical period (involving the same number of players, pitch size, and rules as a match), we hypothesized that the differences observed are consequences of differences in tactical function, distance covered, and motor actions performed by players of different positions during match situations. The observation of difference in the amounts of time spent in the 3 intensity zones among futsal players of different positions is a novel finding of the present study.

The intensity of specific exercises for soccer depends on the number of players involved, the pitch size (1,24), and the rules (3). In contrast, the present results suggest that differences in the exercise rules (4 × 4 vs. MS) or in the number of players (4 × 4 vs. 6 × 4) of the typical activities evaluated, even though resulting in different areas covered per player (4 × 4 and MS = 90 m2; 6 × 4 = 72 m2), were not sufficient to change the overall intensity measured by HR during professional futsal training (Table 2). The unpredictability of situational activities is a well-described characteristic and is considered by coaches as a positive aspect that allows for the tactical (decision-making), technical, and physical development of athletes (42). This characteristic can also generate high variability, as observed by the ICC in the average intensity and percentage of time spent in low intensity for the 3 game formats, which may have influenced the lack of differences observed among the studied activities.

We also measured the daily % of body mass loss after training to estimate the hydration status of the players. The body mass loss after training was 0.52 ± 0.19%, indicating that fluid ingestion almost matched the sweat loss (1.32 ± 0.20 L vs. 1.62 ± 0.25 L, respectively), even in the presence of a high sweat rate (1.13 L·h−1). Therefore, our HR recordings were not likely influenced by dehydration. This assertion should be considered with caution because other hydration measurements (e.g., urine-specific gravity, urine osmolality, and plasma osmolality) were not obtained (7).

The weekly sRPE observed for most weeks in this study (1395–2332 AU) was lower than that in previous studies of futsal, in which sRPE varied from 2674 to 3884 AU in the preseason (36) and from 2,000 to 6,000 AU in the precompetition period (33). Notably, although our players were subjected to resistance training once or twice each week, these sessions were not included in the calculation of weekly sRPE because our main interest was to study the technical-tactical sessions.

Situational activities are widely used for team sports training because they enable the simultaneous development of physical capacity and technical-tactical ability (27,44). Serrano et al. (42) observed that high-level futsal coaches from Portugal, Spain, and Brazil use both small-sided games and MS activities to improve players' capacities to cope with the technical, tactical, physiological, and psychological demands of matches. However, a possible disadvantage of using situational activities as the only training method is the low variation in the internal load, as evidenced in the present study by the lack of difference in the daily TRIMP and sRPE values across the 8 weeks (Figure 1). These results are in agreement with a recent study that showed low variation of training loads across several training cycles in a professional soccer team (29). Notably, however, the training load obtained in the present study refers only to an offseason period, during which no official matches were held. Future investigations should evaluate whether the relatively constant loads caused by trainings sessions consisting mostly of situational activities prevent optimal adaptations and impair match performance in futsal at different periods during a season.

We observed a strong association (r = 0.70) between the average values of TRIMP and sRPE, 2 measures commonly used to quantify the training load, in the 37 evaluated sessions (Figure 1). This finding is in agreement with some previous studies that investigated this association in technical-tactical training sessions in team sports (4), including professional futsal (32). However, upon individually analyzing the association between these 2 variables (Table 1), we found very weak to strong correlations (0.11–0.70), which differ from the moderate to very strong and significant correlations previously reported for futsal (0.64–0.91; 31) and soccer players (0.57–0.97; 4). One possible reason for these differences among studies is that the present study is the only one to use data collected exclusively from technical-tactical training sessions to report individual correlations between TRIMP and sRPE. In fact, when analyzing a team as a whole, Milanez et al. (32) observed stronger correlations between TRIMP and sRPE in technical-physical sessions (involving technical drills, resistance training, high intensity interval running, and plyometric training) compared with those found in technical-tactical sessions.

Despite the strong association between sRPE and TRIMP (Figure 3), a very weak association was observed between the RPE and HR (r = 0.12; Figure 4), possibly because one common factor used in both the sRPE and TRIMP calculations (i.e., session duration) was not accounted for when testing the correlation between a physiological measure (HR) and a psychophysiological measure (RPE). Therefore, sports scientists and coaches should carefully analyze the characteristics of the sport and the available methods to select the optimal tool for monitoring the responses of athletes to a given training stimulus.

The lack of correlation between HR and RPE can be partially explained by the limited ability of the HR to reflect the physiological strain associated with high-intensity intermittent activities (3). Additionally, the RPE is representative of a psychophysiological state and can be influenced by the athletes' state, such as anxiety level, mood, personality and depression level (34), and by their physical condition (31). We also suggest that the cognitive effort imposed by the tactical challenge in the majority of the training sessions may also have influenced the RPE. Indeed, mental fatigue can enhance the RPE and reduce performance in high-intensity, short-duration exercise despite a lack of differences in cardiovascular or metabolic parameters (30), suggesting that physical and cognitive efforts interact to determine the RPE.

An attempt to reduce the limitations of the HR for quantifying the metabolic demand of training sessions could include V[Combining Dot Above]O2 measurement with a portable spirometer; however, this equipment would limit the players' activity because of the possibility of falls and contact with other players. Therefore, the use of a portable spirometer would reduce the ecological validity of this study with high-level futsal players. Future studies should also examine the motor activity of players to increase knowledge of the load of futsal training sessions.

In conclusion, our results showed that the average intensity of technical-tactical training sessions of a professional futsal team was 73.7 ± 3.6% of HRmax, which corresponded to an energy expenditure of 9.3 ± 1.0 kcal·min−1. Analysis of the intensity distribution indicated that the athletes spent most of the time at intensities below the VT. Although the average training intensity was similar among wingers, pivots and defenders, the times spent at low-, moderate- and high-intensity zones differed among players of different positions. Contrary to the observations made during the entire training session, players exercised predominantly at intensities above the VT during the 3 typical activities (4 × 4, 6 × 4, and MS), and even with different rules and different numbers of players, no differences in the average intensity or the intensity distribution were found among these activities. Finally, a strong correlation was observed between TRIMP and sRPE when both parameters were averaged for the team; however, when analyzed on an individual basis, this association was significant for only 4 of 12 players.

Practical Applications

This is the first study to analyze different aspects of technical-tactical training sessions of professional futsal players. Because situational activities are commonly used in futsal training (42), understanding the physiological strain that these activities produce in players can help futsal coaches to select the appropriate activity for technical-tactical development that aligns with the physiological load in each training period. The 3 futsal-specific activities investigated in this study induced players to exercise at a moderate to high intensity most of the time and showed little variation in energy demand and cardiovascular strain, even with different numbers of players involved and different instructions from the coach. Future studies should examine the influence of the exercise duration, intervals, and pitch size of different activities on the exercise intensity and on the motor actions performed.

Another finding obtained in this study for the first time was the difference in the training intensity distribution among players of different positions. This result indicates that although all players participate in the same session, the stress imposed on each athlete can differ; therefore, monitoring of the individual training load is important in futsal. Our results also demonstrate the multifactorial and individual characteristics of the RPE. Although the RPE was not capable of representing the physiological strain measured by the HR, it can be considered an important and practical monitoring tool for training sessions if analyzed on an individual-player basis. The RPE can be particularly valuable during technical-tactical training sessions because the situational activities prescribed by futsal coaches address aspects that can interfere with match performance (physiological, technical, tactical, and psychological demands; 40). Thus, the best approach to monitor the training load in futsal appears to be a combination of different measures (HR and RPE).

Finally, the low levels of body mass loss observed after the training sessions suggest that it is unnecessary to subject futsal athletes to individualized drinking plans. Ad libitum fluid drinking during the training sessions, including free access to water and commercial sport drinks, appears to be sufficient for avoiding dehydration and associated decreases in performance.


This investigation was supported by the National Council for Scientific and Technological Development (CNPq), the Research Support Foundation of the State of Minas Gerais (FAPEMIG), the Coordination for the Improvement of Higher Education Personnel (CAPES), the Office of the Dean for Research of the Federal University of Minas Gerais (Pró-Reitoria de Pesquisa da Universidade Federal de Minas Gerais), FUNDEP/Santander, and the Brazilian Ministry of Sport.


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energy expenditure; situational activity; team sport; training monitoring

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