Shortening Recovery Periods Is a Better Time-Efficient Strategy to Enhance Single and Repeated High-Intensity Efforts Using Elastic Band Exercises with Different Force-Vectors

Abstract

Background: The study aimed to examine recovery time between sets (30 s vs. 2 min) during elastic band training for jumping, sprinting, COD, and repeated high-intensity efforts in young padel players. Methods: Twelve highly trained male padel players were allocated to one of the two groups randomly (short recovery [SRG] or long recovery [LRG]) and evaluated the triple hop test (3HJ), linear (10 m) and multidirectional (5 + 5 m sprint with a direction change of 45°) tests, and the repeated sprint ability (RSA) test after 3 weeks of training intervention. After 3 weeks, there was a 3-week washout period to cross both groups, and the participants then performed the opposite training program. Both groups performed two sets of four exercises, each with six repetitions, with an elastic band, recovering 30 s (SRG) or 2 min between exercises (LRG). Results: No between-training-program differences were established (p < 0.05). SRG showed a better trend in the 3HJ with the right (effect size (ES) = 0.85), while LRG showed small advantages in the 5 m and 10 m sprints (ES = 0.33 to 0.36). SRG also showed small to moderate improvements in COD on both sides (ES = 0.46 to 0.49), although period effects (p < 0.05) indicated the influence of familiarization. In RSA, LRG showed a slight tendency to improve the mean and the best time (ES = 0.24 to 0.41), while SRG showed an advantage in the percentage of decrement (ES = 0.54). Conclusions: SRG appeared more effective in horizontal jumping, COD, and fatigue resistance during the RSA test, whereas LRG may show small advantages in acceleration and RSA performance. Although the effects were mostly small and not statistically significant, the observed trends could have practical relevance for planning specific training programs focused on power, speed, and fatigue resistance in padel players.

1. Introduction

Recently, padel has experienced significant worldwide popularity growth. It is played on a 10 × 20 m synthetic turf court in pairs, surrounded by a structure made of glass walls and metal fences [1]. Several studies have analyzed the effect of tempo-space variables on physical and physiological demands during a game [2,3,4]. The presence of walls and corners on the court affects the type of displacements, such as accelerations, turns, pivots, or changes of direction (COD), mostly through lateral and diagonal movements [5]. Each point is compounded by 8 to 12 explosive efforts [2], lasting each rally of 7.2 ± 8.0 s and 9.1 ± 3.0 s pauses between them [6]. Thus, it seems that performing and repeating explosive efforts during a game might be essential in padel.

Padel is an intermittent sport combining short high-intensity movements (e.g., running, sprinting, jumping, changing direction, etc.) with short recovery times between 10 and 20 s [2]. Interestingly, a repeated power ability (RPA) training (i.e., power training with short recoveries between sets/blocks) seems to be an effective training strategy for improving linear sprinting, changing direction, fatigue resistance during HIA, or power fluctuations in team-sports athletes [7,8]. However, there is a lack of studies investigating the effect of modifying the recovery time between sets on the ability to perform or repeat high-intensity efforts in general.

The use of elastic bands as a training method is rapidly gaining popularity [9]. Their primary advantage lies in their ability to adapt the direction of force application and movement plane, effectively mirroring the dynamic movements essential to various sports [10]. Furthermore, both long (i.e., 2 min) and short recovery times (i.e., 30 s) between sets have been used to improve HIA [11,12]. However, no study has compared different recovery times between sets in an elastic band training program. Therefore, the present study aimed to examine the recovery time between sets (30 s vs. 2 min) through elastic band training on jumping, sprinting, COD, and repeated high-intensity efforts in young padel players. We hypothesize that both training approaches improve HIA and repeated high-intensity efforts, with greater improvements in repeated efforts through a shorter recovery time (30 s).

2. Materials and Methods

2.1. Design

Using a crossover randomized controlled trial, players were randomly (AB/BA) divided into a short recovery group (i.e., 30 s between-sets) (SRG) (n = 6) and a long recovery group (i.e., 2 min between-sets) (LRG) (n = 6) (https://www.randomizer.org/). Participants were informed exclusively about the specific exercises that the training program consisted of and continued performing their habitual tennis training sessions, avoiding lower-body strength training during the study. Firstly, three training weeks were developed, with players randomly allocated to groups A and B (A/B). Thereafter, a three-week washout period was established. This choice was based on previous studies showing that neural adaptations develop over approximately 3 weeks, while their residual effects without neuromuscular or specific training also last approximately 3 weeks [13]. Finally, both groups were crossed (AB/BA) to perform the other training program.

A synthetic grass court was used to execute the physical tests. Before the commencement of the study, a test–retest analysis (

Table 1. Test–retest performance assessments in the full sample (n = 12).

	ICC (95% CI)	CV (95% CI)
Triple Hop R (cm)	0.85 (0.68, 0.91)	2.65 (2.23, 3.59)
Triple Hop L (cm)	0.84 (0.72, 0.96)	2.59 (2.18, 3.49)
5 m (s)	0.73 (0.55, 0.84)	2.91 (2.44, 3.72)
10 m (s)	0.73 (0.55, 0.84)	2.89 (2.37, 3.65)
COD45R (s)	0.92 (0.84, 0.97)	2.11 (1.65, 2.96)
COD45L (s)	0.93 (0.85, 0.97)	2.19 (1.71, 3.08)
RSAb (s)	0.91 (0.84, 0.98)	1.58 (1.24, 2.22)
RSAm (s)	0.89 (0.81, 0.97)	1.87 (1.46, 2.62)
RSAw (s)	0.84 (0.72, 0.96)	2.16 (1.69, 3.03)
%Dec (%)	0.80 (0.68; 0.92)	3.77 (2.95, 5.32)

Abbreviations: ICC: intraclass correlation coefficient; CI: confidence interval; CV: coefficient of variation; Triple Hop R and Triple Hop L: triple jump with the right and left leg; COD45R and COD45L: 10 m sprint (5 + 5 m) with a change of direction of 45° to the right or to the left; RSAb: the best time, RSAm: the mean time, RSAw: the worst time during the repeated sprint ability (RSA) test; %Dec: the percentage of decrement during the RSA test.

) was carried out using the same sample of participants (n = 12) who participated in the study. They were familiarized with all testing procedures. One week and two weeks before the training intervention began, players underwent the same testing battery to evaluate test–retest reliability. Five days after finishing the intervention (after both training periods), the physical fitness tests were repeated to examine the effect of both training interventions. Tests included the triple hop test, linear sprinting test, COD tests (45°), and RSA test. Subjects were required to avoid vigorous exercise on the day before each testing session and to avoid caffeine and meals for at least 3 h before testing.

2.2. Participants

Twelve young male highly trained padel players (age: 15.4 ± 1.3 years; body mass: 60.0 ± 8.8 kg, height: 171.0 ± 10.8 cm; body fat percentage: 12.9 ± 3.2%) of the same elite club voluntarily participated in this study. On average, players performed a combination of 12 h of padel (8 h) and strength (4 h) sessions per week before starting the intervention. Strength and power sessions were avoided during the intervention period (1st phase A/B, washout, and 2nd phase B/A). A minimum of one year of resistance training was required. All players had practiced the exercises used during the intervention. Inclusion criteria were having no injuries (e.g., muscle or bone) in the past 2 months. Players who did not participate in at least 80% of training sessions, did not execute all the assessments, or were absent from any practices or games due to injury were excluded. Two weeks and one week prior to the commencement of the training intervention, players underwent identical assessments to evaluate test–retest reliability. Participants, along with their parents or guardians, were briefed on the study’s procedures, potential risks, and benefits, and both parties provided written informed consent before the investigation began. The protocol received full approval from the ethics committee of *** to ensure blinding prior to recruitment, in accordance with the Declaration of Helsinki (2013).

2.3. Training Intervention

Three training sessions per week were scheduled (Monday, Wednesday, and Friday), always in the morning (8 AM), for a 3-week period. Every session lasted 18–24 min in the SRG and 54–60 min in the LRG. The training program consisted of four exercises: front step, lateral step, lateral crossover step, and frontal deceleration. An elastic band (Sanctband, Super Loop Purple; 4.76 mm thick × 25.4 mm wide × 1000 mm long; 13.61 KGF; Sanct Japan Co., Ltd., Ipoh, Malaysia) was used to carry out all exercises. It was attached to the waist with a belt and anchored to the floor, producing a low vector. Both groups performed two sets of four exercises, each with six repetitions per leg (6 R left and 6 R right). The SRG training consisted of the following exercises in the following order. 1st set: front step, 30 s rest; lateral step, 30 s rest; lateral crossover step, 30 s rest; frontal deceleration, 2 min of passive recovery. 2nd set: front step, 30 s rest; lateral step, 30 s rest; lateral crossover step, 30 s rest; frontal deceleration. The LRG training performed the following exercises in the following order. 1st set: front step, 2 min rest; lateral step, 2 min rest; lateral crossover step, 2 min rest; frontal deceleration, 2 min of passive recovery. 2nd set: front step, 2 min rest; lateral step, 2 min rest; lateral crossover step, 2 min rest; frontal deceleration. A standardized warm-up including lower-body mobility, lunges, deadlifts, skipping, cariocas, jumps, and sprints was developed before each training session. Both concentric and eccentric phases were executed as fast as possible. All players were familiarized with the exercises prior to the commencement of the study to achieve maximum intention. The starting distance (i.e., 1 m from the attaching point) was standardized for all subjects and exercises. All sessions were supervised by the main investigator. Players received similar verbal support in both groups.

2.4. Testing Procedures

Before the testing commenced, all participants engaged in a standard pre-game warm-up routine. This included 10 min of low-intensity jogging, followed by 5 min of dynamic stretches featuring lunges, diver stretches, and lateral squats. The warm-up concluded with 5 min of varied-intensity activities, including cariocas, high-knees, accelerations, butt kicks, decelerations, linear sprints, and sprints on several planes. The testing sequence consisted of the triple hop test, 10 m sprint, 45° change of direction (COD), and a repeated sprint ability (RSA) assessment. For the COD tests, players carried out submaximal trials in each direction (i.e., at around 75% and 90% perceived effort) prior to attempting their maximum valid trials.

2.5. Triple Hop Test

The triple hop test measured distance using a standard measuring tape (i.e., behind a marked line). They flexed and quickly extended the test leg to jump forward three times on the same leg, landing each time on that leg with arms at their sides. After landing, participants held their balance on one leg for 2 to 3 s. Distance was measured in centimeters from the toe position to the heel at landing. Arm swings and movements of the opposite leg were allowed to aid propulsion. Each leg (right and left) was tested three times, with at least 45 s of recovery between trials. Any invalid attempts—such as losing balance or stepping with the opposite leg—were deleted, and new attempts were made until three valid trials were completed. The best value for each leg was recorded for further analysis.

2.6. Speed Test

To evaluate running speed, the 10 m sprint times were recorded along with split times at the 5 m mark. This measurement was conducted using photoelectric cells (Witty, Microgate, Bolzano, Italy). Participants placed their front foot 0.5 m ahead of the first timing gate while adopting a staggered stance with two points. The timing gates were positioned at a height of 0.75 m, ensuring a lateral distance of 1.5 m between the two photocells, forming a single gate. Each athlete undertook the 10 m sprint on three occasions, with 2 min of passive recovery between trials, using the fastest time for analysis.

2.7. 45° Change of Direction Test

Players rested for five minutes passively after the speed test. The 10 m sprint test involved a specific setup where participants first sprinted five meters ahead, then made a 45° turn before accelerating towards the finish line. The test included two sprints—one to the left and another to the right. Participants had to navigate around a pole within a 1.5 m wide rail marked by cones, allowing them to employ either a lateral foot plant or a crossover step as they changed direction. For a trial to be deemed valid, participants had to complete the test within the boundaries of the rail without stepping out of it. Each directional sprint (the first run and those to the left [COD45L] and right [COD45R]) was repeated twice in an alternating order. Photoelectric cells (Witty, Microgate, Bolzano, Italy) were used to record total time. A two-point staggered stance was used with the players’ front foot 0.5 m prior to the first gate. They were set at a height of 0.75 m, with a lateral separation of 1.5 m between the two photocells to form a single gate. After each trial, participants were allowed to rest passively for 2 min. The best time from each direction was employed for statistical analysis [14].

2.8. Repeated Sprint Ability Test

Six maximal 5 + 5 m sprints with a 45° change of direction compounded the repeated sprint ability test (Figure 1) [15]. Participants rested for 20 s between sprints, standing passively. Three seconds before each sprint, they assumed a staggered starting position, with the front foot 0.5 m in front of the first timing gate. Timing was recorded with photoelectric cells (at 0.75 m height and 1.5 m of distance) (Witty, Microgate, Bolzano, Italy), and verbal encouragement was provided throughout. We used the following variables: best sprint time (RSAb), mean sprint time (RSAm), worst sprint time (RSAw), and percentage of decrement (%Dec), calculated as (100 × (mean time/best time)) − 100.

2.9. Statistical Analyses

Data are presented as mean ± standard deviation (SD). The Shapiro–Wilk test was used to assess normality; all data were found to be normally distributed. To assess reliability, initial pairwise comparisons were conducted. The analysis of between-session reliability utilized two methods: (i) a two-way random intraclass correlation coefficient (ICC) that accounted for absolute agreement along with 95% confidence intervals, and (ii) the coefficient of variation (CV). The ICC interpretations were categorized as poor (<0.5), moderate (0.5–0.74), good (0.75–0.9), or excellent (>0.9) (Koo & Li, 2016 [16]). Coefficients of variation were considered acceptable if <10% (Cormack et al., 2008 [17]). A linear mixed model (LMM) was used to analyze changes in a repeated measures crossover design. The subject was included as a random effect to control for intra-individual variability. Fixed effects included treatment (A vs. B), period (first or second phase), treatment sequence, and the treatment × period interaction. The dependent variable was the pre-post difference (Δ) of each variable. Fixed effect estimates (β) and their p-values were reported, with p-values < 0.05 considered significant. The magnitude of the training effect was estimated using the effect size (d), calculated from the difference in estimated marginal means between conditions obtained from the linear mixed model and the residual standard deviation of the same. Given the small sample size, Hedges’ correction for small samples was applied, and effect sizes (ES) were reported along with their 95% confidence intervals. ES were interpreted as follows: trivial (<0.2), small (>0.2–0.5), moderate (>0.5–0.8), large (>0.8–1.2), and very large (>1.2). A sensitivity analysis was performed by removing observations with absolute standardized residuals greater than 2. One outlier was detected in RSAb, RSAw, and %Dec and removed from the analysis. Thereafter, a new analysis was performed, yielding a similar result to before, thus demonstrating robustness in our results (SPSS for Mac, Version 29.0; SPSS Inc., Chicago, IL, USA).

3. Results

The effects of training conditions on performance are shown in

Table 2. Effects of training conditions on performance variables assessed using linear mixed models.

	Change (B–A) (95% CI)	d (95% CI)	p-Value	Period (p)	Sequence (p)
Triple Hop R (cm)	3.85 (−98.3 to 106.0)	0.03 (−0.87 to 0.93)	0.93	NS	NS
Triple Hop L (cm)	19.5 (−1.24 to 40.2)	0.85 (−0.054 to −1.75)	0.06	NS	NS
5 m (s)	−0.18 (−0.065 to 0.029)	−0.33 (−1.19 to 0.53)	0.43	NS	NS
10 m (s)	−0.03 (−0.102 to 0.045)	−0.36 (−1.22 to −0.54)	0.428	NS	NS
COD45R (s)	0.03 (−0.027 to 0.085)	0.46 (−0.43 to 1.35)	0.29	0.01	NS
COD45L (s)	0.03 (−0.019 to 0.073)	0.49 (−0.35 to 1.33)	0.23	0.02	NS
RSAb (s)	−0.02 (−0.103 to 0.061)	−0.24 (−1.15 to 0.68)	0.59	0.014	NS
RSAm (s)	−0.04 (−0.125 to 0.047)	−0.41 (−1.32 to 0.50)	0.356	0.005	NS
RSAw (s)	−0.01 (−0.105 to 0.093)	−0.05 (−0.96 to 0.85)	0.906	NS	NS
%Dec (%)	0.99 (−0.669 to 2.66)	0.54 (−0.36 to 1.44)	0.225	NS	NS

Abbreviations: Triple Hop R and Triple Hop L: triple jump with the right and left leg; COD45R and COD45L: 10 m sprint (5 + 5 m) with a change of direction of 45° to the right or to the left; RSAb, RSAm, and RSAw: the best, mean and worst time during the repeated sprint ability (RSA) test; %Dec: the percentage of decrement during the RSA test. Values are estimated differences between training conditions (B–A) derived from linear mixed models. Effect sizes are expressed as Hedges’ d with 95% confidence intervals. Period and sequence effects were included in the models to account for the crossover design. NS: non-significant (p > 0.05). Positive changes indicate a trend toward improvement in the short recovery group, while negative values indicate a trend toward improvement in the long recovery group.

. No statistically significant differences (p > 0.05) were observed between training interventions for any of the variables analyzed. Period effects (p < 0.05) were observed in the COD tests and in RSAb and RSAm, while no sequence effects (p < 0.05) were detected.

4. Discussion

The main aim of the current study was to assess the effect of recovery time between sets/exercises (30 s vs. 2 min) through elastic band training on jumping, sprinting, COD, and repeated high-intensity efforts in young padel players. The main findings were as follow: (1) despite no significant between-training differences, there was a trend to improve horizontal jumping and COD ability in the SRG, while linear sprinting in LRG, (2) the ability to repeat high-intensity efforts may show different type of improvements as the LRG reported a trend to improve RSA performance, whereas the SRG may help to enhance fatigue resistance (%Dec), and (3) no evidence of carry-over/order effects was detected.

Three weeks of training with long recovery time may impact RSA performance (i.e., RSAm). Although no significant differences were observed between the training conditions, the short recovery time between exercises resulted in a lower effect size. The results of the current study may be similar to those of previous studies using several training strategies with adult and young male racket and team-sports players [7,18,19,20,21,22]. There is only one study with rugby players [22] that used RPA training with superimposed vibrations combined with RSA, which found greater training effects. Previous studies have used high-intensity aerobic training, speed and agility training, RPA training, strength training, or sprint interval training, resulting in lower-magnitude effects. Such differences might be related to the training protocol developed. In this regard, as movement efficiency in the specific direction is necessary to increase displacement performance [23], the exercises performed during our protocol may positively affect RSA performance (i.e., in the same movement plane). Although a training repetition may develop a learning effect [24], as it is also show through the significant effect of period where it may indicate that test practice and familiarization might contribute to the observed improvement, different repeated linear sprints, linear speed/COD, or RPA training protocols, which have used similar sprint distances or times and shuttles as the RSA tests conducted, have achieved lower magnitude improvement. Thus, it seems that adapting the working time during resistance/strength training, applying force in the specific direction, and the recovery time between exercises/sets may be essential to optimizing RSA performance. Beyond varying training modalities, disparities in repeated sprint ability (RSA) among studies may also stem from several other factors. These include the specific sport being analyzed (such as soccer, rugby, padel, tennis, or basketball), the training backgrounds of the athletes (ranging from trained to highly trained), and the frequency of their training sessions (whether they train once, twice, or three times a week). However, as non-significant results were found, caution should be used when interpreting the current effects, which are considered exploratory.

The most interesting finding was the difference in the RSA test depending on the recovery time used between sets/exercises. While the LRG may show a trend of improvement in the RSAb and RSAm, the SRG may as well in the %Dec. However, caution should be exercised, as non-significant effects were reported between the training conditions. As observed in the current study, the average time and best performance in the repeated sprint ability (RSA) test demonstrated comparable enhancements following various training methods [20,25]. Given that the best sprint is a key factor in RSA performance [26], an improvement in the best sprint is expected to lead to a lower average time. However, while the repeated-sprint ability (RSAb) in the short rest group (SRG) may exhibit lower performance than that in the long rest group (LRG), the adaptations in repeated sprint performance observed in this group are likely more associated with improvements in the capacity to sustain initial sprint performance, rather than increases in the initial sprint performance itself. In summary, as the mean time in RSA may be improved through enhancements in either maximal sprinting capacity or recovery between sprints, if you have a deficit in maximal sprinting, you will select a longer recovery time between sets. Meanwhile, if recovery between sets is the deficit, a shorter recovery time should be chosen. Similar interventions to the SRG (i.e., strength training with short recovery times) might be comparable to ours, as the decrement in the average repetition velocity in a set reaching muscle failure [27], the number of repetitions performed above 90% of maximal power [8], and the total work (watts) established during a cycling repeated efforts test [28], were enhanced. The enhanced ability to tolerate fatigue during high-intensity running (i.e., sprints) might be related to changes, among others, in muscle oxidative phenotype, ion homeostasis, and buffering capabilities, which have all been factors associated with enhanced fatigue resistance during high-intensity efforts [11,12].

The current study may show greater improvements in the sprinting of 5 m (ES = 0.33) and 10 m (ES = 0.36) in the LRG than in the SRG. To our knowledge, there are no longitudinal studies on padel players, nor are there assessments of the effects of short recovery times using elastic bands; thus, no direct comparisons are possible. Previous studies using similar recovery times (i.e., random times between 15 s and 35 s) reported improvements similar to those in our study [29], whereas the use of elastic bands during a training program showed a considerably greater effect [30]. The above-mentioned differences might be due to sample differences (male vs. females), the number of weeks (3 vs. 5), the current sprinting performance (2.01 vs. 2.24 s), or the sport (basketball vs. football vs. padel). Notwithstanding, the most interesting point is the low volume used to improve short-sprint performance. Elastic bands are ideal for designing specific stimuli to the force vector and movement plane based on the sports’ motor program requisites [31,32]. Given the importance of horizontal force production in acceleration performance [33], exercises with a high degree of dynamic correspondence might explain the improvements, as the front step with a posteroanterior force vector focuses on such considerations. Furthermore, using elastic bands is associated with a stretch-shortening cycle improvement [34,35], rate of force development, and muscle-tendon stiffness [36]. However, the large CI shows that the improvements are not consistent between subjects and may be due to individual explosive or skill differences. Therefore, it seems that using elastic bands, specifically applying force in the required direction (e.g., horizontal force exercises to improve sprinting ability or rotational force exercises to improve multidirectional ability), may help to increase acceleration performance. However, more studies with padel players are needed to support the previous exploratory analysis.

COD45 showed a trend to increase in the SRG. As in linear sprinting, no direct comparisons are possible as no study has previously assessed the effects of elastic bands on COD45. However, previous studies in different sports using elastic bands have reported heterogeneity adaptations in different COD tests [9,31,37]. When focusing on elastic bands, only two studies (i.e., ours and [31]) address the specific force vector. Several studies have incorporated elastic bands into conventional exercises like squats or deadlifts, which primarily target vertical movement. These adaptations have led to either significant improvements [37] or no noticeable enhancements [9]. It is important to highlight that previous studies may not have replicated the specific force vector, suggesting that adjusting the training load by up to 20% of the athlete’s maximum capacity each week could be a crucial factor in achieving effective training outcomes. Irrespective of the exercises or force vectors used, all studies showed improvements of different magnitudes. The training period (3 weeks vs. 4 weeks), the COD test used (single vs. multiple and curve vs. the multiple COD test), the devices used (elastic bands vs. bars + elastic bands), or the sport might have affected the previous differences. Thus, the force vector seems to affect COD ability adaptations. However, as there was a significant effect on period, these improvements may be due to a learning effect added to training, and thus the results should be considered with caution.

In the present study, the SGR group showed differentiated effects on performance in the horizontal triple jump. The results indicate that the group with less rest time between exercises showed greater improvements, especially in the left leg, although the effects were moderate and not statistically significant. This finding suggests that more frequent stimulation could promote the neuromuscular adaptation necessary to optimize repeated horizontal strength. To date, no studies have specifically evaluated the effect of elastic band training on the horizontal triple jump; thus, these results provide novel evidence on the potential influence of recovery time between exercises on this movement. Although the observed changes are small to moderate in magnitude, they could have practical relevance in sports where unilateral horizontal force is crucial. However, it should be noted that the small sample size and individual variability limit the generalizability of the findings. Therefore, future studies should explore different volumes, intensities, and durations of elastic band training to optimize performance in horizontal jumps.

Some limitations are presented. First, the current study’s underpowered sample necessitates treating it as an exploratory analysis and exercising caution when interpreting the results. Second, a longer training period may have a positive impact on training adaptations. Third, the elastic resistance, or the number of repetitions measured with a force measurement device, can individualize each player’s training/exercise load. Fourth, the lack of neuromuscular or metabolic markers to support mechanistic interpretations. Finally, no biological maturation indicators were included. As all participants were adolescents, this represents a limitation, as maturation can affect adaptations in speed, power, or fatigue resistance. Future research should investigate the effect of elastic band training with short recovery periods in conjunction with other strength training protocols (e.g., resistance training, flywheel training, or combined training). Additionally, it could examine the combination of elastic bands with resisted sprinting and unresisted sprints, or analyze its effects on subjects of different ages, genders, or sports.

5. Conclusions

Short recovery group showed a trend of improvement in repeated jumping and multidirectional abilities, while the long recovery group showed a positive trend in linear sprinting. Furthermore, the ability to repeat high-intensity efforts in young padel players may be developed through potentially different performance pathways (fatigue resistance vs. maximal sprint capacity). Based on the time used to develop each training program, SRG may be used as a time-efficient alternative strategy (three times less time). Furthermore, as elastic bands can be easily moved and attached anywhere (padel or tennis circuit is played worldwide, and time to practice at “home” is null), they may be recommended for young padel players as essential tools, as they help improve explosive performance and repetition. Lastly, adapting these movements to the same movements with the racket and balls can facilitate their incorporation into real practice and situations similar to those encountered during games.