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ABSTRACT
ABSTRACT
Literature is scarce on how players with poorly and well developed physical qualities respond to different combinations of strength-power training during in-season. The aim of this study was to investigate the effects of (i) compound training performed by stronger athletes at different days and (ii) complex training performed by weaker athletes within the same training session. Twenty male handball players were classified as strong or weak according to countermovement jump performance and assigned to a 12-week training programme. Linear sprint, changes of direction, repeated sprint ability and vertical jump capacity were used to assess physical profiles. Compound training performed by stronger players resulted in unclear effects on vertical jump, 20-m and repeated sprint. Likely improvements were found in 10-m sprint (−11.3%; 11.9%). Weaker players who performed complex training presented likely and very likely improvements on vertical jump (13.7%; 5.4%), sprint (10 m, −10.7%; 10.3%; 20 m, −6.0%; 3.4%) and repeated sprint (−4.1%; 3.7%) with moderate to large effect size. The results show that complex and compound strategies are useful in improving the physical profiles of weaker players and maintaining stronger players’ capacities during in-season, respectively. Players involved in the same competitive context, even from the same team, may require different strength training strategies.
Introduction
Team sports performance is influenced by a complex, adaptive and dynamic process requiring players to constantly manage the disorder and respond to emergent situations of cooperation and opposition (Clemente, Figueiredo, Martins, Mendes, & Wong, 2016). Additionally, players are required to perform short-term high-intensity actions such as repeated accelerations and changes of directions (Romaratezabala, Nakamura, Castillo, Gorostegi-Anduaga, & Yanci, 2018), sprints and jumps (Trecroci, Longo, Perri, Iaia, & Alberti, 2019). Successful motor performances rely on well-developed muscular strength, which demands for specific strength training with high-intensity external loads to induce significant neuromuscular adaptations (Weiss, Coney, & Clark, 2003). These demands require efficient and accurate strength training periodization models in order to develop strength endurance, coordination, explosive strength and speed within the annual training cycle (Issurin, 2010).
Research focused on seasonal variations in physical fitness in team sports suggests that power training and high-volume training are important drivers to improve anaerobic and aerobic fitness during preseason, respectively (Meckel, Doron, Eliakim, & Eliakim, 2018). However, as the in-season period is typically characterized by load and well-being variations between normal and congested weeks (Clemente et al., 2019), training loads prescription should be regulated by performance-related indicators such as circannual rhythm, nutritional needs (Lombardi et al., 2017), physical/neuromuscular and physiological profiles (Oliveira, Abade, Goncalves, Gomes, & Sampaio, 2014) and playing position characteristics (Vitale et al., 2018). Under the scope of strength training, coaches usually prescribe undulating non-linear periodization models to maintain players close to their peak throughout the regular season (Haff & Triplett, 2015). The main purpose of this approach is to promote variations in training loads within each microcycle to allow a concurrent account for multiple training goals, which has been shown to be effective in increasing both upper and lower body strength in trained subjects (Monteiro et al., 2009). The effect of training frequency on muscular strength gains appears to be primarily driven by training volume, which means that greater training frequency is likely to result in greater muscular strength gains (Grgic et al., 2018). However, determining an optimum range of training frequency should consider players’ training status, exercise selection, projected training load and other concurrent training (Haff & Triplett, 2015) to allow players to train according to individual needs and/or calendar constraints (Gamble, 2010).
Neuromuscular strength and power adaptations are extremely important to optimize the force–velocity relationship and increase muscle power output (Cormie, McGuigan, & Newton, 2011). For that reason, combining general strength training with specific power exercises such as plyometrics is a common practice among team sports coaches when aiming to optimize the players’ performance during the in-season period (Carvalho, Mourao, & Abade, 2014). In fact, previous research showed that combining strength and power training may be a more efficient strategy to improve muscular power when compared to strength or power training alone (Ebben, 2002). This combination can be achieved by performing compound or complex strength training models. Compound training is characterized by strength (high loads and high velocity) and power training (low loads and high velocity) sessions performed on different days (Mihalik, Libby, Battaglini, & McMurray, 2008). This method seems to be a time-efficient strategy to promote increases in contractile proteins and improve stretch reflex of a muscle (Kotzamanidis, Chatzopoulos, Michailidis, Papaiakovou, & Patikas, 2005; Mihalik et al., 2008) and improve power production at short-term (Mihalik et al., 2008).
On the other hand, complex method includes strength and power exercises performed in pairs within the same training session (Ebben, 2002). Complex training is supported by the idea that performing a maximal or near maximal muscle contraction – conditioning activity – may increase power production in the subsequent exercise, a mechanism described as post-activation potentiation (Parry et al., 2008; Seitz & Haff, 2016).
The majority of the studies focused on combined strength-power training are based on short-term programmes performed with non-athletes’ population and do not consider all the time and calendar constraints inherent to an in-season team sports period. Additionally, recent literature indicates that post-activation potentiation effects are higher among stronger individuals and those with more resistance training experience, particularly under complex training scenarios (Seitz & Haff, 2016) and that weaker players with poorly developed physical qualities are more vulnerable to injury when spikes in workloads occur (Gabbett, 2018). However, it is unknown how stronger and weaker individuals respond to different combinations of strength-power training during congested in-season periods in team sports.
The aim of this study was to investigate the effects of a 12-week combined strength-power training programme applied during handball in-season period under two different contexts: (i) compound strength-power performed by stronger athletes at different days and (ii) complex strength-power performed by weaker athletes within the same training session. It was hypothesized that both stronger and weaker players would improve physical profiles as the result of the compound and complex strength-power training, respectively.
Material and methods
Subjects
Twenty semi-professional male handball players (age: 24.7 ± 3.8 years old; stature: 182.2 ± 6.2 cm; body mass: 83.6 ± 5.8 kg; playing experience: 12.2 ± 1.8 years) from the same team competing in the Portuguese 2nd national league participated in this study. Players were assigned to a Compound Strength Training group (n = 10) or Complex Strength Training group (n = 10) using baseline CMJ results, as described in procedures. The study was conducted during the in-season period with players performing 5 training units per week (~90 minutes per session) with official matches every weekend. Players were free to withdraw from the study at any time without any penalty. Players with existing injuries at the beginning of the study were excluded. Written informed consent was obtained from all participants. The investigation was approved by the local Institutional Research Ethics Committee (PEst-OE/SAU/UI4045/2019) and conformed to the recommendations of the 1964 Declaration of Helsinki.
Design
To investigate the effects of compound and complex training, male handball players participated in a 12-week training program applied during in-season under two different contexts: compound training performed by stronger athletes at different days and complex training performed by weaker athletes within the same training session (Figure 1). Physical profiles were assessed one week before and after the training period. Particularly, measurements included linear sprint capacity (Sprint, 10 m and 20 m), changes of direction (COD, 6 × 20 m) and repeated sprint ability (RSA, 6 × 20 m). Vertical jump capacity was assessed with Countermovement Jump (CMJ), Abalakov Jump (AJ) and Throw Jump (TJ) tests. Even though complex training designs appear to enhance stronger and experienced athletes muscle strength to a greater extent, it is unknown how stronger and weaker individuals respond to different combinations of strength-power training during congested in-season periods in team sports. As weaker players with impaired lower body strength are more vulnerable to injury when spikes in workloads occur, players were classified as stronger and weaker using baseline CMJ results and allocated to Compound Strength Training group or Complex Strength Training group, respectively. Strength training was performed two times per week for 12 weeks, with compound group training in separate days and complex group within the same training session. Both groups performed the same number of exercises and repetitions at the same relative intensities. Training program included horizontal leg press, bench press and 90º half back squat exercises.
Published online:
05 December 2019Figure 1. Schematic representation of the experimental design. All players performed strength training two times per week during 12 weeks. Stronger players performed strength and power in separate days (compound group) and weaker players performed strength and power within the same training session (complex group). Both groups performed the same number of exercises and repetitions at the same relative intensities.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/gspm20/2020/gspm20.v028.i03/15438627.2019.1697927/20200706/images/medium/gspm_a_1697927_f0001_b.gif"})
Figure 1. Schematic representation of the experimental design. All players performed strength training two times per week during 12 weeks. Stronger players performed strength and power in separate days (compound group) and weaker players performed strength and power within the same training session (complex group). Both groups performed the same number of exercises and repetitions at the same relative intensities.
Testing
Pre-test measurements included vertical jump tests (CMJ, AJ and TJ), linear sprint capacity (10 m and 20 m), COD (6 × 20 m) and RSA (6 × 20 m). A 10-minutes recovery period was allowed between tests.
In the 10 m and 20 m linear sprint tests, participants were asked to start from a standing position with the front foot at 50 cm from the photocells and to run as fast as possible, just decelerating after crossing the end point. Subjects performed 2 maximal attempts at each sprint test with the best result being registered for analysis. In RSA test, participants performed 6 × 20 m sprints with 10 seconds of passive recovery. In COD test, participants were asked to perform a 6 × 20 m sprint (7.5 m + 5 m + 7.5 m) with two 90°changes of direction at 7.5 m and 12.5 m. The 90° angle was used because it requires handball players to adapt sideways leaning posture in an effort to apply enough lateral force to the ground to successfully change direction at high speeds (Buchheit, Haydar, & Ahmaidi, 2012). A 10-seconds passive recovery was allowed in-between repetitions in order to represent the incomplete recovery pattern of repeated high-intensity actions in the sport (Oliveira et al., 2014). An infrared ray photocell system (Globus Ergo Timer, Italy) was used to record time (seconds) in all sprint tests.
Weaker players with lower body strength are more vulnerable to injury when spikes in workloads occur. Under this scope, as vertical jump is recognized as a useful index of the muscular ability to generate power and an important predictor of functional ability of lower limbs under different conditions (Quagliarella, Sasanelli, Belgiovine, Moretti, & Moretti, 2010), CMJ baseline values were used to allocate players into the Stronger (i.e. S-compound, higher CMJ values) and into the Weaker group (i.e. W-complex, lower CMJ values). This evaluation was performed one week before the beginning of the study. CMJ and AJ were assessed according to the Bosco protocol (Bosco, Luhtanen, & Komi, 1983). In TJ test, subjects were asked to start from a standing position with the ball and to accomplish two in run steps before jump off with one leg as high as possible, releasing the ball at the highest point. All vertical jump tests were performed with an Optojump device (Microgate, Italy). Subjects performed 2 maximal attempts at each VJ exercise with the best result being registered for analysis.
One maximum repetition was used to assess muscular strength of the participants (Seo et al., 2012), measured prior to the beginning of the training program and re-assessed at weeks 4 and 8. Thus, training loads (%RM) were accurately adjusted during the course of the training program, following previous literature guidelines (Haff & Triplett, 2015). First, the player was instructed to perform a light resistance warm-up from 10 to 12 repetitions in the assessed exercise. Then, a 1-minute rest was allowed. A warm-up load was added to allow the athlete to complete 3 to 5 repetitions (5% to 10% for bench press and 10% to 20% for leg press and back squat). A 2-minute rest time was provided. Again, a 5% to 10% increase in the load was performed for bench press and 10% to 20% for leg press and back squat. A 4-minute rest time was provided. The load was again increased for the athlete to attempt one maximum repetition. The load continued to be increased or decreased until the player completed one repetition with proper exercise technique. In both leg press and squat exercises, participants were asked to perform a thigh-knee 90° angle range of motion. In bench-press, also an arm-forearm 90° range of motion was defined as the final moment of the eccentric phase.
Training
Strength training was performed two times per week (separated by 48 h) for 12 weeks. The S-compound group performed strength and power training in alternate days, whereas the W-complex performed strength and power training in the same training session. Compound and Complex training methods were designed according to previous guidelines suggested in the literature under this particular scope (Stasinaki et al., 2015). S-compound performed 4 × 6 repetitions at 80% 1RM on a strength day and 4 × 8 repetitions at 30% 1RM on a power training day. Both strength and power sessions were performed with a maximum speed concentric phase without repetition failure (Davies, Orr, Halaki, & Hackett, 2016), with rest intervals of 3–5 minutes between sets. The W-complex performed 2 × 6 repetitions at 80% 1RM and 2 × 8 repetitions at 30% 1RM in paired exercises with 3-minute interval between complex pairs and 5 minutes between exercises. Training volume was equated as both groups performed the same number of exercises and repetitions at the same relative intensities. Training program included the horizontal leg press, bench press and 90º half back squat exercises. In W-complex, paired exercises only differed in the % load used (i.e. 90º half squat 80%1RM + 90º half squat 30%1RM; bench press 80%1RM + bench press 30%1RM and 90º leg press 80%1RM + 90º leg press 30%1RM).
Statistical analysis
To identify the effects of strength training intervention to both Compound and Complex groups, data were analysed with a specific spreadsheet for a post-only crossover (Hopkins, 2006). The effects were estimated in per cent units through log-transformation to reduce the non-uniformity of error and uncertainty in the estimate was expressed as 90% confidence limits. The outcome for performance measures was evaluated with the non-clinical version of magnitude-based inferences. Quantitative chances of impairment or improvement performance effect were assessed qualitatively and reported using the following scale: 25–75%, possibly; 75–95%, likely; 95–99.5%, very likely; >99.5%, most likely. If the chance of having an impairment or improvement performances were both >5%, the true difference was assessed as unclear (W. G. Hopkins, Marshall, Batterham, & Hanin, 2009). Standardized (Cohen) mean differences, and respective 90% confidence intervals were also computed as the magnitude of observed effects, and, thresholds were 0.2, trivial; 0.6, small; 1.2, moderate; 2.0, large; and >2.0, very large (Hopkins et al., 2009).
Results
Table 1 presents the descriptive and probabilistic statistics and Figure 2 includes the standardized differences for the pre- to post-test performance measures’ variations in S-compound. A possible performance impairment (−2.7%; ±4.1%: mean changes, %; ±90% confidante limits) was observed in AJ after strength training intervention program (small effect). The TJ followed the same trend since the intervention promoted a likely impairment (−8.1%; ±6.2%, small effect). Regarding linear sprint tests, a likely improvement was shown in the 10 m sprint (−11.3%; ±11.9% decrease in time, moderate effect). Although the 20 m sprint performance presented unclear results, 72% of the chances presented an improvement. Finally, the COD test showed a possible impairment (small effect).
Table 1. Inferences for the pre- to post-test performance measures’ variations in compound strength training group.
Published online:
05 December 2019Figure 2. Standardized Cohen’s differences for the pre- to post-test performance measures’ variations in compound strength training groups. Error bars indicate uncertainty in true mean changes with 90% confidence intervals. Note that for the sprint performance testes (sprint duration), higher values mean lower performance. Abbreviations: T = trivial; S = small; M = moderate; L = large; VL = very large.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/gspm20/2020/gspm20.v028.i03/15438627.2019.1697927/20200706/images/medium/gspm_a_1697927_f0002_b.gif"})
Figure 2. Standardized Cohen’s differences for the pre- to post-test performance measures’ variations in compound strength training groups. Error bars indicate uncertainty in true mean changes with 90% confidence intervals. Note that for the sprint performance testes (sprint duration), higher values mean lower performance. Abbreviations: T = trivial; S = small; M = moderate; L = large; VL = very large.
Table 2 presents the descriptive and probabilistic statistics and Figure 3 includes the standardized differences for the pre- to post-test performance measures’ variations in W-complex. The CMJ presented a most likely improvement (13.7%; 5.4%, moderate effect) after strength training intervention and a very likely improvement in both AJ and TJ (6.8%; ±4.9% and 14.8%; ±8.4%, respectively, both moderate effects). This group effectively improved the performance in both 10- and 20 m sprint (−10.7%; ±10.3% and −6.0%; ±3.4% variation from pre- to post-test, respectively, with a moderate/large effect) and the RSA presented a likely decrease in the test time (−4.1%; ±3.7%), that corresponded to a moderate improvement. Unclear results were observed to COD test protocol.
Table 2. Inferences for the pre- to post-test performance measures’ variations in complex strength training group.
Published online:
05 December 2019Figure 3. Standardized Cohen’s differences for the pre- to post-test performance measures’ variations in complex strength training groups. Error bars indicate uncertainty in true mean changes with 90% confidence intervals. Note that for the sprint performance testes (sprint duration), higher values mean lower performance. Abbreviations: T = trivial; S = small; M = moderate; L = large; VL = very large.
![]({"type":"image","src":"/na101/home/literatum/publisher/tandf/journals/content/gspm20/2020/gspm20.v028.i03/15438627.2019.1697927/20200706/images/medium/gspm_a_1697927_f0003_b.gif"})
Figure 3. Standardized Cohen’s differences for the pre- to post-test performance measures’ variations in complex strength training groups. Error bars indicate uncertainty in true mean changes with 90% confidence intervals. Note that for the sprint performance testes (sprint duration), higher values mean lower performance. Abbreviations: T = trivial; S = small; M = moderate; L = large; VL = very large.
Discussion
This is the first study to explore the effects of a combined strength-power training program applied during a team sports’ in-season period under two different contexts: stronger players performing compound strength-power training and weaker players performing complex strength-power training. Generally, no remarkable effects were observed for stronger players who performed the compound training program. However, the results show that weaker players experienced significant improvements in physical profiles during in-season periods when performing complex strength training. As this period is influenced by calendar constraints, coaches typically choose to adopt non-linear periodization models with variations in training loads. Under this scope, research shows that weaker players with lower body strength are more vulnerable to injury when spikes in workloads occur (Gabbett, 2018). The results of the present investigation represent new and very important insights into the strength training periodization literature and real-world scenarios that helps coaches to address specific and individual needs according to the players’ timeframe and magnitude responses to training (Gamble, 2013).
W-complex program resulted in a very likely/most likely positive effect on CMJ, AJ and TJ performances and in a likely/very likely positive effect on linear sprint and repeated sprint ability. These results support the idea that strength training involving heavy resistance exercises coupled with biomechanically similar power exercises on the same session is effective in increasing neuromuscular performance (Ebben, 2002), even in weaker and inexperienced players with poorly developed physical qualities. The present investigation findings are also in accordance to previous research that showed that when heavy resistance exercises and power exercises are combined set for set in the same training session, significant improvements may be observed in vertical and horizontal force-oriented tasks such as sprinting and jumping performances (Docherty, Robbins, & Hodgson, 2004).
The physiological mechanisms underlying the post-activation potentiation effects appear to be related to the motor-neurons excitability resultant from a pre-conditioning high-intensity activity (Matthews, Matthews, & Snook, 2004) and an increase in the synchronization and number of motor units recruited (Sale, 2004). Under this scope, the literature suggests that stronger individuals are able to experience higher acute potentiation effects than weaker ones (Seitz & Haff, 2016). Apparently, this may be due to the fact that stronger athletes experience greater potentiation effects earlier after high-intensity conditioning activities (Seitz, de Villarreal, & Haff, 2014). However, this study showed that when repeated post-activation potentiation effects are experienced over time (i.e. chronic effect), weaker athletes also benefit from this training method, even during in-season. These remarkable findings may be explained by the fact that responses to a strength-power potentiation complex are highly individual (Seitz & Haff, 2016). More importantly, it seems that weaker athletes are able to increase the capacity to dissipate fatigue after high-intensity exercises over time, which may potentiate the chronic effect of the complex strength training approach in explosive performances, as reflected by the improvements in sprinting and jumping capacities in the present investigation.
Generally, the effects of compound training program in the sprint and jump performances of stronger players were unclear in this investigation. Previous reports have shown that compound training is as effective as complex training for improving lower body power output (Mihalik et al., 2008), while others showed that compound training is more effective for improving explosive muscle performance (Stasinaki et al., 2015). However, these investigations were only focused on short-term effects (4 to 6-weeks) in non-elite individuals and were not performed during in-season, which is the most challenge period for coaches and athletes to maintain or improve physical profiles. The present non-significant improvements in strong athletes should not be interpreted as a negative outcome of the present investigation. In fact, one of the hardest challenges in in-season period is to efficiently couple strength and training field sessions in order to avoid fatigue and performance impairments (Abade, Abrantes, Ibáñez, & Sampaio, 2014). This study shows that compound strength training is a very interesting periodization strategy that helps to maintain high-level physical profiles during the in-season period.
Moreover, it was not expected to find significant improvements in players with already high-level physical profiles, particularly during in-season period where the need to recover and regenerate after multiple stress stimuli is constant (Ekstrand, Hagglund, & Walden, 2011). Generally, this investigation shows that both complex and compound strategies are useful in improving the physical profiles of weaker players and maintaining stronger players’ capacities during in-season periods.
Conclusion
The results of the present investigation reinforce the importance of adopting strength and power training combinations under non-linear periodization strategies. According to the main outcomes, complex and compound strategies represent useful strategies to improve physical profiles of weaker players and maintaining stronger players’ physical profiles during in-season, respectively. Additionally, it is highlighted the need to adjust these strategies in accordance to players’ individual training load experience and specific needs. In real-world scenarios, coaches should be aware that players involved in the same competitive context, even in the same team, may have different training loads experience and may require different strength training strategies aiming to enhance their physical profiles. As this study was performed during an in-season real world, intervention on the training process was limited.
Table 1. Inferences for the pre- to post-test performance measures’ variations in compound strength training group.
| Variables | Compound strength training group | ||||
|---|---|---|---|---|---|
| Pre-test mean±SD | Post-test mean±SD | Mean changes %; ±90% CL | Practical inferences | Impairment/trivial /improvement | |
| Countermovement Jump CMJ | 36.2 ± 5.6 | 36.6 ± 5.6 | 1.0; ±5.3 | unclear | 10/63/26 |
| Abalakov Jump AJ | 46.03 ± 4.65 | 44.78 ± 4.78 | −2.7; 4.1 | possibly | 64/32/4 |
| Throw Jump TJ | 47.2 ± 7.9 | 43.5 ± 8.1 | −8.1; ±6.2 | likely | 89/10/1 |
| Linear sprint 10 m | 1.85 ± 0.09 | 1.65 ± 0.21 | −11.3; ±11.9 | likely | 4/5/90 |
| Linear sprint 20 m | 2.99 ± 0.14 | 2.93 ± 0.19 | −2.2; ±3.6 | unclear | 6/22/72 |
| Repeated sprint ability RSA, 6 × 20 m | 3.21 ± 0.12 | 3.18 ± 0.20 | −0.9; ±2.8 | unclear | 11/44/45 |
| Changes of direction sprint COD, 6 × 20 m | 4.69 ± 0.35 | 4.76 ± 0.41 | 1.6; ±2.3 | possibly | 53/45/2 |
Table 2. Inferences for the pre- to post-test performance measures’ variations in complex strength training group.
| Variables | Complex strength training group | ||||
|---|---|---|---|---|---|
| Pre-test mean±SD | Post-test mean±SD | Mean changes %; ±90% CL | Practical inferences | Impairment/trivial/improvement | |
| Countermovement Jump CMJ | 27.24 ± 2.89 | 31.02 ± 3.84 | 13.7; 5.4 | Most likely | 0/0/100 |
| Abalakov Jump AJ | 36.7 ± 3.8 | 39.1 ± 3.7 | 6.8; ±4.9 | Very likely | 0/4/95 |
| Throw Jump TJ | 35.0 ± 5.9 | 39.9 ± 5.2 | 14.8; ±8.4 | Very likely | 0/1/99 |
| Linear sprint 10 m | 1.86 ± 0.10 | 1.69 ± 0.29 | −10.7; ±10.3 | Likely | 3/8/89 |
| Linear sprint 20 m | 3.16 ± 0.11 | 2.97 ± 0.12 | −6.0; ±3.4 | Very likely | 0/1/99 |
| Repeated sprint ability RSA, 6 × 20 m | 3.40 ± 0.21 | 3.26 ± 0.16 | −4.1; ±3.7 | Likely | 2/7/91 |
| Changes of direction sprint COD, 6 × 20 m | 4.87 ± 0.26 | 4.93 ± 0.35 | −1.9; ±4.0 | Unclear | 8/38/54 |
Disclosure statement
No potential conflict of interest was reported by the authors.
References
- Abade, E. , Abrantes, C. , Ibáñez, S. , & Sampaio, J. (2014). Acute effects of strength training in the physiological and perceptual response in handball small-sided games. Science & Sports , 29(5), 83–89. [Crossref], [Google Scholar]
- Bosco, C. , Luhtanen, P. , & Komi, P. V. (1983). A simple method for measurement of mechanical power in jumping. European Journal of Applied Physiology and Occupational Physiology , 50(2), 273–282. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Buchheit, M. , Haydar, B. , & Ahmaidi, S. (2012). Repeated sprints with directional changes: Do angles matter? Journal of Sports Sciences , 30(6), 555–562. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Carvalho, A. , Mourao, P. , & Abade, E. (2014). Effects of strength training combined with specific plyometric exercises on body composition, vertical jump height and lower limb strength development in elite male handball players: A case study. Journal of Human Kinetics , 41(1), 125–132. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Clemente, F. M. , Figueiredo, A. , Martins, F. , Mendes, R. , & Wong, D. P. (2016). Physical and technical performances are not associated with tactical prominence in U14 soccer matches. Research in Sports Medicine , 24(4), 352–362. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Clemente, F. M. , Oliveira, H. , Vaz, T. , Carrico, S. , Calvete, F. , & Mendes, B. (2019). Variations of perceived load and well-being between normal and congested weeks in elite case study handball team. Research in Sports Medicine , 27(3), 412–423. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Cormie, P. , McGuigan, M. R. , & Newton, R. U. (2011). Developing maximal neuromuscular power part 1-biological basis of maximal power production. Sports Medicine , 41(1), 17–38. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Davies, T. , Orr, R. , Halaki, M. , & Hackett, D. (2016). Effect of training leading to repetition failure on muscular strength: A systematic review and meta-analysis (vol 46, pg 487, 2016). Sports Medicine , 46(4), 605–610. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Docherty, D. , Robbins, D. , & Hodgson, M. (2004). Complex training revisited: A review of its current status as a viable training approach. Strength and Conditioning Journal , 26(6), 52–57. [Web of Science ®], [Google Scholar]
- Ebben, W. P. (2002). Complex training: A brief review. Journal of Sports Science and Medicine , 1, 42–46. [PubMed], [Google Scholar]
- Ekstrand, J. , Hagglund, M. , & Walden, M. (2011). Injury incidence and injury patterns in professional football: The UEFA injury study. British Journal of Sports Medicine , 45(7), 553–558. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Gabbett, T. J. (2018). Debunking the myths about training load, injury and performance: Empirical evidence, hot topics and recommendations for practitioners. British Journal of Sports Medicine . https://bjsm.bmj.com/content/early/2018/10/26/bjsports-2018-099784 [Crossref], [Web of Science ®], [Google Scholar]
- Gamble, P. (2010). Strength and conditioning for team sports: Sport-specific physical preparation for high performance . New York: Routledge. [Google Scholar]
- Gamble, P. (2013). Planning and scheduling Strength and conditioning for team sports: Sport-specific physical preparation for high performance (pp. 204–220). London: Routledge. [Crossref], [Google Scholar]
- Grgic, J. , Schoenfeld, B. J. , Davies, T. B. , Lazinica, B. , Krieger, J. W. , & Pedisic, Z. (2018). Effect of resistance training frequency on gains in muscular strength: A systematic review and meta-analysis. Sports Medicine , 48(5), 1207–1220. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Haff, G. G. , & Triplett, N. T. (2015). Program design for resistance training essentials of strength training and conditioning (4th ed., pp. 439–471). Champaign, IL: Human kinetics. [Google Scholar]
- Hopkins, W. G. (2006). Spreadsheets for analysis of controlled trials, with adjustment for a subject characteristic. Sportscience , 10, 46–50. [Google Scholar]
- Hopkins, W. G. , Marshall, S. W. , Batterham, A. M. , & Hanin, J. (2009). Progressive statistics for studies in sports medicine and exercise science. Medicine and Science in Sports and Exercise , 41(1), 3–12. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Issurin, V. (2010). New horizons for the methodology and physiology of training periodization block periodization: New horizon or a false dawn? Reply. Sports Medicine , 40(9), 805–807. [Crossref], [Web of Science ®], [Google Scholar]
- Kotzamanidis, C. , Chatzopoulos, D. , Michailidis, C. , Papaiakovou, G. , & Patikas, D. (2005). The effect of a combined high-intensity strength and speed training program on the running and jumping ability of soccer players. Journal of Strength and Conditioning Research , 19(2), 369–375. [PubMed], [Web of Science ®], [Google Scholar]
- Lombardi, G. , Vitale, J. A. , Logoluso, S. , Logoluso, G. , Cocco, N. , Cocco, G. , … Banfi, G. (2017). Circannual rhythm of plasmatic vitamin D levels and the association with markers of psychophysical stress in a cohort of Italian professional soccer players. Chronobiology International , 34(4), 471–479. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Matthews, M. , Matthews, H. , & Snook, B. (2004). The acute effects of a resistance training warmup on sprint performance. Research in Sports Medicine , 12(2), 151–159. [Taylor & Francis Online], [Google Scholar]
- Meckel, Y. , Doron, O. , Eliakim, E. , & Eliakim, A. (2018). Seasonal variations in physical fitness and performance indices of elite soccer players. Sports , 6(1), 14. [Crossref], [Web of Science ®], [Google Scholar]
- Mihalik, J. P. , Libby, J. J. , Battaglini, C. L. , & McMurray, R. G. (2008). Comparing short-term complex and compound training programs on vertical jump height and power output. Journal of Strength and Conditioning Research , 22(1), 47–53. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Monteiro, A. G. , Aoki, M. S. , Evangelista, A. L. , Alveno, D. A. , Monteiro, G. A. , Picarro, I. D. , & Ugrinowitsch, C. (2009). Nonlinear periodization maximizes strength gains in split resistance training routines. Journal of Strength and Conditioning Research , 23(4), 1321–1326. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Oliveira, T. , Abade, E. , Goncalves, B. , Gomes, I. , & Sampaio, J. (2014). Physical and physiological profiles of youth elite handball players during training sessions and friendly matches according to playing positions. International Journal of Performance Analysis in Sport , 14(1), 162–173. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Parry, S. , Hancock, S. , Shiells, M. , Passfield, L. , Davies, B. , & Baker, J. (2008). Physiological effects of two different postactivation potentiation training loads on power profiles generated during high intensity cycle ergometer exercise. Research in Sports Medicine , 16(1), 56–67. [Taylor & Francis Online], [Google Scholar]
- Quagliarella, L. , Sasanelli, N. , Belgiovine, G. , Moretti, L. , & Moretti, B. (2010). Evaluation of standing vertical jump by ankles acceleration measurement. Journal of Strength and Conditioning Research , 24(5), 1229–1236. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Romaratezabala, E. , Nakamura, F. , Castillo, D. , Gorostegi-Anduaga, I. , & Yanci, J. (2018). Influence of warm-up duration on physical performance and psychological perceptions in handball players. Research in Sports Medicine , 26(2), 230–243. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Sale, D. (2004). Postactivation potentiation: Role in performance. British Journal of Sports Medicine , 38(4), 386–387. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Seitz, L. B. , de Villarreal, E. S. , & Haff, G. G. (2014). The temporal profile of postactivation potentiation is related to strength level. Journal of Strength and Conditioning Research , 28(3), 706–715. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Seitz, L. B. , & Haff, G. G. (2016). Factors modulating post-activation potentiation of jump, sprint, throw, and upper-body ballistic performances: A systematic review with meta-analysis. Sports Medicine , 46(2), 231–240. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Seo, D. I. , Kim, E. , Fahs, C. A. , Rossow, L. , Young, K. , Ferguson, S. L. , … So, W. Y. (2012). Reliability of the one-repetition maximum test based on muscle group and gender. Journal of Sports Science and Medicine , 11(2), 221–225. [PubMed], [Web of Science ®], [Google Scholar]
- Stasinaki, A. N. , Gloumis, G. , Spengos, K. , Blazevich, A. J. , Zaras, N. , Georgiadis, G. , … Terzis, G. (2015). Muscle strength, power, and morphologic adaptations after 6 weeks of compound vs. complex training in healthy men. Journal of Strength and Conditioning Research , 29(9), 2559–2569. [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
- Trecroci, A. , Longo, S. , Perri, E. , Iaia, F. M. , & Alberti, G. (2019). Field-based physical performance of elite and sub-elite middle-adolescent soccer players. Research in Sports Medicine , 27(1), 60–71. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Vitale, J. A. , Povia, V. , Vitale, N. D. , Bassani, T. , Lombardi, G. , Giacomelli, L. , … La Torre, A. (2018). The effect of two different speed endurance training protocols on a multiple shuttle run performance in young elite male soccer players. Research in Sports Medicine , 26(4), 436–449. [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
- Weiss, L. W. , Coney, H. , & Clark, F. (2003). Optimal post-training abstinence for maximal strength expression. Research in Sports Medicine , 11(3), 145–155. [Taylor & Francis Online], [Google Scholar]
