Muscular power output is critical in the development of athletic performance (Cronin & Sleivert, 2005). As power output is the product of force output and movement velocity, it is vital to understand the training practices that develop force output (i.e. muscular strength) and movement velocity (e.g. rate of force development). A common and effective method to enhance force and velocity characteristics of muscular power is through resistance training (Cormie, McGuigan, & Newton, 2011). Resistance training (including Olympic lifts and their derivatives) have been shown to lead to increases in power output in athletic populations (Baker & Newton, 2006; Hackett, Davies, Soomro, & Halaki, 2016). Among other useful types of resistance training to improve power output such as complex training (Baker, 2003), plyometric training (Adams, O’Shea, O’Shea, & Climstein, 1992) and velocity-based training (Mann, Ivey, & Sayers, 2015); the alteration of set-structure has garnered a high volume of attention in the field and research contexts, collectively known as ‘cluster-set structures’ (Haff, Burgess, & Stone, 2008a; Haff et al., 2003). Briefly, a cluster-set structure involves the completion of a set of resistance training with the inclusion of pre-planned rest intervals (i.e. intra-set rest intervals or, if within individual repetitions, inter-repetition rest intervals) followed by traditional inter-set rest periods (Tufano, Brown, & Haff, 2017). The appropriate addition of short rest periods within a set theoretically allows the performance of repetitions to remain maximised while concomitantly reducing the experienced fatigue seen within a traditional-set structure (i.e. a set structure that does not include intra-set or inter-repetition rest periods). In the literature, cluster-set structures have been suggested to create a superior stimulus for the development of muscular power compared to traditional-set structures, while the opposite has been suggested for muscular strength development. Although the field suggests that cluster-set structures are superior during the development of muscular power and traditional-set structures are superior for the development of muscular strength, the literature appears to tell a different story.
Acute responses to manipulating set-structure
During training sessions, the benefits of cluster-set structures are apparent. The addition of rest intervals will lead to a greater movement velocity (Figure 1) which drives greater power outputs (Oliver et al., 2016; Tufano et al., 2017). Force output typically is quite similar between set-structures (Tufano et al., 2016); however, there is some evidence to suggest that force output is better maintained within a cluster-set structure in Olympic Weightlifting movements such as power cleans (Hardee, Triplett, Utter, Zwetsloot, & McBride, 2012). Unsurprisingly, rating of perceived exertion is found to be lower within a cluster-set structure compared to a traditional-set structure (Mayo, Iglesias-Soler, & Fernández-Del-Olmo, 2014) with data from my PhD also showing that the ‘repetitions in reserve’ model following the same trend. Outside of mechanical and exertional outcomes, cluster-set structures compared to traditional-set structures allow an athlete to feel fresher after a session, provide a better environment for technical advancement (Hardee et al., 2013) which may reduce injury risk (Duffey & Challis, 2007). Lastly, the main benefit of cluster-set structures is that a higher training load can be utilised with a given training volume, and this may provide a greater stimulus for strength and power development.
Are there differences in the development of muscular strength and power when set-structure is manipulated?
Although the differences in the acute response between cluster-set structures and traditional-set structures are clear, when used to develop strength or muscular power, the literature appears to be conflicted. Collectively, the evidence suggests that cluster- and traditional-set structures develop muscular strength and power equally (Tufano et al., 2017). Of the 10 studies that have measured power output following cluster- or traditional-set structures, only three have shown that cluster-set structures are superior (Morales-Artacho, Padial, García-Ramos, Pérez-Castilla, & Feriche, 2018; Oliver et al., 2013; Zarezadeh-Mehrizi, Aminai, & Amiri-Khorasani, 2013), while the remaining studies showing each set-structure being similar in their effectiveness (Asadi & Ramírez-Campillo, 2016; Davies, Halaki, Orr, Helms, & Hackett, 2019; Hansen, Cronin, & Newton, 2011; Izquierdo et al., 2006; Lawton, Cronin, Drinkwater, Lindsell, & Pyne, 2004; Nicholson, Ispoglou, & Bissas, 2016).
It is also commonly believed that traditional-set structures develop muscular strength to a greater extent compared to cluster-set structures which is based on the notion that fatigue is a necessary occurrence when developing muscular strength (Rooney, Herbert, & Balnave, 1994). The literature on muscular strength is more variable than the literature on muscular power. Like the studies measuring muscular power, 10 studies have measured muscular strength following resistance training of different set-structures, of which four stated that the traditional-set structure was superior (Hansen et al., 2011; Lawton et al., 2004; Rooney et al., 1994; Zarezadeh-Mehrizi et al., 2013), one study suggested that the cluster-set structure was superior (Oliver et al., 2013) with five studies showing that both set-structures are similarly effective (Davies et al., 2019; Iglesias-Soler et al., 2016; Izquierdo et al., 2006; Morales-Artacho et al., 2018; Nicholson et al., 2016). The Nicholsen et al., (2016) study is of particular interest as they incorporated a cluster-set group that performed a greater load compared to the traditional-set structure (90% 1RM compared to 85% 1RM on the back squat).
Practical Applications and Conclusions
The evidence suggests that cluster- and traditional-set structures appear to be similar when developing muscular strength and power across a wide-variety of population-types, inclusive of athletes and the general population. Therefore, it is proposed that cluster-set structures do not appear to alter the training stimulus drastically compared to a traditional-set structure. The most important practical implication of this finding is that coaches have the flexibility to design training sessions with set-structure being somewhat irrelevant to the subsequent training adaptation. Moreover, the addition of rest periods within a set comes with the trade-off of increased training session time and reduced injury risk, which may or may not be worth the trade-off depending on your context. If the trade-off is worth it, then there are many ways that cluster-set structures can be implemented into a training program. Figure 2 shows different types of cluster set-structures adapted from Tufano et al., (2017) with an example prescription adapted from Haff et al. (2008b) in Table 1.
There are many types of cluster-sets that you can employ; for example, a basic cluster set is the simple addition of rest periods within a traditional-set with inter-set rest periods remaining constant (see ‘Squat jump’ in Table 1) with an inter-repetition rest model allowing rest periods in between individual repetitions. You can manipulate load within each cluster to create an undulating (and their variants) cluster-set which allows for higher average loads to be performed in a session (see ‘Power clean’ and ‘Back squat’ in Table 1). Lastly, the rest-pause method is a type of cluster-set structure which shortens training session time and drastically increases experienced fatigue (Marshall, Robbins, Wrightson, & Siegler, 2012). This method has many different variants, but the core definition of the rest-pause method is by performing a set amount of repetitions and by accumulating repetitions through multiple sets to failure (see ‘Split squat’ in Table 1). In conclusion, the implementation of cluster-set structures are effective in improving muscular strength and power; however, they do not appear to be superior compared to traditional-set structures. Coaches should be aware that the acute response that is seen during training, especially mechanical responses that are measured with linear position transducers, does not necessarily predict the chronic adaptation that is desired.
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