The reliability and validity of repeat power ability assessments and measurement indices in loaded vertical jumps

Introduction

The ability to perform multiple high intensity efforts, termed repeat power ability (RPA) is a key component of many team sports (Mohr, Krustrup & Bangsbo, 2003; Spencer et al., 2004; Austin, Gabbett & Jenkins, 2011). RPA can be defined as the capacity to repeatedly produce maximal muscular efforts against external resistances (Natera, Cardinale & Keogh, 2020). A range of metrics have been used to describe and quantify RPA performance, with mean power output the most common (Patterson, Platzer & Raschner, 2019; Apanukul, Suwannathada & Intiraporn, 2015; Baker & Newton, 2007). Despite mean power output being the most common measure of RPA, Alemany et al. (2005) reported peak power output to be more reliable than mean power output (ICCs between 0.94–0.96 versus 0.89–0.96 and CVs 3.2% vs 4.4% respectively) in a 1 × 30 repetition continuous rebound jump protocol, where upon landing the subjects immediately descended to a self-selected squat depth before commencing the upward jumping movement. Ultimately, there is still relative uncertainty regarding what might be the most appropriate human movement e.g., jump type as well as ways to calculate the outputs e.g., fatigue index, percent decrement and if such outputs should be calculated using mean or peak power values.

Although it is likely that a combination of neural, metabolic, and mechanical factors influence RPA, there is a paucity of research explaining and investigating the performance characteristics of RPA. In contrast there is a plethora of evidence examining anaerobic capacity and the role of the phosphagen and fast glycolytic system on repeated sprint ability (Girard, Mendez-Villanueva & Bishop, 2011; Granatelli et al., 2014; Soares-Caldeira et al., 2014). Although the Wingate anaerobic test is often used to measure anaerobic power and capacity, it is suggested that different mechanisms of maximal power and fatigue are used when compared to assessments of RPA (Fry et al., 2014). The acyclical repetitions used in RPA assessments may cause more of a reliance on the phosphagen system in comparison to the cyclical Wingate anaerobic test (Fry et al., 2014). The external loads used along with the stretch-shortening cycle (SSC) actions and the landing forces experienced in some RPA jump assessments e.g., 60 s Bosco Jump Test (60BJT) may also cause a greater stress on the neuromuscular system in comparison to the Wingate anaerobic test (Sands et al., 2004; Fry et al., 2014; Natera, Cardinale & Keogh, 2020).

The 60BJT was the first RPA assessment developed to better replicate the ballistic characteristics and SSC actions seen in many sports (Bosco et al., 1983). The 60BJT is performed with bodyweight (no additional resistance) and has been used to assess both anaerobic power and anaerobic capacity (Bosco et al., 1983). The 60BJT has also been used to differentiate between athletic cohorts and estimate muscle fiber type composition (Bosco et al., 1983; Bosco, Luhtanen & Komi, 1983; Sands et al., 2004). Notwithstanding the support for the use of the 60BJT, abbreviated forms of the 60BJT such as the 30 s Bosco Jump Test (30BJT), have been utilised in recent years to mediate excessive fatigue during testing which can negatively interfere with subsequent elements of training (Dal Pupo et al., 2014; Pupo et al., 2013; Trinkūnas et al., 2011). The 30BJT has been reported as a reliable and valid assessment of anaerobic power and capacity, particularly in athletes who require the use of stored elastic energy for performance purposes (Dal Pupo et al., 2014; Pupo et al., 2013; Trinkūnas et al., 2011).

One criticism of RPA assessments such as the 30BJT and 60BJT, is that they do not utilise external loading, and as such they may not adequately represent the external load experienced in many sports (Natera, Cardinale & Keogh, 2020). As such, unloaded RPA assessments may not provide sufficient stress to the neuromuscular and cardiorespiratory system to replicate loading strategies typically used to improve power output (Natera, Cardinale & Keogh, 2020). The Kansas Squat Test is an RPA assessment that was developed to address this lack of loading, involving 15 repetitions of speed squats with a system mass back squat load of 70% 1RM. Reliability and validity of the Kansas Squat Test was established against the Wingate anaerobic test (ICCs = 0.754 to 0.937 and r = 0.775 respectively) (Fry et al., 2014), but not the 60BJT or 30BJT. However, it is important to consider that speed variations of traditional strength exercises, like the speed squat used by Fry et al. (2014), can have up to 40% of the concentric portion of the lift used to decelerate the barbell (Elliott, Wilson & Kerr, 1989).

Although Fry et al. (2014) is the only group to investigate the validity of an RPA assessment, other studies using loaded CMJs have reported their protocol’s reliability. RPA assessments using loaded CMJs have reported ICCs of between 0.73 to 0.97 and 0.881 to 0.987, respectively (Alemany et al., 2005; Patterson, Raschner & Platzer, 2014). However, these RPA protocols differed considerably with Alemany et al. (2005) using a Smith machine for 1 set of 30 repetitions and Patterson, Raschner & Platzer (2014) using a free barbell for a 2.5-minute protocol. Further differences between protocols were seen in the loads and measurement device used (rotary encoder vs. force plate respectively). Further differences between protocols were seen in the loads and measurement device used (rotary encoder vs. force plate respectively).

Patterson, Raschner & Platzer (2014) sought to establish more control over their CMJ protocol by standardising the time between jump and the depth of countermovement. Only Patterson, Raschner & Platzer (2014) used a maximal power reference value, to minimise possible pacing strategies. Although the Alemany et al. (2005) protocol was reliable, an accurate measure of RPA might not have been established without controlling these factors. For example, allowing a self-selected countermovement depth may have resulted in participants changing their strategy and utilising a shallower countermovement as they fatigued. This may have artificially inflated power output by decreasing the time to perform work. Unlike Patterson, Raschner & Platzer (2014), Alemany et al. (2005) did quantify load relative to strength levels, and as a result of using a Smith machine, the requirement to control the vertical tracking of the bar was lessened.

Ballistic movements may better replicate many of the actions performed in sports where acceleration throughout the entire range of motion is important. As such RPA assessments performed with ballistic exercises, like loaded CMJs, involve greater acceleration of the barbell throughout the entire movement (Newton et al., 1996). However, with changes in countermovement strategy observed as a result of fatigue, controlling for technical influence in the countermovement strategy might be provided by using a squat jump (SJ) (Cormack et al., 2008). To date no studies have investigated the SJ as a potential ballistic exercise for RPA assessments. With a SJ performed from a static position, the countermovement strategies used in a CMJ are largely avoided. However, it is yet to be determined whether under fatigue, a SJ can be truly performed without some form of a small amplitude countermovement, particularly when maximal power output for each repetition is the objective.

The method of calculation of power decline is a further source of discrepancy in the RPA literature. To quantify the change in power output across multiple repetitions in RPA, Baker & Newton (2007) and Fry et al. (2014) calculated the percent difference in mean power output between the final repetition and the repetition with the highest mean power output. Patterson, Platzer & Raschner (2019) quantified the change in power output as the percentage difference between the jump that registered the highest power output with the average power output of the final 12 jumps in the assessment. In an investigation of four different approaches to quantify the ability to repeatedly produce high intensity efforts, the percent decrement calculation was found to be the most valid and reliable method of quantifying fatigue (ICCs between 0.81–0.83) (Glaister et al., 2004). The percent decrement calculation identifies the percent difference between the total sum and the ideal sum. Currently, no RPA assessments utilise the percent decrement method to quantify RPA.

In repeated high intensity efforts, where the overall repetitions to be performed are known by the participant, there may be a risk of pacing to mitigate the earlier onset of fatigue (Billaut et al., 2011). Participants may consciously or unconsciously use pacing during RPA assessments, therefore it may be important to control for the most variable jumps within the assessment by removing them from the calculation of power decline. To our knowledge the removal of potentially highly variable jumps, that may occur at the very start and very end of an RPA assessment, have not been performed before to improve RPA assessment reliability.

The aim of this study was to: (1) compare the inter-test reliability of an RPA assessments consisting of loaded SJs and an RPA assessment consisting of loaded CMJs, using an average score, a fatigue index and a percent decrement score, for both mean and peak power output; and (2) assess the validity of the two RPA assessments and the different measurement indices against the 30BJT. We hypothesized that: (1) the CMJ protocol would be more reliable than the SJ protocol and that the peak power percent decrement score would be the most reliable measure of RPA; and (2) none of the measured RPA variables would be valid in comparison to the 30BJT.

Materials & Methods

Procedures

Participants were required to attend the strength and conditioning facility on six different occasions over a three-week period (see Fig. 1). The first session of week one was used to collect descriptive data and assess 3RM Half Squat (3RMHS) in order to estimate a 1RM Half Squat (1RMHS), which was used to calculate 30% of 1RMHS (30%HS) loads that were used for the RPA assessments. A percent 1RMHS load was chosen to stay consistent with regular strength training prescription guidelines and to allow RPA assessments to be able to cater for all strength levels, with jump loads based on individual capabilities. Along with 3RMHS testing, each participant performed a familiarisation trial with the 30BJT at the end of the first session. During session two, which was performed 72 h later, the 30BJT was assessed after establishing the maximal power reference value for both CMJ and SJ with the 30%HS load.

Weeks two and three were used for test-retest of the RPA protocols, where in a randomized order separated by 72 h, each participant performed either the 20SJ or the 20CMJ RPA assessment in different sessions. During week three, each of the RPA assessments were performed on the same corresponding day with the identical 48-hour period leading up to the assessment.

Results

AvgCMJ_peak and AvgSJ_peak had good intertest reliability (CV = 2.5–3.8; ICC = 0.94–0.96 [CI [0.83–0.991]]). AvgCMJ_mean had better reliability than AvgSJ_mean (CV = 3; ICC = 0.96–0.96 [CI [0.884–0.991]] vs CV = 7.2–7.4; ICC—0.841–0.846 [CI [0.534–0.955]]). PD%CMJ_peak18 (Fig. 2) was the most reliable measurement of power output decline (CV = 4.9; ICC = 0.85 [CI [0.62–0.964]]).

There were no significant differences found between the two testing occasions for all variables (p = 0.105–0.858) except for PD%SJ_peak18 and PD%CMJ_mean18 (p = 0.029 and p = 0.045 respectively). In establishing the magnitude of difference between trials only small differences were observed (Hedges g effect = 0.517) All participants displayed similar peak power output for each trial (Fig. 3) with a mean first repetition of 6834.8 ± 808.2 W and a 20th repetition of 5178.9 ± 804.5 W for both trials. The mean decrease between 1st and 2nd repetitions was 250.2 ± 57.7 W and the mean decrease from 19th to 20th repetitions was 77.6 ± 16.3 W. The first and/or last repetition, in the present study have high variability between trials. Therefore, when removing them from the calculation the CV for PD%CMJ_peak improved from 20.5% to 4.9% for PD%CMJ_peak18.

Both AvgCMJ_mean and AvgCMJ_peak had moderate correlations with Avg30BJT_peak (r = 0.618, p = 0.043 and r = 0.639, p = 0.34 respectively) (Figs. 4 and 5). AvgCMJ_mean18 and AvgCMJ_peak18 also had moderate correlations with Avg30BJT_peak (r = 0.615, p = 0.044 and r = 0.638, p = 0.035 respectively) (Figs. 6 and 7). AvgCMJ_mean and AvgCMJ_mean18 had strong correlations with Avg30BJT_mean (r = 0.757, p = 0.007 and r = 0.755, p = 0.007) (Figs. 8 and 9).

No RPA measurements of power decline were significantly related to 30BJT measurements of power decline. The limits of agreement between PD%CMJ_peak18 and percent decrement of 30BJT peak power (Fig. 10) were poor (bias = 19.164, limits of agreement = 10.56–27.768).

Discussion

The results from this study show that an RPA assessment consisting of either 20 repetitions of CMJs or SJs with a 30% 1RM load can be a reliable assessment for outcomes reflecting average power output. Specifically, both the average peak and average mean power output for the 20CMJ had good reliability, whereas only the average peak power output in the 20SJ had good reliability. When removing the first and last jumps from the calculation, the 20CMJ PD% score proved to be the most reliable measure of power decline and is therefore the recommended measurement of RPA. Although there were large to very large associations found between Avg CMJ peak and mean power output with 30BJT peak and mean power output, measures of power output decline had only trivial to moderate associations and with no validity established between the assessments.

Relative test re-test reliability of the 20CMJ using the PD%CMJ_peak18 had better relative test re-test reliability than the Kansas Squat Test in the assessment of power decline (ICCs = 0.875 versus 0.754 respectively) (Fry et al., 2014). The Kansas Squat Test is an RPA assessment utilising a traditional strength training lift consisting of 15 repetitions of back squats executed at maximal velocity. Each repetition of the Kansas Squat Test was performed every 6 s, with a system mass back squat load of 70% 1RM. To minimise variability in the Kansas Squat Test, the time between repetitions, depth of squat, vertical tracking of the barbell and technical execution of the squat, in not allowing ankle plantar flexion at the end of the ascent, were all controlled. In the current study, jump depth, timing of jump and vertical tracking of the barbell were also controlled, however, the ballistic movement of the jump allowed for a continuation of momentum and greater acceleration throughout the range of movement. Allowing for the continuation of momentum may have contributed to the 20CMJ being a more reliable assessment of RPA than the Kansas Squat Test. With the ability to accelerate continuously throughout the movement, the 20CMJ may also more closely replicate sporting movements than the Kansas Squat Test (Newton et al., 1996).

Although absolute reliability was not assessed in the Kansas Squat Test, Alemany et al. (2005) did examine absolute reliability in their RPA assessment consisting of 30 loaded CMJs with a 30% 1RM back squat load. The loaded CMJs were performed consecutively with no pause between jumps and with self-selected depth. In comparing both AvgCMJ_peak and AvgCMJ_mean with the average peak and mean power output in the Alemany et al. (2005) assessment, the 20CMJ is a comparable or slightly more reliable RPA assessment (CVs = 2.5–3% vs 3.2–4.4%, respectively). In visually examining a representative fatigue curve illustrated by Alemany et al. (2005), it appears that their use of 30 continuous jumps caused a more substantial decline in power output than the present study (∼50% decline from first to last repetition vs ∼25% decline from first to last repetition, respectively).

In both the current study and the work of Alemany et al. (2005), CMJ peak power output was found to be more reliable than mean power output. Mean power output represents the rate of mechanical work done over the whole propulsive phase of the jump as opposed to peak power output which represents a specific sample period of the highest rate of mechanical work during the propulsive phase (Gathercole et al., 2015). In RPA assessments, a longer sampling period across the CMJ propulsive phase seems to introduce greater variability and therefore less reliability between trials. Much of the variability captured in the longer sampling period may reflect the greater ability to capture changing movement strategies used to try to maintain power output. This variability in mean power output seems to be consistent across both loaded and unloaded CMJ conditions (García-Ramos et al., 2016; Hori et al., 2009; Cormack et al., 2008). Peak power output is therefore the recommended metric for assessing RPA.

The current study also sought to examine whether jump type may influence reliability, and it appears to be the only known study to use SJs in an RPA assessment, which might be particularly important for athletes needing to repeatedly perform ballistic concentric only actions. However, it has also been proposed that in a SJ, it can be difficult to maintain a stable and static period before the initiation of the propulsive phase of the jump (García-Ramos, Pérez-Castilla & Jaric, 2021; Pérez-Castilla et al., 2021). In the 20SJ, where fatigue induced declines in power output even with live feedback of power output, it is likely that technical strategies to maintain power output could be used more readily under these conditions. One such strategy might be performing a small countermovement to potentiate the propulsive phase of the jump (Dugan et al., 2004). Holding a static position under increasing levels of fatigue along with the potential use of a countermovement would introduce a higher level of variability in the 20SJ as opposed to the 20CMJ and may be the reason why no RPA studies to date have used SJs. Despite this potential variability, the 20SJ did show good reliability for AvgSJ_peak and AvgSJ_peak18.

In general, across both the 20CMJ and 20SJ, the Avg power output scores are the most reliable calculation identified. Avg power output scores could be used longitudinally for an individual athlete to understand their ability to maintain power output. However, an average power output score does not provide a clear measure of power decline and can often be heavily influenced by maximal power output (Douglas, Ross & Martin, 2021). For example, due to a higher starting threshold an athlete with a high maximal power output but high levels of power decline, can have comparatively higher overall Avg power output than an athlete with a lower peak power output threshold and power decline (see example of this between two different participants in Fig. 11). For comparisons of RPA to be made between athletes, it is recommended that a power decline score be used to describe an athlete’s ability more precisely to repeatedly produce maximal muscular efforts against external resistances.

In the current study, a FI% (Fatigue = ([highest power output − lowest power output]/highest power output × 100)) and a PD% (Fatigue = 100 × [total jump power/ideal jump power] − 100) were used to quantify power output decline. When calculating the FI% and PD%, neither of the RPA assessments were found to be reliable when all 20 repetitions were incorporated into the calculation. However, when the first and last repetition were removed from the calculations, reliability significantly improved with PD% showing the best reliability (CV = 4.9%). PD% has previously been shown to be the most valid and reliable method of quantifying fatigue where each repetition is factored into the overall result rather than a finite representation (Glaister et al., 2004). Again, the first and/or last repetition, in the present study have high variability between trials. Therefore, when removing them from the calculation, the CV for PD%CMJ_peak improved from 20.5% to 4.9% for PD%CMJ_peak18. It is suggested that the knowledge of repetition number in repeated maximal efforts tasks can lead to the use of significant pacing strategies (Billaut et al., 2011). The first and last repetition of the CMJ20 seems to be highly susceptible to some form of pacing and therefore the removal of these repetitions from the PD%CMJ_peak calculation appears to better represent RPA and substantially improve absolute reliability.

None of the RPA power decline assessments were related to the 30BJT power decline assessments. The continuous nature of the 30BJT versus the brief between jump rest periods provided in the 20CMJ and 20SJ and the higher number of jumps performed in the 30BJT versus the 20CMJ and 20SJ may have contributed to this. This finding may suggest that the addition of load in an RPA assessment presents a substantially different physical challenge that alters the power decline profile observed in an RPA assessment with no external load. However, despite the reduced number of jumps and the brief recovery between jumps in the 20CMJ and 20SJ, the addition of load seems to have provided a higher stress to the neuromuscular and cardiorespiratory systems and in turn altered the power decline profile more readily then in the 30BJT. This is evident for example when comparing the mean and standard deviations in PD% between PD%CMJ_peak18 and PD%30BJT_peak (26.61 ± 3.71% versus 7.44 ± 1.77% respectively). It appears that PD%CMJ_peak18 and the PD%BJT30_peak are both unique assessments and measurement indices. The poor level of agreement between these two assessments is further evidence of the disparity between these two measures and further confirmation that validity is not established between these assessments.

When comparing Avg mean and peak power output for the 20CMJ against the Avg mean and peak power output for the 30BJT, large to very large relationships were observed. However, as Avg measures can be substantially influenced by maximal power output, the relationship is likely more indicative of the association between maximal power output in a relative 1RM loaded jump condition versus a jump condition with no external load.

This is the first study to examine jump type, measurement indices and power decline calculations to determine the most reliable ballistic assessment of RPA in well trained athletes. A limitation to this study may be the calculation of power decline for the 30BJT assessment. In the current study we followed the recommendations provided in the original research by Bosco et al. (1983) using the 60BJT, where the average of power output for the first 15 s was compared to the average of the final 15 s of the 30BJT. Perhaps factoring in each individual jump, as done in the CMJ20 and the SJ20 power decline calculations, may have provided a better comparison between the assessments.

Conclusions

We hypothesized that the PD%CMJ would be the most reliable RPA assessment, however removing the first and last repetition made PD%CMJ_peak18 the most reliable measure of RPA power output decline. As also hypothesized, no RPA assessment and measurement was valid with the 30BJT. In comparing mean power output and peak power output for 20SJ and 20CMJ with various methods of quantifying power output decline, we found the PD% score of peak power output for CMJ20, with the first and last jumps removed, to be the most reliable assessment of RPA. The addition of load, the reduced number of jumps and the discontinuous nature of jumps in the CMJ20 appear to have a differing effect on the rate and magnitude of power decline seen in 30BJT. The 20CMJ assessment now provides a reliable ballistic RPA assessment, that with the addition of load, may be more applicable to certain sporting movements and actions whilst being simple to administer and conduct in the field. Future research should look to further explain and define CMJ20 by identifying related physical qualities and relationships with aspects of competition performance.