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Hook-grip improves power clean kinetics and kinematics


Abstract and Figures

The purpose of this study was to compare one repetition maximum (1RM), as well as biomechanical outputs across a range of loads (75-100%) in the power clean (PC) utilizing the hook grip (HG) or closed-grip (CG). Eleven well-trained males (PC 1RM=1.34xBW) with at least six months of HG experience volunteered. Following a familiarization session, PC 1RM testing with the HG and CG were completed in random order, 5-7 days apart on a force platform with linear position transducers and 2D motion capture. The HG condition resulted in greater PC 1RM (6.6%, ES=0.43), peak barbell velocity (2.9-5.2%, ES=0.41-0.70) and relative peak barbell power (5.7-15.1%, ES=0.32-0.71) at all submaximal loads compared to CG. No substantial differences were found in horizontal bar-path (ES=-0.27-0.32). The results of this study suggest that athletes who implement weightlifting movements in their physical preparation should adopt the HG.
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Dustin J. Oranchuk1, Riki R. Lindsay1,2, Eric R. Helms1, Eric Harbour1, Adam
Storey1, Eric J. Drinkwater3
Sports Performance Research Institute New Zealand, Auckland
University of Technology, Auckland, New Zealand1
Institute of Sport, Exercise and Active Living, Victoria University,
Melbourne, Australia2
Centre for Sport Research, School of Exercise and Nutrition Science,
Deakin University, Melbourne, Australia3
The purpose of this study was to compare one repetition maximum (1RM), as well as
biomechanical outputs across a range of loads (75-100%) in the power clean (PC)
utilizing the hook grip (HG) or closed-grip (CG). Eleven well-trained males (PC
1RM=1.34xBW) with at least six months of HG experience volunteered. Following a
familiarization session, PC 1RM testing with the HG and CG were completed in random
order, 5-7 days apart on a force platform with linear position transducers and 2D motion
capture. The HG condition resulted in greater PC 1RM (6.6%, ES=0.43), peak barbell
velocity (2.9-5.2%, ES=0.41-0.70) and relative peak barbell power (5.7-15.1%, ES=0.32-
0.71) at all submaximal loads compared to CG. No substantial differences were found in
horizontal bar-path (ES=-0.27-0.32). The results of this study suggest that athletes who
implement weightlifting movements in their physical preparation should adopt the HG.
KEYWORDS: Weightlifting, velocity, resistance training.
INTRODUCTION: Optimizing muscle power and rapid force production are important for
performance in a variety of sports (Seitz, Reyes, Tran, de Villarreal, & Haff, 2014).
Weightlifting movements such as the power clean mirror many athletic movements as they
are ballistic and biomechanically similar to jumping, sprinting and change of direction tasks
(Cormie, McGuigan, & Newton, 2010). Weightlifting movements and their variations are
commonplace in strength and conditioning settings (Ebben, Carroll, & Simenz, 2004) as they
are established for improving high velocity strength to a greater degree compared to
traditional resistance training (Channell & Barfield, 2008).
Competitive weightlifters routinely utilize the hook-grip (HG) (Figure 1) when performing
pulling actions (Tsuruda, 1989). Anecdotally, the HG prevents the barbell from rotating in the
lifter’s hand, thus enabling a secure grip (Tsuruda, 1989). Athletes and coaches report that a
minimal amount of muscular effort is required to maintain a secure hold of the bar with a HG.
By requiring less muscular tension in the finger flexors (Tsuruda, 1989), the arms remain
passive, leading to a greater force transfer from the prime movers of the legs and back,
facilitating greater force and power outputs (Tsuruda, 1989). This increased power output
may benefit long-term athletic development (Channell & Barfield, 2008; Cormie et al., 2010;
Hori et al., 2008). Therefore, the primary purpose of this study was to compare the kinetics
and kinematics of the power clean with and without the HG. It was hypothesized that the HG
would increase 1RM, and enable greater levels of force, velocity and power to be generated
compared to a standard closed-grip (CG). It was also hypothesized that the HG would enable
an optimized bar-path when compared to the CG condition.
Figure 1. Hook-grip
METHODS: Eleven well-trained male strength and power athletes (reported PC
1RM=113.4±15.9 kg, age=28.1±5.6 years, height=176.2±6.4 cm, body mass=84.7±11.1 kg)
volunteered. All testing procedures were completed across three laboratory visits, each
separated by five to seven days. Following an initial CG 1RM familiarization session, all
subjects completed PC 1RM testing sessions using CG and HG in random order. Each
session was preceded by a standardized dynamic warm-up and followed a systematic
sequence of increasing loads ranging from 50% to 100% of PC 1RM in 2.5-10% increments.
Kinetic and kinematic data were collected with a force plate (AMTI, Watertown, MA) sampling
at 1000 Hz, and duel linear position transducer system (Fittech, Australia) sampling at 500
Hz interfaced with custom LabVIEW software (National Instruments, Austin, TX). Discribed in
detail by Cormie, McBride and McCaulley (2007), the kinetic method was used to obtain
peak and mean barbell velocity (m.s-1) and peak and mean barbell force (N) during the entire
pull. Peak and mean barbell power was determined by multiplying force and velocity at each
time point (Cormie, McBride, & McCaulley, 2007). A camera (Casio, EXLIM, EX-FH20,
Tokyo, Japan) positioned 5 m from the end of the barbell and 65 cm above the platform,
filmed at 300 fps to collect horizontal barbell displacement (Garhammer & Newton, 2013). A
reflective marker, and a scaling rod were applied to the end of the barbell and platform
respectively. Additional lighting was applied to the barbell with lamps placed behind the
camera. Video footage was analyzed in Kinovea 0.8.15 motional analysis software to assess
the four horizonal bar-path variables discribed in detail by Garhammer and Newton (2013).
Data were split into five categories to examine the effect of the HG at different defined
relative intensities: 75-79%, 80-84%, 85-89, 90-94% and 95-100% of 1RM. Differences in the
mean changes between the grips (CG and HG) were determined by paired samples t-tests.
The precision of mean differences is expressed with 95% confidence limits (95%CL). The
95%CLs were constructed around the mean differences to express the range of uncertainty
of the interval containing the true parameter value (or unknown population mean). Qualitative
descriptors of standardized (Cohen’s d) effect sizes were assessed using these criteria:
trivial <0.2, small 0.2-0.49, moderate 0.5-0.79, large >0.8. Effects with 95%CLs overlapping
the thresholds for small positive and small negative effects (i.e. exceeding 0.2 of the 95%CLs
on both sides of zero) were defined as unclear. A clear effect size was defined as the mean
of the 95%CL being 0.2 and not exceeding a trivial effect size on the other side of zero
(Batterham & Hopkins, 2006). The reliability of all CG variables were assessed by typical
error of measure (TEM) as SD÷√2.
RESULTS: Power clean 1RM was 6.8 kg greater when utilizing the HG (109.4±17.2 kg),
compared to the CG (102.6±14.6 kg) (ES=0.43 95%CL [0.27-0.58]). The TEM of 1RM CG
was 0.39 kg or 0.38%. Low TEMs were also found for all other reported variables (1.99-
9.13%). No substantial between-condition differences were found for any horizontal bar-path
variables (ES=-0.27-0.32). Descriptive statistics for the primary dependent variables are
presented in Table 1. Differences between the primary dependent variables and each
condition are presented in Figures 2-5.
Table 1. Descriptive data of dependent variables
Variable Condition
Peak Velocity
Peak Relative
Power (w·kg
Peak Vertical
Hook 1.10 0.07 1.06 0.07 1.05 0.06 1.02 0.06 1.02 0.06
Catch Height
Peak Velocity
Effect Size
-0.5 -0.2 1.2
Peak Relative Power
Effect Size
-0.5 -0.2 0.80.5
0.20.0 1.2
Peak Vertical Displacement
Effect Size
-0.5 -0.2
0.0 1.2
Catch Height
Effect Size
-0.5 -0.2 1.2 1.5
Figures 2-5. Forest plots illustrating effect sizes and 95%CL for each %1RM intensity
bandwidth. The shaded region indicates trivial effect sizes.
DISCUSSION: The primary findings of this investigation confirmed the contentions of
competitive weightlifters. The HG enabled substantially greater PC 1RM (6.64%, ES=0.43),
improved peak velocity (2.9-5.2%, ES=0.41-0.70) and relative peak power (5.7-15.1%,
ES=0.32-0.71) at all measured intensities. These data suggest implementing the HG leads to
greater velocity and power in athletes who utilize weightlifting movements and their
derivatives. The HG may allow athletes to utilize greater loads and express higher power in
training which could enable greater overload and facilitate adaptations benefitting athletic
performance (Cormie et al., 2010; Hori et al., 2008).
Peak vertical displacement and catch height where the participants secured the rack and
ceased the downward movement of the barbell, provide interesting findings. Differences in
peak vertical displacement between conditions were trivial to small (0.95-1.94%, ES=0.18-
0.42) at any load below 95% of 1RM. These data show that the athletes were able to pull the
barbell to similar heights regardless of the grip employed. Conversely, the HG enabled small
to large improvements in catch heights at all loads above 84% (4.35-12.35%, ES=0.40-0.96).
This relationship suggests that the HG is especially beneficial during the transition between
the pull and catch phases of the PC at high relative loads, potentially by allowing the arms to
remain relatively passive (Tsuruda, 1989). Additionally, peak velocity, a key determinant of
weightlifting performance, was greater when using the HG across all intensities. This
dichotomy between peak velocity and peak vertical displacement suggests that the
participants utilized different movement strategies to complete the PC depending on grip
condition. Movement strategy distinctions would likely include alterations in impulse
magnitude or the timing of force application (Suchomel & Sole, 2017). While it appears that
grip is especially important in the transition between the pull and catch phases, practitioners
who employ pulling derivatives should introduce their athletes to the HG. Additionally, the
present data suggest that using barbell height to monitor progress and optimal loading in
weightlifting derivatives may be inappropriate.
Limitations exist in the present study. Firstly, participants were required to have at least six
months of experience with the HG to avoid inhibition due to initial discomfort. While there
was no substantial change (-0.52%, ES=0.03) in 1RM reliability testing, suggesting no acute
learning effect, the results could have been different in a population accustomed to
performing the PC with a CG. Secondly, the present study only examined the PC. Other
weightlifting movements or derivatives including the high-pull may be differently affected by
grip choice. Finally, thumb pain is anecdotally reported during the initial adoption of HG.
Thus, practitioners should provide a transitional period before expecting increased
CONCLUSION: The HG enabled greater maximal loads to be lifted in the PC and also
improved velocity and power output across a range of submaximal loads. It was also
apparent that the ability to transition from the pull to the catch phases of the PC was
enhanced in the HG condition at near maximal loads. Interestingly, there was not a clear
difference in peak vertical displacement of the barbell between conditions at submaximal
intensities. Therefore, future research comparing grips in weightlifting movements should
examine force-time curves (Suchomel & Sole, 2017) and include joint level kinematics (Kipp
et al., 2018) to elucidate any further differences in movement strategies. Additionally,
researchers should control and report the type of grip used in studies examining weightlifting
movements and their derivatives. The examination of lifting straps and other grip tools may
also be of interest.
Batterham, A. M., & Hopkins, W. G. (2006). Making meaningful inferences about magnitudes. International
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Channell, B. T., & Barfield, J. P. (2008). Effect of Olympic and traditional resistance training on vertical jump
improvement in high school boys. Journal of Strength and Conditioning Research, 22, 1522-1527.
Cormie, P., McBride, J. M., & McCaulley, G. O. (2007). Validation of power measurement techniques in
dynamic lower body resistance exercises. Journal of Applied Biomechanics, 23(2), 103-118.
Cormie, P., McGuigan, M. R., & Newton, R. U. (2010). Adaptations in athletic performance after ballistic
power versus strength training. Medicine and Science in Sports and Exercise, 42, 1582-1598.
Ebben, W. P., Carroll, R. M., & Simenz, C. J. (2004). Strength and conditioning practices of National
Hockey League strength and conditioning coaches. Journal of Strength and Conditioning Research, 18,
Garhammer, J., & Newton, H. (2013). Applied video analysis for coaches: Weightlifting examples.
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Hori, N., Newton, R. U., Andrews, W. A., Kawamori, N., McGuigan, M. R., & Nosaka, K. (2008). Does
performance of hang power clean differentiate performance of jumping, sprinting, and changing of
direction? Journal of Strength and Conditioning Research, 22(2), 412-418.
Kipp, K., Malloy, P., Smith, J. C., Giordanelli, M., Kiely, M., Geiser, C. F., & Suchomel, T. J. (2018).
Mechanical demands of the hang power clean and jump shrug: A joint-level perspective. Journal of
Strength and Conditioning Research, 32(2), 466-474.
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hook grip. National Strength and Conditioning Association Journal, 11(2), 40-41.
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The primary purpose of this study was to investigate whether the athlete who has high performance in hang power clean, a common weightlifting exercise, has high performances in sprinting, jumping, and changing of direction (COD). As the secondary purpose, relationships between hang power clean performance, maximum strength, power and performance of jumping, sprinting, and COD also were investigated. Twenty-nine semiprofessional Australian Rules football players (age, height, and body mass [mean +/- SD]: 21.3 +/- 2.7 years, 1.8 +/- 0.1 m, and 83.6 +/- 8.2 kg) were tested for one repetition maximum (1RM) hang power clean, 1RM front squat, power output during countermovement jump with 40-kg barbell and without external load (CMJ), height of CMJ, 20-m sprint time, and 5-5 COD time. The subjects were divided into top and bottom half groups (n = 14 for each group) based on their 1RM hang power clean score relative to body mass, then measures from all other tests were compared with one-way analyses of variance. In addition, Pearson's product moment correlations between measurements were calculated among all subjects (n = 29). The top half group possessed higher maximum strength (P < 0.01), power (P < 0.01), performance of jumping (P < 0.05), and sprinting (P < 0.01). However, there was no significant difference between groups in 5-5 COD time, possibly because of important contributing factors other than strength and power. There were significant correlations between most of, but not all, combinations of performances of hang power clean, jumping, sprinting, COD, maximum strength, and power. Therefore, it seems likely there are underlying strength qualities that are common to the hang power clean, jumping, and sprinting.
The following article presents a reasonably detailed introduction to video analysis, as can be used by coaches in many sports for both qualitative (subjective) and quantitative (objective) evaluation of their athletes from a two dimensional (20) point of view. Video cameras and their set-up to capture video records of training or competition performances of athletes are emphasized, along with a review of five video analysis software programs, two of which can be obtained free of charge. Examples from the sport of Weightlifting are provided, but similar applications can be made to other sports. A brief general history of cimematographic (film) and video analyis is given, in addition to a history that is more specific to Weightlifting.
To determine whether the magnitude of improvement in athletic performance and the mechanisms driving these adaptations differ in relatively weak individuals exposed to either ballistic power training or heavy strength training. Relatively weak men (n = 24) who could perform the back squat with proficient technique were randomized into three groups: strength training (n = 8; ST), power training (n = 8; PT), or control (n = 8). Training involved three sessions per week for 10 wk in which subjects performed back squats with 75%-90% of one-repetition maximum (1RM; ST) or maximal-effort jump squats with 0%-30% 1RM (PT). Jump and sprint performances were assessed as well as measures of the force-velocity relationship, jumping mechanics, muscle architecture, and neural drive. Both experimental groups showed significant (P < or = 0.05) improvements in jump and sprint performances after training with no significant between-group differences evident in either jump (peak power: ST = 17.7% +/- 9.3%, PT = 17.6% +/- 4.5%) or sprint performance (40-m sprint: ST = 2.2% +/- 1.9%, PT = 3.6% +/- 2.3%). ST also displayed a significant increase in maximal strength that was significantly greater than the PT group (squat 1RM: ST = 31.2% +/- 11.3%, PT = 4.5% +/- 7.1%). The mechanisms driving these improvements included significant (P < or = 0.05) changes in the force-velocity relationship, jump mechanics, muscle architecture, and neural activation that showed a degree of specificity to the different training stimuli. Improvements in athletic performance were similar in relatively weak individuals exposed to either ballistic power training or heavy strength training for 10 wk. These performance improvements were mediated through neuromuscular adaptations specific to the training stimulus. The ability of strength training to render similar short-term improvements in athletic performance as ballistic power training, coupled with the potential long-term benefits of improved maximal strength, makes strength training a more effective training modality for relatively weak individuals.