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Abstract

BACKGROUND:

Strength-power tests are commonly used to monitor performance improvement and to assess preparedness for competition in weightlifters. Previous studies were limited to male weightlifters, consisted of a small number of tests, or used small samples of female weightlifters.

OBJECTIVE:

The purpose of this study is to determine the strongest indicators of weightlifting performance (WPER) and to reveal the relationships between competition performance and strength-power tests in junior female weightlifters.

METHODS:

Forty-two female weightlifters (age: 17.8 $\pm$ 2.3 years, body mass: 56.6 $\pm$ 8.1 kg; height: 156.1 $\pm$ 5.8) participated in this study. Participants were tested on a series of performance indicators including Wingate anaerobic power (lower and upper body), isokinetic leg force, vertical jumps, handgrip strength, and isometric leg strength following a national weightlifting competition. Competition performance was calculated with the Sinclair equation. Pearson correlation analysis was used to reveal the relationships between strength-power variables and Sinclair score, and Ridge regression analysis was used to determine the strongest indicators of WPER.

RESULTS:

The main results showed that Wingate leg peak power (L-PP) and countermovement jump height (CMJ) were the strongest indicators for WPER. They accounted for 74% of the common variance. Additionally, there was a significant correlation between strength-power variables ( $r=$ 0.41–0.846) and Sinclair score.

CONCLUSIONS:

This study’s findings suggest that the strongest predictors of WPER are L-PP and CMJ, and these tests can be used to monitor WPER in junior female weightlifters.

Keywords

Olympic weightlifting Wingate countermovement jump isokinetic strength vertical jump isometric leg strength

1. Introduction

Weightlifting was an important sporting discipline, mainly organized to determine the strongest males in the ancient Olympic Games. Although men’s weightlifting has been in the modern Olympic Games since 1896, women have only been allowed to participate since 1987. Female weightlifting was included as a medal sport and thus achieved Olympic status at the 2000 games in Sydney. Consequently, it has become popular in many countries over the last two decades [1, 2].

The snatch and the clean and jerk – two lifts used in the modern Olympic Games – was described as multi-joint strength movements, which produce great muscle power demands on both the upper and lower body. Although weightlifting is known as a dynamic strength sport, it has been reported that a successful lift of the barbell cannot be predicted on the basis of a single variable [3] and the bar’s trajectory [4], speed [4, 5], and displacement [5, 6] of a lift are closely related to the manner in which forces are applied to the barbell [7]. The distinctive combination of power, muscle strength, flexibility, kinesthetic awareness, and lifting technique required for successful weightlifting performance requires a unique physiological profile [1]. Many variables that are thought to be related to weightlifting performance, such as anaerobic power, balance, jump, flexibility, and knee flexor and extensor strength, have been examined in studies of certain test protocols [8, 9, 10, 11].

Biomechanical studies have reported some differences between male and female weightlifters in weightlifting lifts [12]. Women are able to produce high short-term power outputs, however, their strength is lower than that of men both in absolute terms and in terms of relative body mass [13]. In addition, women’s use of elastic energy during the snatch transition phase is lower and they drop under the barbell more slowly [14]. Moreover, the duration of the second pulls, maximum vertical barbell velocity and maximum barbell heights are lower in females than in males. An interesting finding indicated a similarity in the amount of mechanical work in female athletes’ first snatches and second pulls, while the amount of mechanical work in the first pull was higher in males [13]. However, in more recent studies, it has been observed that the snatch patterns of elite female weightlifters are similar to those of male weightlifters [15].

There is consensus in the literature about the importance of evaluating physical and physiological characteristics to optimize sport performance [16]. The use of laboratory and field tests to assess strength-power profiles of weightlifting athletes is widespread and the number of these tests has increased exponentially in recent years [17]. These tests are very important to identify athletic talent, training efficiency, and to monitor performance [10, 11, 16]. However, as in many sports, female athletes have not been studied as extensively as male athletes [2, 18, 19]. In addition, the number of studies on women is limited and in these studies have contained small sample sizes [2, 18, 20] or consisted of a small number of tests [19, 20]. Therefore, this study aims to predict the competition performance of female weightlifters via commonly used strength-power tests. Thus, this study may close the sex-based gap evident in existing literature related to weightlifting. We hypothesized that among the commonly used strength-power tests, tests that measure the explosive power of the lower body could better predict the weightlifting performance in female weightlifters.

2. Methods

2.1 Experimental approach to the problem

This cross-sectional study was designed to reveal the relationships between strength-power tests and weightlifting performance in female weightlifters and determine that were tests better predictors of competition performance. Wingate leg mean power (L-MP), Wingate leg peak power (L-PP), Wingate arm mean power (A-MP), Wingate arm peak power (A-PP), handgrip strength (HGS), isometric leg strength (LS), isokinetic knee extension strength 60 deg/s (IS-60), isokinetic knee extension strength 180 deg/s (IS-180), squat jump (SJ), countermovement jump (CMJ), and countermovement jump with arm swing (CMJ-A) were determined as independent variables, while Sinclair total (competition performance) was determined as a dependent variable. Ridge regression analysis was used to determine the effect of independent variables on Sinclair score, and Pearson correlation analysis was used to reveal the relationships between strength-power test results and Sinclair score.

2.2 Subjects

Forty-two junior female weightlifters volunteered to participate in this study. The sample group consisted of subjects included in the national athlete monitoring program by the weightlifting federation of our country. This program aims to improve the performance of athletes and prepare them for the Olympics by providing nutrition, training, and material support under the supervision of professionals appointed by the Weightlifting Federation. Other participation criteria were that participants had to be at least 15 years old, have at least two years of training experience with a coach registered in the National Federation, and have competed in the national championship just before the initial measurements were taken. Participants who had disabilities or were undergoing medical treatment and those using any dietary supplements, caffeine or stimulants during the test week were excluded from the study. All participants and their families were informed about the possible risks related to the experimental procedures and gave their informed consent in writing. The Ethics Committee of the Central University approved the study protocol (Ethics Committee meeting date and decision number: 31/08/2019, 254).

2.3 Testing protocols

The participants’ weightlifting ability was evaluated based on their performance in the national championship, which took place seven to ten days before the tests. For the tests, the athletes were divided into three groups. Each group completed three test sessions at 48-hour intervals. The three test sessions assessed (A) anthropometric measurements and Wingate lower body anaerobic power; (B) Wingate upper body anaerobic power, handgrip, and leg strength; and (C) vertical jump heights and isokinetic strength. No familiarization session was necessary as the participants were already accustomed to these tests, having done them at least twice as part of the above-mentioned national project. In order to avoid test-retest errors, the same investigator conducted the vertical jump and isometric strength tests using the same test devices. Participants were verbally encouraged to maximize their performance during the tests and not allowed to perform any physically demanding activities during the study period. In addition, as all participants were trainees at the Olympic Preparation Center, they followed the same meal schedule, which was established by their dietitian. Participants were asked to maintain their normal daily meal routines and not to use any stimulant or supplement during the study period.

2.4 Olympic weightlifting performance

The Sinclair formula was used to calculate weightlifting performance based on the total weight lifted (using both the snatch and the clean and jerk technique) in the national championship, which took place before the tests. The Sinclair formula is a polynomial equation that allows the comparison of a weightlifter’s lifting performance with that of other athletes in different weight categories. This formula is based on the current Olympic records and is updated every four years (https://www.iwf.net/weightlifting_/sinclair-coefficient/). For the current Olympic cycle, the Sinclair formula for women is as follows: Sinclair total $=$ Unadjusted total $\cdot$ 10 ${}^{AX2}$ , where $X=\log^{10}$ (BM $\cdot$ 153.6551) and $A=$ 0.783497476.

2.5 Anthropometric measurements

The height of the participants was measured with a portable stadiometer according to standard procedures (Holtain Ltd, Crosswell, Crymych, Dyfed, UK). Body weights were measured with a Tanita weighing scale (BC-310; Tanita Corp., Tokyo, Japan). Skinfold thickness measurements were performed using a skinfold caliper device (Holtain Ltd., Crymych, UK) with $\pm$ 0.02 mm measurement sensitivity. Jackson and Pollock’s generalized skinfold equation (measuring seven body regions) was used to calculate body density (g-mhO) [21], and relative fat levels were determined using the Siri equation [22].

2.6 Wingate anaerobic tests

The anaerobic power of the upper and lower limbs was assessed using Wingate anaerobic power tests, which were performed on a cycle ergometer (Monark 894E Peak Bike, Stockholm, Sweden) via a test software program. The tests required participants to exercise at maximum intensity for 30 seconds against external resistance (75 g $\cdot$ kg ${}^{-1}$ BM for the lower body and 55 g $\cdot$ kg ${}^{-1}$ BM for the upper body). Participants warmed up by pedaling at 60–70 rpm for five minutes and performing three rounds of all-out sprinting during the last five seconds of the last three minutes. After the warm-up protocol, participants were allowed a passive rest period of five minutes. Participants were asked to maintain the maximum cadence rate for 30 seconds and external resistance was added when they reached a cadence rate of 130–150 rpm. The cadence rate (visible to the participants) was simultaneously monitored and recorded during the tests. The highest power value reached in any five seconds during the tests was calculated as peak power (PP) and the average power was calculated as the mean power (MP) in watts [23]. In addition, relative values corresponding to body weight were calculated.

2.7 Vertical jump tests

For the warm-up before the jump tests, the participants performed standard stretching exercises, free jumps, and finally completed two sets of eight squats with barbells at 25% of BM. SJ, CMJ, and CMJ-A tests were completed in regular order after three minutes of rest. During the CMJ test, participants were asked to put their hands on their waist, keep their knees in full extension, then stretch the knees and jump vertically as quickly as possible. If the participants moved their hands from their waist at any stage of the jump or pulled in their knees while in the air, the test was invalid and repeated. For CMJ-A tests, the same procedure was applied but the participants’ hands were free. In the SJ test, the participants were asked to put their hands next to their waist, keep their knees in a 90 ${}^{\circ}$ squat position, and jump vertically as high as possible without further knee flexion. The knee angles were checked using a goniometer. Two trials were performed for all vertical tests and the highest result was considered valid. Jump tests were measured using an optoelectronic measurement system (Optojump Next; Microgate, Bolzano, Italy) [24].

2.8 Handgrip and trunk strength tests

During the assessment of handgrip strength, the participants were asked to stand upright with their feet hip-width apart and look forward with their elbow fully extended. The dynamometer (Takei A5001 Hand Grip Dynamometer, Tokyo, Japan) was held in a neutral, comfortable position (not bent or flexed), at 90 ${}^{\circ}$ of flexion in the index finger of the test hand. For the measurement of isometric leg strength, the subjects stood on the footplate of the dynamometer (Takei A5002 Leg Dynamometer, Tokyo, Japan) initially in the same manner as for the measurement of leg strength. The legs were kept straight, and the back was flexed at the hip. Flexion continued until the tips of the index fingers reached the patellae, with the elbows fully extended. The pull-bar of the dynamometer was then placed in the hands and the chain length was adjusted. A reverse grip was adopted for the measurement of back strength to deter the use of shoulder muscles during the pull. The participants were also instructed to keep their heads up during the measurement. In both tests, the highest score from the two trials, which were separated by three minutes of rest, was recorded [25].

2.9 Isokinetic strength tests

Before the tests, the isokinetic dynamometer was calibrated according to the manufacturer’s instructions, and descriptive information about the participants (name, age, gender, body weight, height, and dominant leg) was entered into the dynamometer’s computer. The isokinetic knee extensor strength test consisted of concentric phases in the isokinetic dynamometer system (Cybex HUMAC Norm; CSMi, Stoughton, MA, USA) and then concentric phases at angular speeds of 180 ${}^{\circ}$ /s and concentric speeds of 60 ${}^{\circ}$ /s. Participants completed a standard five-minute warm-up on a 60–70 W cycle ergometer. The tests were started after the seat, dynamometer, stabilization, isolation, gravity correction, and range of motion were adjusted to angular velocity and following the manufacturer’s instructions. The participants were fixed in a sitting position with approximately 90 ${}^{\circ}$ hip flexion. The axis of rotation of the knee joint coincided with the axis of rotation of the dynamometer. An angular range of motion from 90 ${}^{\circ}$ to 0 ${}^{\circ}$ was used. During the test, the participants were fixed in the optimum position to the chair with stabilization straps on the trunk, hips, and thigh while they kept their arms on their chest. For each type of angular velocity and contraction, the participants performed three maximum contractions with a full range of motion to adapt to the device before testing. The absolute peak torque and relative (BM.kg-1) peak torque specific to both angular velocities were determined for the dominant leg.

For isokinetic tests, two attempts were made in concentric mode and the highest value was considered valid. ICC (95% CI) values were calculated as follows: for 60 ${}^{\circ}$ /s, 0.92 (0.89–0.94); for 180 ${}^{\circ}$ /s, 0.91 (0.88–0.95). During the test, there was a three-minute rest interval between trials and a five-minute rest interval between the two angular velocities.

2.10 Statistical analysis

The normality of data was controlled using the Kolmogorov-Smirnov test. Data were analyzed using descriptive statistics, and the results were summarized as means $\pm$ standard deviations. Simple Pearson’s correlations were used to determine the relationships between strength-power tests and competition performance. Multiple Ridge regression, a technique for analyzing multiple regression data suffering from multicollinearity, was used to determine the predictors of competition performance without needing to remove any variables from the model [26, 27, 28]. Statistical analyses were performed using Statistica version 12.0 (Statsoft Inc., Tulsa, OK, USA), and a $p$ -value of ${<}$ 0.05 was accepted as significant.

Table 1
Participants’ descriptive and performance characteristics

Competition performance results			Descriptive characteristics
Sinclair	218.99	$\pm$ 14.31	Age (years)	17.76	$\pm$ 2.33
Snatch (kg)	68.81	$\pm$ 14.69	Height (cm)	156.13	$\pm$ 5.77
Clean and Jerk (kg)	86.48	$\pm$ 18.92	Body mass (kg)	56.59	$\pm$ 8.15
Total (kg)	154.69	$\pm$ 33.39	Body fat (%)	22.01	$\pm$ 2.96
Wingate anaerobic tests			Vertical jumps tests
Leg mean power (W.kg ${}^{-1}$ )	9.66	$\pm$ 1.63	SJ (cm)	30.12	$\pm$ 3.68
Leg peak power (W.kg ${}^{-1}$ )	6.99	$\pm$ 0.64	CMJ (cm)	32.52	$\pm$ 4.53
Arm mean power (W.kg ${}^{-1}$ )	6.21	$\pm$ 0.80	CMJ-A (cm)	35.51	$\pm$ 5.38
Arm peak power (W.kg ${}^{-1}$ )	3.77	$\pm$ 0.53
Isokinetic knee extension test			Isometric strength tests
IS at 60 deg/s (Nm.kg ${}^{-1}$ )	160.21	$\pm$ 25.23	Handgrip strength (kg)	33.51	$\pm$ 6.54
IS at 180 deg/s (Nm.kg ${}^{-1}$ )	115.90	$\pm$ 19.59	Leg strength (kg)	100.59	$\pm$ 15.32

Values are expressed as mean $\pm$ SD, ( $n=$ 42). IS-60 $=$ Isokinetic knee extension strength 60 deg/s; IS-180 $=$ Isokinetic knee extension strength 180 deg/s; SJ $=$ Squat jump; CMJ $=$ Countermovement jump; CMJ-A $=$ Counter movement jump with arm swing.

Table 2

Pearson product-moment correlation coefficients between different variables

	LMP	L-PP	A-MP	A-PP	IS-60	IS-180	SJ	CMJ	CMJ-A	HGS	ILS
Sinclair	0.751	0.846	0.410	0.457	0.637	0.638	0.735	0.835	0.829	0.478	0.482
L-MP	1	0.832	0.477	0.420	0.632	0.667	0.684	0.747	0.776	0.114	0.477
L-PP	0.832	1	0.383	0.485	0.659	0.660	0.978	0.810	0.856	0.334	0.465
A-MP	0.447	0.383	1	0.693	0.466	0.549	0.400	0.405	0.330	0.192	0.299
A-PP	0.420	0.485	0.693	1	0.555	0.628	0.390	0.407	0.388	0.272	0.331
IS-60	0.632	0.659	0.466	0.555	1	0.912	0.538	0.591	0.601	0.345	0.486
IS-180	0.667	0.660	0.549	0.628	0.912	1	0.584	0.575	0.631	0.308	0.547
SJ	0.684	0.678	0.400	0.390	0.538	0.584	1	0.890	0.864	0.458	0.477
CMJ	0.747	0.810	0.405	0.407	0.591	0.575	0.890	1	0.929	0.468	0.488
CMJ-A	0.776	0.856	0.330	0.388	0.601	0.631	0.864	0.929	1	0.449	0.493
HGS	0.114	0.334	0.192	0.272	0.345	0.308	0.458	0.468	0.449	1	0.445
ILS	0.477	0.465	0.299	0.331	0.486	0.547	0.477	0.488	0.493	0.445	1

${}^{*}$ Correlation is significant at the level of $p<$ 0.01 ( $n=$ 42). L-MP $=$ Leg mean power (Wingate test); L-PP $=$ Leg peak power (Wingate test); A-MP $=$ Arm mean power (Wingate test); A-PP $=$ Arm peak power (Wingate test); IS-60 $=$ Isokinetic knee extension strength 60 deg/s; IS-180 $=$ Isokinetic knee extension strength 180 deg/s; SJ $=$ Squat jump; CMJ $=$ Countermovement jump; CMJ-A $=$ Counter movement jump with arm swing; HGS $=$ Hand grip strength; ILS $=$ Leg strength.

Table 3

Summary of ridge regression model of weightlifters’ performance (sinclair score) on the basis of different strength tests and body composition ( $n=$ 42)

(Constant)		20.304	19.512
	Beta	B	Std. error
L-PP	0.459	9.619	3.985
CMJ	0.422	3.191	3.662
R ${}^{2}$		0.740
F		55.548
p		0.0001

B $=$ Unstandardized Coefficients; L-PP $=$ Leg peak power (Wingate test); CMJ $=$ Countermovement jump.

3. Results

The correlations between strength-power tests and Sinclair score are presented in Table 2. Pearson correlation results showed significant correlations between 11 different variables and Sinclair score ( $r=$ 0.41–0.846). The variables correlated that correlated most strongly with Sinclair score were Wingate leg peak power ( $r=$ 0.846) and countermovement jump ( $r=$ 0.835).

A multiple Ridge regression model was used to determine the strongest indicators of competition performance (Table 3). The results suggest that the determinants of competition performance are L-PP and CMJ, which account for 74% of the common variance. The following regression function was obtained from a multiple ridge regression analysis for the dependent variable (Sinclair score): Point score $=$ 20.304 $+$ 9.619 $\times$ L-PP $+$ 3.191 $\times$ CMJ.

4. Discussion

This study aimed to reveal the relationships between power-strength tests and competition performance and to determine the best predictors of competition performance in junior female weightlifters. Our findings showed that L-PP and CMJ height variables were the strongest predictors of Sinclair score values (which accounted for 74% of the common variance) with significant correlations between all strength-power variables and Sinclair score ( $r=$ 0.41–0.846). Our previous study involving similar tests on junior male weightlifters indicated that L-MP, CMJ-A, and BF were the best predictors of Sinclair score and these variables accounted for approximately 88% of the common variance [28]. The main difference between these two studies, which were similar in terms of their use of Wingate and vertical jump tests, was that BF made no significant contribution to the regression model in this study on female weightlifters. The findings of this study show a lower prediction of Sinclair score and an insignificant effect of BF in the regression model compared to our previous study, which suggests that strength-power variables are more determinant in male than in female weightlifters. However, other components of weightlifting, such as technique, balance, experience, and tactics could be more effective in female than male weightlifters.

Weightlifting requires exceptional neuromuscular coordination, good kinesthetic perception and agility. Weightlifters must apply lifting techniques quickly and explosively with maximum accuracy for a successful lift [30]. However, competition performance of female weightlifters may be more affected by technical and psychological factors than it is for male weightlifters. Unfortunately, there is a lack of literature comparing the psychological and physiological adaptations of Olympic weightlifters by gender, but a systematic review and meta-analysis showed that both men and women could adapt to resistance training with similar effects in terms of hypertrophy and lower body strength [29]. A wealth of information has indicated that strength-power outputs are the main determinants of weightlifting performance [31, 32]. Therefore, especially for weightlifters who have partial training experience, combining the explosive power of lower body with the correct lifting technique provides a great advantage during lifts [33].

For successful snatch or clean and jerk lifts, the bar must have sufficient height in the second pull phase. Therefore, the most critical factor is power, which requires an optimum balance of strength and speed, to lift the bar to a sufficient height [24]. Power can be defined as work/time or strength $\pm$ speed. Peak (instantaneous) power represents the maximum force generated in a given movement for a short period of time under a given condition and is produced when both strength and speed are at optimum values [34]. Thus, our study’s findings on the Wingate leg peak power variable, which provide information about the power output and the optimum level of time and force for the lower body’s main extensor muscle groups, provide evidence that the use of a Wingate test is suitable for predicting competition performance in female weightlifters.

Our findings, indicating that L-PP and CMJ height variables are the strongest predictors of weightlifting performance, support the existing literature on the importance of lower body extensor muscles for weightlifters. Unfortunately, there are no studies comparing Wingate test variables in men and women, but vertical jump and lift kinematics were frequently investigated in the literature. Carlock et al. [18] showed that the correlations between vertical jump performance variables (force and peak power) and weightlifting performance were not strong in either men or women, but the correlations were slightly higher in the former than the latter. Travis et al. [19] reported that there are significant moderate relationships between vertical jumps (SJ and CMJ) and Sinclair scores in male weightlifters but no such significant relationships in female weightlifters. Hence, prior results suggest weightlifting performance in women is less dependent on strength-power characteristics and that there are some sex-based differences in lift biomechanics [18, 35].

The lifting biomechanics of male and female weightlifters were compared in several studies. Gourgoulis et al. [14] reported that relative peak power is lower in women than men. However, Harbili [36], comparing male and female weightlifters competing in the same weight categories, indicated their peak power outputs were similar. In the general population, muscle mass and strength characteristics are known to be higher in men than in women, but performance differences between the genders is higher in weightlifting athletes than in the general population. This difference has been attributed to female weightlifter’s much shorter history, and thus they and lack many of the advantages that male weightlifters benefit from, such as experience, technical skills, training, and coaches [37, 38]. According to the world championship results that occurred between 1987 and 1998, great improvements were observed in the performance of female weightlifters [39]. In addition, in the 2010 World Weightlifting Championships, the performance of elite female athletes had improved further when compared to previous scores and female weightlifters showed a snatch pattern similar to that of the male weightlifters [15, 18, 20, 28, 40].

Our regression model revealed CMJ was the second strongest predictor of competition performance in junior female weightlifters. Similar movement patterns are observed in knee flexion during the transition phases of CMJ and weightlifting lifts. However, the flexion should be performed quickly enough to allow the storage of recoverable elastic energy and provide stress-reflex facilitation immediately after the concentric contraction of the knee and hip joint extensor muscles [41]. Gourgoulis et al. [14] indicated that women bend their knees less and do so more slowly during the transition from the first to the second pull. However, they also reported that women show significantly greater extension values in the ankle and hip joints; the authors concluded that this is probably because of women’s greater flexibility compared to men. Hence, existing studies showed there are important differences between men’s and women’s weightlifting, thus the generalizations drawn from the studies on males seem insufficient. This study, which uses a large sample size, provides specific evidence on the performance of junior female weightlifters.

The gender gap in weightlifting world records has been around 36.8% ( $\pm$ 6.2) since 1998, when women officially entered the competition. No significant turning points have been detected in women’s weightlifting due to their recent inclusion in the sport. However, the gender gap and the performances of female weightlifters have tended to reach a plateau [42]. In addition, 50.4% of the world records in women’s weightlifting were set by Chinese athletes [43]. Therefore, women’s weightlifting is considered to be a new branch of Olympic sports and its development is ongoing. Further research is needed to identify differences between male and female weightlifters and to describe appropriate testing methods, training strategies, and physical and physiological assessments. One of the important limitations of this study is that the isometric mid-thigh pull test [2, 44, 45], which is one of the most commonly used to evaluate weightlifters, cannot be included in this research because it is not available in our laboratory.

It is clear that generalizations drawn from studies on males are insufficient for female weightlifters. Therefore, to distinguish specific requirements and appropriate measurement methods, further studies are needed on female weightlifters who have been allowed to compete for two to three decades. According to the findings of the present study, to measure the predominant type of explosive effort required in weightlifting, lower-body Wingate and vertical jump tests can be used in female weightlifters.

5. Conclusions

This study suggests that L-PP and CMJ are strong predictors of weightlifting performance, and these tests can be used to monitor weightlifting performance among junior female weightlifters. The key to success in competitive weightlifting is hidden in many complex details. It is clear no single variable can accurately predict competition performance in weightlifting, but a better understanding of the factors contributing to successful competition performance can provide useful information. Although many tests are used to assess performance characteristics of successful weightlifters, more specific approaches are necessary for female weightlifting. The present study provides evidence that L-PP and CMJ variables can be used to determine a female weightlifter’s preparedness for competition. Additionally, these tests can be applied in discriminant analysis to aid the search for skilled young female weightlifters. The regression model presented in this study can help predict female weightlifting performance, and therefore inform the competitive training process and the selection of appropriate competition initiatives. Findings of this study indicate common strength-power tests are the best predictors of a female weightlifter’s Sinclair score, accounting for 74% of the common variance. However, it should not be ignored an important part (26%) may be accounted for by other factors, such as technique, balance, and flexibility.

Author contributions

CONCEPTION: Süleyman Ulupınar.

PERFORMANCE OF WORK: Süleyman Ulupınar and İzzet İnce.

INTERPRETATION OR ANALYSIS OF DATA: İzzet İnce.

PREPARATION OF THE MANUSCRIPT: Süleyman Ulupınar and İzzet İnce.

REVISION FOR IMPORTANT INTELLECTUAL CONTENT: Süleyman Ulupınar and İzzet İnce.

SUPERVISION: Süleyman Ulupınar and İzzet İnce.

Ethical considerations

All participants and their families were informed about the possible risks related to the experimental procedures and gave their informed consent in writing. The Ethics Committee of the Central University approved the study protocol (Ethics Committee meeting date and decision number: 31/08/2019, 254).

Funding

This study did not receive any financial support.

Footnotes

Acknowledgments

There has been no financial support for this work that could have influenced its outcome. The authors would like to thank the athletes for their participation in the study.

Conflict of interest

The authors wish to confirm that there is no conflict of interest associated with this publication and that there has been no financial support for this work that could have influenced its outcome.

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Prediction of competition performance via commonly used strength-power tests in junior female weightlifters

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

2. Methods

2.1 Experimental approach to the problem

2.2 Subjects

2.3 Testing protocols

2.4 Olympic weightlifting performance

2.5 Anthropometric measurements

2.6 Wingate anaerobic tests

2.7 Vertical jump tests

2.8 Handgrip and trunk strength tests

2.9 Isokinetic strength tests

2.10 Statistical analysis

Table 1 Participants’ descriptive and performance characteristics

4. Discussion

5. Conclusions

Author contributions

Ethical considerations

Funding

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
Participants’ descriptive and performance characteristics