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Article

Correlation Between Leg Length and Physical Performance According to Sports Characteristics of Well-Trained Athletes

by
Hyeongtae Kwon
1 and
Daeho Kim
2,*
1
Center for Sport Science in Incheon, Incheon 22234, Republic of Korea
2
Department of Sports Rehabilitation Medicine, Kyungil University, Gyeongsan 38428, Republic of Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(7), 3836; https://doi.org/10.3390/app15073836
Submission received: 31 January 2025 / Revised: 19 March 2025 / Accepted: 25 March 2025 / Published: 31 March 2025
(This article belongs to the Special Issue Advances in Physical Activity for Sport Performance)
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Abstract

:
In addition to various physiological parameters that affect athletes’ performance and outcomes, anthropometric variables are also related to athletic performance. In particular, the length of the lower limbs is closely associated with human mobility and stride length, making it a crucial factor in various movement-based sports. Furthermore, favorable body proportions may vary depending on the sport, and a better understanding of how body proportions affect physical performance across different levels of athletes is needed. Therefore, the purpose of this study is to investigate the relationship between leg length and physical performance by measuring body dimensions (tibia and femur length) for athletes categorized by sports characteristics and performance levels. The study involved 312 athletes from 23 sports, divided into three activity levels. Anthropometric measurements of tibia and femur length were taken, and physical performance tests, including strength, muscular endurance, cardiovascular endurance, agility, explosiveness, flexibility, and anaerobic power, were conducted in the laboratory. The relationships between variables (leg length × physical performance) were analyzed using Pearson’s correlation coefficients. Leg length via activity levels was verified through one-way analysis of variance (ANOVA) testing, including normality and homoscedasticity. Post hoc analysis (Tukey’s HSD test) was used to compare specific differences when significance was found. Statistical significance was accepted at the 0.05 level. As a result, an increase in lower limb length was found to have a relationship with physical performance components, including power (r = 0.302, p = 0.001), agility (r = −0.289, p = 0.001), endurance capacity (r = 0.168, p = 0.005), and anaerobic peak power (r = 0.265, p = 0.001). However, in the LD group, which consisted of athletes in static sports, no significant relationship was observed between lower limb length and physical performance components. However, in the LD group, which included static sports, no significant relationship was found between lower limb length and physical performance components. These findings may serve as foundational data for athlete talent identification and performance prediction.

1. Introduction

As humans age, various parts of the body naturally grow and mature. Athletes, from a young age, select a specific sport and develop physically in conjunction with that sport. During their growth phase, it is expected that athletes’ bodies will respond to the continuous stimuli of the chosen sport, growing in a way that maximizes athletic performance. In addition to various physiological mediators that influence athletic performance and outcomes, anthropometric variables such as body fat and lean mass [1], arm circumference [2], and skinfold thickness [3,4] are also known to be related to athletic performance. The length of the femur and tibia, especially in the lower body, is closely related to human mobility and stride length, making it an important factor in sports that require movement on the ground [5].
Recent studies have reported a positive correlation between the absolute and relative total lengths of the upper leg (femur) and lower leg (tibia) with running performance [6]. This suggests that longer legs require less energy to accelerate leg movements, allowing endurance runners to move more efficiently and economically [7,8,9]. Leg length is an important morphological factor that influences stride length [5,10], and as leg length increases, stride length also increases, potentially enhancing sprint performance [11]. Additionally, Nasrulloh et al. [12] found significant differences in lower body power between volleyball players with longer and shorter leg lengths, indicating that a longer lower body length is associated with greater lower body power. However, according to the data analysis of Bakti et al. [13], a negative correlation of −0.369 was found between leg length and leg explosive power, suggesting that shorter legs may be more capable of generating explosive power. The conflicting results of these studies, which were conducted on athletes, indicate that controversy over the conclusions still remains.
Traditionally, body measurements using tape measures have been employed to assess leg length, but this method has faced issues with ambiguity (low reliability) and technical limitations. Recently, advancements in equipment have introduced alternative methods such as leg length measurement using Dual Energy X-ray Absorptiometry (DEXA) [14] or the use of Magnetic Resonance Imaging (MRI) to measure the length of the femur or tibia and evaluate their relationship with physical performance [15]. However, while DEXA and MRI provide high accuracy and reliability, the high cost of these methods makes them less practical for use in sports and health sciences, where timely data are crucial. Therefore, it is suggested that using specialized body measurement equipment, such as the Martin Anthropometer operated by a trained expert, may offer a more cost-effective and efficient solution for practical applications in the field.
Based on the results of previous studies, it is evident that leg length (thigh, lower leg) is strongly correlated with endurance capacity, sprinting ability, lower body power, and jumping ability [8,12,15,16]. However, prior studies have primarily focused on runners or athletes from a single sport, and most have looked at the total leg length rather than segment-specific measurements. There is a noticeable gap in the research that considers the diversity of sports and the specific characteristics of each different sport, as well as studies exploring the relationship between agility and other physical elements. It is likely that there is an advantageous leg length depending on the nature of each sport, and a deeper understanding of the interaction between leg length and physical performance in athletes across various levels is needed. This study was conducted with the hypothesis that leg length could have an impact on agility, speed, and muscular power.
The results of this study could play a crucial role in identifying potential athletes across various sports, guiding sport selection, and developing effective training programs tailored to specific sports. Therefore, this study aimed to identify the correlation between leg length and physical performance to help develop a deeper understanding of the physical factors influencing athletic performance by classifying athletes based on sports characteristics and dynamic levels [17,18] and to enhance our understanding of the relationship between leg length and physical performance through anthropometric measurements.

2. Materials and Methods

2.1. Participants

This study was conducted at the Center for Sport Science in Incheon. A total of 312 elite athletes (179 males and 133 females) were recruited for the study. Participants were selected from the following sports: archery (n = 5), diving (n = 1), gymnastics (n = 3), judo (n = 15), shooting (n = 13), weightlifting (n = 4), baseball (n = 28), fencing (n = 6), seppak takraw (n = 8), running sprinter (n = 13), Taekwondo (n = 14), tennis (n = 8), wrestling (n = 10), badminton (n = 6), field hockey (n = 11), fin swimming (n = 8), soccer (n = 22), swimming (n = 16), team handball (n = 83), boxing (n = 7), cycling (n = 17), modern pentathlon (n = 5), and rowing (n = 9). Athletes with a history of cardiac, pulmonary, or inflammatory diseases or other medical contraindications were excluded from the study. All participants who agreed to participate were provided with a detailed description of the study, including its purpose and the methods used, in accordance with the ethical standards outlined in the Declaration of Helsinki. Additionally, all participants signed an informed consent form prior to participation. This study was approved by the University’s Institutional Review Board for Human Subjects (1041459-202411-HR-008-01).

2.2. Procedures

The participants (athletes) visited the laboratory as teams based on their respective sports disciplines. During their visit, anthropometric measurements, including lower limb length (tibia length and femur length) and body composition assessments (height, weight, body fat mass, etc.) were conducted. After a sufficient warm-up, tests for basic physical performance (muscular strength, muscular endurance, muscular power, cardiorespiratory endurance, agility, and flexibility) and anaerobic power (peak power) were performed. The collected data were categorized according to the classification table of sports disciplines based on activity level, as outlined by Pelliccia et al. [17] and Mitchell et al. [18]. Participants were grouped into three categories: low dynamic sports (LD; n = 41), moderate dynamic sports (MD; n = 87), and high dynamic sports (HD; n = 184). The participant information is presented in Table 1.

2.2.1. Body Composition and Anthropometric Measurements (Femur and Tibia Length)

Leg length measurements were conducted by trained professionals using a sliding caliper (Martin’s Anthropometer, Japan), as shown in Figure 1. The femoral length was measured as the distance between the tip of the greater trochanter and the distal end of the lateral condyle of the femur. The tibial length was measured as the distance between the proximal end of the lateral condyle and the distal inferior surface of the tibia (lateral malleolus). Anthropometric measurements included body weight (BW), body mass index (BMI), and body fat percentage (%FAT); these measurements were obtained using the body composition analyzer InBody 770 (InBody Co., Seoul, Republic of Korea) using the simultaneous multi-frequencies impedance measurement method. To increase measurement accuracy, alcohol consumption and strenuous exercises on the day before the measurement and any form of drinking or eating 2 h before the measurement was prohibited.

2.2.2. Basic Physical Performance Assessments

The athletes underwent basic physical performance assessments (muscular strength, muscular endurance, muscular power, cardiorespiratory endurance, agility, and flexibility) using sensor-based equipment. To evaluate leg power, the standing long jump and Sargent jump tests [19] were conducted. Lower body agility was assessed using the 10 m shuttle run and side-step test [20,21]. Cardiovascular endurance was measured with the shuttle run test [22], while flexibility was evaluated using the sit-and-reach test [23]. Grip strength was used to assess muscular strength [24].

2.2.3. Anaerobic Test

The Wingate anaerobic test (WAnT) was used following experiments performed by Castañeda-Babarro [25]. The WAnT was performed on a cycle ergometer (Monark 824 E, Monark, Sweden) equipped with a photoelectric sensor for recording 1.0 kg resistance baskets and flywheel revolutions. Data for each 30 s WAnT were collected using POWER software (SMI, St. Cloud, MN, USA) and an IBM-compatible microcomputer. Each participant completed a self-selected stretching exercise and a five-minute cycle at the ergometer without applying a time limit. At the end of the 1 min warm-up, each participant performed an “all-out” sprint for 4 to 5 s to simulate the actual test. Before starting the WAnT, the resistance for each participant was calculated using a body weight of kilograms multiplied by 7.5% for males and 5% for females, and the determined amount was placed in the basket. At the start of the test, the assistant lifted the resistance basket, and no resistance was applied to the flywheel; each participant was instructed to begin pedaling to reach the maximum rpm at the end of the 5 s countdown. The resistance basket was released, and data collection began, subsequently ending after 30 s [26]. Among the test results, we analyzed peak power data in relation to leg length.

2.3. Statistical Analysis

All values are presented as means with standard deviations. GraphPad Prism 10.0 (GraphPad Software Inc., San Diego, CA, USA) was used for the statistical evaluation and preparation of graphs. Data analysis was conducted with the Statistical Package for the Social Sciences, version 23.0 (IBM SPSS Statistics for Windows, Version 23.0: IBM Corp., Armonk, NY, USA). The relationships among variables (leg length × physical performance) were analyzed using Pearson’s correlation coefficients. Leg length by activity levels were verified through one-way analysis of variance (ANOVA) testing, including normality and homoscedasticity. Post hoc analysis (Tukey’s HSD test) was used to compare specific differences (leg length between groups) when significance was found. Statistical significance was accepted at the 0.05 level.

3. Results

The results of the analysis on leg length differences by sport type revealed that the absolute lengths of the tibia and tibia + femur were significantly shorter in the LD group compared to the MD group (p = 0.019; p = 0.011, respectively). However, no significant differences were observed between the groups when leg length was expressed as a relative value to height (Table 2).
A significant correlation was observed between the tibia length relative to height and physical performance variables, including muscular strength, muscular endurance, muscular power, agility, flexibility, and lower limb anaerobic peak power (p < 0.05 for both).
A significant correlation was found between femur length relative to the height and physical performance variables, specifically muscular power and flexibility (p < 0.05 for both).
A significant correlation was observed between the tibia + femur length relative to the height and physical performance variables, including muscular strength, muscular power, agility, flexibility, cardiorespiratory endurance, and lower limb anaerobic peak power (p < 0.05 for both) (Table 3; Figure 2).
In the correlation analysis between relative leg length by sport group and physical performance, tibia length showed a stronger correlation with agility (10 m shuttle run test) in the HD group. On the other hand, femur length exhibited a higher correlation with muscular power (standing long jump test) in the MD group compared to the other groups (Table 3; Figure 3).

4. Discussion

The purpose of this study was to measure lower limb length (tibia, femur, and tibia + femur) using anthropometric methods in elite athletes and investigate the relationships between these values (both absolute and relative to height) and physical performance components. Additionally, the athletes were categorized based on the activity level classification table by Pelliccia et al. [17] and Mitchell et al. [18] for a more detailed examination.
The main findings of this study indicate that, regardless of sport type, longer leg lengths (tibia, femur, and tibia + femur; both absolute and relative to height) are significantly correlated with muscular power, agility, cardiorespiratory endurance, muscular strength, and lower limb anaerobic peak power. In terms of group differences, the MD group showed the highest correlation between tibia length and muscular power; the HD group demonstrated the strongest correlation between tibia length and forward–backward agility; and the MD group exhibited the highest correlation between tibia + femur length and lateral agility.
Thus, the results of this study provide further evidence that longer leg lengths, as measured by anthropometric methods, are positively related to various physical performance components in well-trained athletes across different sports. This supports the notion that longer legs may be advantageous for improving performance and athletic ability.
Although several studies have described various anthropometric variables in elite athletes [27,28,29,30], few have focused on the ratios of different anthropometric measurements [6,31], which could be important characteristics of athletic performance.
In our study, a positive correlation was observed between the total leg length (tibia + femur) and the shuttle run cardiorespiratory endurance test in all athletes (r = 0.168, p = 0.005). This finding is somewhat consistent with previous studies on high-level East African long-distance runners, where relatively longer legs were found to be advantageous for endurance performance [6]. Morrison et al. [32] reported a positive relationship between tibia length and Achilles tendon length, suggesting that longer tibia could contribute to better running performance. Furthermore, since leg length is related to stride length [5], it is proposed that shorter legs may require a lower work level, contributing to more efficient running performance [7]. Therefore, the total length of the femur and tibia plays a crucial role in achieving excellent running performance by improving endurance economy.
Muscular strength and power, including better muscle function, are critical elements for athletes. These abilities are not only the first step in maintaining excellent performance but are also essential for reducing the risk of sports injuries [33,34]. Additionally, the ability to rapidly change the speed and direction of the body’s center of mass, known as agility, is a fundamental skill in most sports [35]. In this context, the ratio of leg length may be useful in reducing the inertial moment of the legs and the action of the hip flexors during phases when the body needs to move quickly and powerfully [36]. Therefore, this advantageous structure may contribute to the economic sprinting ability (muscular power and agility) of sprinters, potentially helping them achieve superior long-distance sprinting performance.
Moreover, previous studies have confirmed that the larger the thigh muscles, including the quadriceps and hamstrings, the better the performance of sprinters in events such as the 100 m sprint [1,3,7]. This suggests that not only structural differences but also differences in muscle mass should be considered. However, since this study measured lower limb length using anthropometric methods, the muscle mass of the athletes’ lower limbs was not assessed.
In this study, the analysis of group differences revealed that the correlation between tibia length and agility (through the 10 m shuttle run–sprint and turn test) was stronger in the HD group (r = −0.455, p = 0.001) compared to the other groups (LD: r = 0.117, p = 0.497, MD: r = −0.028, p = 0.808). This suggests that the HD group, which consists of athletes from sports requiring frequent forward–backward directional changes (such as soccer, hockey, and handball), may benefit from longer tibia in terms of agility during offensive and defensive maneuvers.
In addition, for another agility factor (side-step test—lateral direction change), the correlation between femur length and performance was significantly higher in the MD group (r = 0.405, p = 0.001) compared to the other groups (LD: r = 0.086, p = 0.593, HD: r = 0.014, p = 0.855). This suggests that athletes in sports that involve lateral movements, such as tennis and baseball, may benefit from longer femora for improved agility during lateral direction changes.
In the analysis of group differences, the correlation between femur length and performance in muscular power or explosiveness (standing long jump) was significantly higher in the MD group (r = 0.453, p = 0.001) compared to the other groups (LD: r = 0.075, p = 0.642, HD: r = 0.047, p = 0.523). This suggests that athletes in sports requiring explosive, short bursts of performance, such as sprinting, baseball, and fencing, may benefit from longer femora for more effective power generation.
In the LD group, no significant correlations were observed with any physical performance factors. This lack of correlation is likely due to the nature of the sports with lower activity levels (such as shooting, archery, and diving), which may have a limited impact on the physical attributes measured in this study.
In addition to physical structure, a combination of performance indicators such as speed, strength, endurance, agility, and flexibility can have a positive impact on an athlete’s performance. Physical characteristics vary according to physiological abilities, which significantly influence athletic performance. To achieve satisfactory results, physical performance is crucial in the context of sports [37]. Future research should focus on the notable correlation between leg length and physical attributes such as power and agility in moderate dynamic sports groups, including baseball, fencing, sprinting, tennis, and wrestling. It would be highly meaningful to investigate the biomechanical and physiological mechanisms underlying this correlation through in-depth measures.

5. Conclusions

In conclusion, a relationship between relative lower limb length (tibia, femur, and tibia + femur) and physical performance was observed. As the lower limb length increases, stride length also increases, contributing to improved performance, including efficient cardiovascular endurance. Furthermore, tibia length was found to be related to forward–backward agility, while the combined length of the tibia and femur was associated with muscular power and anaerobic power. These findings may serve as foundational data for talent identification and performance prediction in athletes. This can be considered valuable as foundational data can be used when selecting athletes for sports where lower body movement is crucial. Additionally, as a future study, we plan to investigate how differences in leg length according to gender affect athletic performance and the relationship between this and physiological variables.

Author Contributions

H.K. and D.K. were responsible for the conception and design of the study. H.K. and D.K. were involved in the analysis and/or interpretation of data. H.K. and D.K. were responsible for the first drafts of the manuscript, which was revised critically for important intellectual content. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Kyungil University for Human Subjects (1041459-202411-HR-008-01).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data cannot be provided due to privacy or ethical restrictions.

Conflicts of Interest

The authors declare no conflict of interest.

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Applsci 15 03836 g001
Figure 1. The measurement position of upper leg length and lower leg length.
Figure 1. The measurement position of upper leg length and lower leg length.
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Figure 2. Relationships between the relative leg lengths and physical performance. (A) Tibia length; (B) femur length; and (C) tibia + femur length. The leg lengths were normalized with body height to calculate relative leg lengths, which were expressed as percentages (i.e., the % of body height).
Figure 2. Relationships between the relative leg lengths and physical performance. (A) Tibia length; (B) femur length; and (C) tibia + femur length. The leg lengths were normalized with body height to calculate relative leg lengths, which were expressed as percentages (i.e., the % of body height).
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Figure 3. Relationships between relative leg lengths and physical performance by group. (A) Tibia length; (B) femur length. The lengths of the leg were normalized with body height to calculate relative leg lengths, which were expressed as percentages (i.e., the % of body height).
Figure 3. Relationships between relative leg lengths and physical performance by group. (A) Tibia length; (B) femur length. The lengths of the leg were normalized with body height to calculate relative leg lengths, which were expressed as percentages (i.e., the % of body height).
Applsci 15 03836 g003
Table 1. The characteristics of the subjects and their classification according to activity level.
Table 1. The characteristics of the subjects and their classification according to activity level.
VariableLow Dynamic Sports
(LD; n = 41)		Moderate Dynamic Sports
(MD; n = 87)		High Dynamic Sports
(HD; n = 184)		Total Athletes
(N = 312)
Age (years)17.46 ± 0.6017.87 ± 1.3418.04 ± 1.9317.92 ± 1.67
Height (cm)166.94 ± 7.37171.36 ± 8.62169.41 ± 7.33169.63 ± 7.81
Weight (kg)67.89 ± 15.8165.85 ± 15.7468.54 ± 12.9267.70 ± 14.15
BMI (kg/m2)24.20 ± 4.4322.37 ± 4.5823.77 ± 3.3923.43 ± 3.95
Career (years)7.46 ± 0.607.55 ± 1.537.94 ± 1.487.84 ± 1.73
I. Low static BaseballBadminton
FencingField hockey
Seppak takraw
Running (sprint)
Taekwondo
Tennis
II. Moderate static Fin swimming
Diving Soccer
Gymnastics Swimming
Judo Team handball
Shooting
III. High staticWeightliftingWrestlingBoxing
Cycling
Modern pentathlon
Rowing
Values are presented as Mean ± SD, Abbreviations: BMI: body mass index. The lengths of the leg were normalized with body height to calculate relative leg lengths, which were expressed as percentages (i.e., the % of body height).
Table 2. Differences in leg length according to activity level.
Table 2. Differences in leg length according to activity level.
VariableGroups
LD (n = 41)MD (n = 87)HD (n = 184)Fp-Value
absolute leg length
tibia (cm)34.80 ± 2.86 b36.35 ± 2.93 a35.86 ± 3.093.6950.026 *
femur (cm)42.84 ± 3.0544.17 ± 3.7243.69 ± 2.712.6550.072
femur + tibia (cm)77.63 ± 4.93 b80.52 ± 5.90 a79.55 ± 4.974.2440.015 *
relative leg length
tibia, % of body length20.82 ± 1.1021.20 ± 1.1021.15 ± 1.261.4950.226
femur, % of body height25.65 ± 1.2825.75 ± 1.2325.78 ± 1.010.2400.787
femur + tibia, % of body height46.47 ± 1.4146.95 ± 1.4846.93 ± 1.401.8690.156
LD: low dynamic sport; MD: moderate dynamic sport; HD: high dynamic sport. Significance (p < 0.05) is denoted by the following: a: relative to LD, b: relative to MD. Differences between groups: *: p < 0.05.
Table 3. Correlation coefficients between leg length and physical performance.
Table 3. Correlation coefficients between leg length and physical performance.
VariableSU
(rp)		SLJ
(cm)		SJ
(cm)		10mRT
(s)		SS
(rp)		20mSRT
(rp)		SR
(cm)		GS
(kg)		PP
(w/kg)
absolute leg length
tibia (cm) −0.1090.430 **0.433 **−0.385 **0.147 *0.212 **−0.365 **0.592 **0.506 **
femur (cm) 0.0530.479 **0.419 **−0.315 **0.0910.243 **−0.271 **0.495 **0.504 **
femur + tibia (cm) −0.0330.527 **0.493 **−0.406 **0.138 *0.266 **−0.368 **0.629 **0.581 **
relative leg length
tibia, % of body lengthALL−0.150 *0.190 **0.215 **−0.256 **0.135 *0.098−0.337 **0.331 **0.217 **
LD−0.0180.2150.098−0.0250.1170.100−0.1390.2930.057
MD−0.1290.1730.116−0.0280.214 *0.035−0.235 *0.1520.226
HD−0.207 **0.166 *0.272 **−0.455 **0.1450.079−0.439 **0.434 **0.338 **
femur, % of body heightALL0.1060.184 **0.115 *−0.0890.0380.104−0.168 **0.0740.113
LD−0.0980.0750.169−0.2680.0860.143−0.406 **0.0660.288
MD0.335 **0.453 **0.412 **−0.368 **0.405 **0.204−0.0790.253 *0.358 **
HD0.0630.047−0.0900.249 **0.0140.015−0.152 *−0.061−0.051
femu + tibia, % of body heightALL−0.0450.302 **0.269 **−0.289 **0.145 *0.168 **−0.412 **0.335 **0.265 **
LD−0.1030.2370.231−0.2650.1710.210−0.480 **0.2890.308
MD0.1840.503 **0.426 **−0.317 **0.493 **0.196−0.239 *0.322 **0.458 **
HD−0.1450.183 *0.180 *−0.238 **0.1450.085−0.504 **0.347 **0.248 **
SU: sit-up test; SLJ: standing long jump; SJ: Sargent jump test; 10mRT: 10 m round trip; SS: side-step test; 20mSRT: 20 m shuttle run; SR: Seated Reach; GS: grip strength; PP: peak power. *: p < 0.05; **: p < 0.01.
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Kwon, H.; Kim, D. Correlation Between Leg Length and Physical Performance According to Sports Characteristics of Well-Trained Athletes. Appl. Sci. 2025, 15, 3836. https://doi.org/10.3390/app15073836

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Kwon H, Kim D. Correlation Between Leg Length and Physical Performance According to Sports Characteristics of Well-Trained Athletes. Applied Sciences. 2025; 15(7):3836. https://doi.org/10.3390/app15073836

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Kwon, Hyeongtae, and Daeho Kim. 2025. "Correlation Between Leg Length and Physical Performance According to Sports Characteristics of Well-Trained Athletes" Applied Sciences 15, no. 7: 3836. https://doi.org/10.3390/app15073836

APA Style

Kwon, H., & Kim, D. (2025). Correlation Between Leg Length and Physical Performance According to Sports Characteristics of Well-Trained Athletes. Applied Sciences, 15(7), 3836. https://doi.org/10.3390/app15073836

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