Unveiling the Biomechanical Insights: Motor Control Shifts Induced by Shoe Friction Adjustments and Their Impact on Defensive Slide, Crossover Dribbling, and Full Approach Jump in Basketball

Abstract

This study endeavors to explore the intricate interplay between the fundamental skills of basketball—defensive slide, crossover dribbling, and full approach jump—and the shoe outsole friction coefficient, with the overarching goal of advancing our comprehension regarding the pivotal role of footwear in athlete performance. Employing a comprehensive methodology that integrates 3D motion capture, force platform dynamometry, and biomechanical modeling, the study seeks to quantify the inherent motor control intricacies associated with these fundamental skills. Data collection involved 12 varsity players, and the research systematically assesses the influence of the shoe friction coefficient on both skill quality and injury risk, utilizing a set of 13 parameters for evaluation. The findings unveil that, with an increased friction coefficient, the following changes occur: for the defensive slide, we observed decreased contact time (p < 0.05), boosted medio–lateral impulse (p < 0.05), and lowered ankle torque (p < 0.01); for crossover dribbling, we observed increased anterior–posterior impulse (p < 0.05) and ankle torque (p < 0.05); for the full approach jump, we observed decreased contact time (p < 0.05) and increased jump height (p < 0.05). Generally, the equal increment in the shoe outsole friction coefficient did not result in equal changes in the selected parameters of motor skill control, indicating a non-linear relationship between the performance quality of essential basketball skills and the shoe friction coefficient. The results suggest the potential existence of an optimal value for skill execution. Notably, the study identifies that, while an augmentation in the friction coefficient enhances specific skill aspects, there is a discernible saturation point, signifying diminishing returns. This investigation makes a substantial contribution to our understanding of the precise impacts of shoe friction coefficients on basketball skills, thereby prompting considerations for the judicious selection of optimal friction coefficients and advocating for possible personalized footwear recommendations based on individual biomechanical profiles.

1. Introduction

The mastery of the fundamental skills of basketball is paramount in the dynamic and fast-paced environment of basketball gameplay. Defensive slide, crossover dribbling, and full approach jump are foundational techniques that directly impact an athlete’s overall performance on the court [1]. Defensive slide is a fundamental defensive maneuver crucial for maintaining defensive positioning, preventing opponents from penetrating the defense, and facilitating effective team play. The crossover dribbling, on the other hand, is an essential offensive skill that allows players to navigate through defenders with agility and control, creating opportunities for scoring or setting up plays. Meanwhile, the full approach jump is a fundamental component of both offensive and defensive play, influencing shooting accuracy, rebounding, and shot-blocking capabilities [1]. Mastering these skills enhances a player’s versatility, crucially contributing to their overall efficacy and strategic value in the game.

The quality of the fundamental skills of basketball is intricately connected to the characteristics of an athlete’s footwear, and shoe friction is among the pivotal factors. Recognized as the resistive force between bodies in contact during relative motion, friction stands as a fundamental phenomenon with profound implications for human motor behavior and the intricate control mechanisms governing human movement. This intricate interplay between surfaces and the resultant frictional force plays a central role in shaping the dynamics of diverse activities, extending from everyday motions to specialized athletic performances [2]. Understanding the motor control shifts associated with friction alteration holds paramount importance across various disciplines, including sports biomechanics, sports engineering, and rehabilitation. Therefore, the study of friction extends beyond mechanics, encompassing the unraveling of complexities inherent in human motor control. As the human body engages with diverse motor skills in sports, the modulation of frictional forces becomes a critical factor influencing the precision, efficiency, and adaptability of movement [3,4].

In the context of basketball, defensive slide, crossover dribbling, and full approach jump highlight the importance of shoe friction [5,6]. Defensive slide, requiring quick lateral movements, necessitates an appropriate level of shoe friction to ensure effective traction on the court surface, facilitating swift changes in direction without compromising stability. Similarly, the crossover dribbling maneuver demands optimal shoe friction for maintaining control during precise footwork and sudden changes in motion direction. Additionally, in a full approach jump, firm contact between shoe and the playing surface is crucial for power generation, directly influencing jump performance. Understanding and optimizing shoe friction concerning these fundamental skills are essential for athletes and coaches seeking to maximize performance and minimize injury risks on the basketball court.

The current study aims to contribute to understanding the critical role of the basketball shoe friction coefficient in athlete performance by elucidating their impact on movement dynamics and motor skill control. Basketball shoes, as core athletic equipment, play a significant role in enhancing athletes’ performance, enabling various movements such as stops, accelerations, jumps, and slides within confined time and space [1]. The advanced state of basketball techniques emphasizes even subtle advantages in shoe performance, underscoring its significance to athletic performance [7].

A systematic review in 2022 [7] categorized advancements in shoe structure based on modifications, including cushioning, midsole hardness, collar height, outsole traction component, forefoot bending stiffness, and shoe mass. These modifications were found to influence lower limb biomechanics, correlating improved cushioning or softer midsoles with enhanced impact attenuation, elevated shoe collars with improved ankle stability, heightened shoe traction and forefoot bending stiffness with enhanced performance in jumps, sprints, and cuts, and reduced shoe mass with improved jumping and cutting performances. Despite these advancements, there remains a lack of investigations into the diverse influences of various shoe friction coefficients specific to basketball shoes. The systematic review identified only two studies. One study emphasized the significant impact of shoe slip resistance on athletes’ technical prowess, including improved performance in lateral cutting maneuvers when the coefficient of friction increased [8]. Another study underscored traction as a pivotal factor influencing various technical movements [9]. In summary, athletes wearing shoes with higher traction exhibit enhanced athletic performance, although specific technical movements may impose varied requirements on traction.

Notably, previous studies using various shoes with different friction coefficients ranging from 0.8 to 1.2 [7] resulted in findings from the joint effects of multiple shoe structural factors, and the main effect of the shoe friction coefficient remains unknown. This unknown is highly relevant for basketball players; on one side, basketball skills are open-control skills [10,11], requiring players to estimate opponents’ intentions through body movement direction and perform sudden cut movements or jumps for defense, shooting, blocking, or facilitating effective team play, necessitating high friction for dynamic balancing in extremely dynamic situations. On the other side, high friction could increase the risk of injury [12,13,14]. Therefore, this study aims to investigate the intricate relationship between the fundamental skills of basketball (i.e., defensive slide, crossover dribbling, and full approach jump) and the shoe friction coefficient. The overarching goal is to enhance our understanding of how changes in shoe friction coefficient influence the execution of these fundamental skills in the dynamic and fast-paced environment of basketball gameplay. We hypothesize that an optimal value of the shoe friction coefficient exists for the maneuvers of these skills, indicating that a non-linear influence exists between the fundamental skills of basketball and the shoe friction coefficient. Our hypothesis would indicate that varying shoe friction coefficients would have distinct effects on athletes’ technical prowess in trained motor skills on the basketball court. In summary, this study seeks to elucidate the nuanced interplay between the fundamental skills of basketball and athlete footwear friction characteristics. The proposed hypotheses aim to provide biomechanical insights into optimizing shoe characteristics for athletes and coaches, ultimately contributing to enhanced performance and injury risk mitigation in the context of basketball.

2. Materials and Methods

2.1. Participants

A total of twelve male athletes belonging to the varsity basketball team at Jimei University were recruited as participants for the research.

Table 1. Participant demographic information.

Age (Years)	Height (cm)	Weight (kg)	Training (Years)	Level 1
22.1 ± 2.5	178.4 ± 3.5	65.3 ± 5.3	6.5 ± 1.7	2

¹ Chinese National Certificate System for Athlete Performance Level. (1) professional; (2) pre-professional; (3) individuals who attained a placement within the highest six positions in competitions held at the county level or above [15].

provides an overview of their physical attributes and relevant experiences. Inclusion criteria necessitated that participants uphold a regular training regimen, involving a minimum of three training sessions per week, totaling approximately 9 h per week. Additionally, participants were required to maintain a high standard of athletic performance, showcasing proficiency in technical skills and consistent execution during the investigation period. Exclusion criteria dictated that participants should not have a history of lower limb injuries within the six months leading up to the experiment. The participants were thoroughly briefed on the experimental procedures and presented with informed consent forms. Prior to the initiation of the study, all participants formally signed the consent forms, signifying their voluntary agreement to participate in the research.

2.2. Manipulating Shoe Friction Coefficients and Test Protocol

To minimize compounding factors related to shoe structure, all test shoes were standardized, with the only variation being the shoe outsole traction/friction coefficient. Previous studies have demonstrated that the shoe friction coefficient can range from 0.8 to 1.2 [7,8]. Therefore, three manipulation levels, namely 0.8, 1.0, and 1.2, were implemented in this study. To ensure a consistent manipulation of the shoe friction coefficient, the research team collaborated with 361 Degrees International Ltd. [16] to achieve the required technical specifications. In response to the study’s needs, the company manufactured three pairs of test shoes for each participant (Figure 1). This industry-standardized procedure guaranteed that the research could fulfill its intended objectives.

The tests were conducted in the training gymnasium of the university, which is floored with international standard sports wooden flooring (floor friction coefficient ranges from 0.4 to 0.6), produced by CONNOR Sports Wooden Flooring, Bedford, TX, USA [17]. As such, the gym provided a competition-like environment for the study (Figure 2a). Prior to the formal evaluation, each participant underwent an individualized warm-up routine tailored to their specific needs, ensuring optimal physical readiness. Following the warm-up, participants were granted an opportunity to perform personal trials of the test skills. This familiarization step allowed subjects to acclimate to the testing environment, facilitating a more natural expression of their skills. Notably, this initial phase also enabled the researchers to obtain a baseline understanding of the participants’ intrinsic abilities, serving as a reference for subsequent analyses. For the actual test, each subject executed three defensive slides, three crossover dribbles, and three full approach jumps. To mitigate the potential effects of fatigue, personalized rest intervals were implemented between trials, promoting consistent performance and reliable data collection.

2.3. Synchronized Data Collection and Biomechanical Modeling

The application of 3D motion capture and biomechanical modeling represents a reliable and widely employed methodology for elucidating the motor control intricacies inherent in various sports skills, specifically through kinematic quantification [18,19,20,21]. This approach, complemented by the measurement of ground reaction forces, facilitates the determination of joint forces and moments/torques—commonly referred to as kinetic quantification—based on 3D joint kinematics, ground reaction forces, and segmental inertial properties [22], as established by inverse dynamic analysis [3,4]. In this study, synchronized data collection from a 3D motion capture system and a ground reaction force platform was implemented to collect data from the 12 varsity players.

The 3D motion capture employed a twelve-camera VICON V8 motion capture system (VICON Motion Systems, Oxford Metrics Ltd., Oxford, UK) operating at a frequency of 200 frames per second, while the synchronization of ground reaction force measurement (a function in VICON system) was achieved using two KISTLER platforms (model 9287C, 900 × 600 × 200 mm, KISTLER AG, Winterthur, Switzerland) operating at 1000 Hz (Figure 2a). A prevalent practical simplification in biomechanical quantifications of running, cutting, and jumping activities involves the utilization of lower limb modeling rather than full-body modeling [23,24,25]. In alignment with this standard practice, the current study adopted lower limb modeling. Eighteen reflective markers (diameter = 14 mm) were utilized in constructing a 7-segment biomechanical model, outlining segments such as the pelvis, thighs, shanks, and feet. This model is one of the human body models provided by the VICON system. For this model, the required 18 markers were placed on the anterior superior iliac crest, the posterior superior iliac crest, the lateral condyle of the tibia, the lateral malleolus of the fibula, the calcaneal tuberosity, the tuberosity of the fifth metatarsal, and the head of the hallux, as well as on the upper and lower leg. The four markers on the upper and lower leg specifically contributed to determining segmental rotations, as they did not influence segmental translations and did not necessitate specific anatomical positioning. Stringent calibration procedures were executed in strict adherence to established VICON guidelines, resulting in minimal calibration residuals and a precision level within 1.5 mm. Additionally, all trials were contemporaneously recorded by a CASIO video camcorder (100 Hz) in conjunction with the VICON system to obtain visual references for performance assessment. Figure 2b,c illustrate the synchronized data collection with video reference.

2.4. Data Processing, Parameter Selection, and Statistical Analysis

The assessment comprised 9 trials per participant, resulting in a total of 108 trials. The acquired raw data underwent processing using a five-point smoothing filter (supplied by VICON software). This processed dataset provided critical three-dimensional coordinates of the 18 markers. Subsequently, the processed 3D coordinates were used to construct the 7-segment biomechanical model [3,26] for kinematic quantification of the three skills. The data from the synchronized ground reaction force (GRF) measurement were used for kinetic quantification, including performing the inverse dynamic analysis of the 7-segment model by using VICON provided software.

Proficiency in the three specified basketball skills relies heavily on the agility, speed, and leg-power-generation capacity of players. Agility refers to the ability to quickly and accurately change body motion direction in response to competitive situations [27,28]. Because agility movements involve rapid acceleration, there is an increased risk of joint and soft tissue injuries [28]. It is important to note that lateral movements, like defensive slides and crossover dribbling, elevate foot inversion/eversion torque, thus heightening the risk of injury [7,29,30]. Therefore, injury prevention is relevant in sport performance and belongs to part of performance analysis [4]. Considering the unique control requirements of these skills and aiming to quantitatively assess these abilities without overloading (i.e., injury prevention), the following parameters were selected from data collection: For defensive slide (lateral movement only)—performing/contact time and lateral impulse acquired through ground reaction force measurement; lateral stride length during defensive sliding derived from 3D motion data; average inversion/eversion torque obtained through biomechanical modeling (inverse dynamic analysis). For crossover dribbling—performing/contact time; anterior–posterior impulse associated with sudden braking movements; medio–lateral impulse relevant to cutting tasks; motion direction change (aiming to be as close to a 90-degree angle as possible) determined based on 3D motion data; average inversion/eversion torque. For full approach jump—performing/contact time; anterior–posterior impulse related to sudden break movement; vertical impulse related to jumping; jumping height determined by 3D motion data. To mitigate the confounding effect of body weight on the quantification of skills, the research findings regarding impulse and torque were normalized by the subjects’ body weight, i.e., impulse/body weight and torque/body weight.

For statistical analysis, the mean and standard deviations (SD) were calculated for the selected parameters. Descriptive statistics (mean ± SD) were used to illustrate the characteristics of these parameters. Due to the small sample size, the Shapiro–Wilk test was first performed to test the normality of the collected data. If normality was found, one-way ANOVA was conducted to detect changes in control patterns induced by the shoe friction coefficient. All statistical analyses were performed using IBM SPSS Statistics 23 (IBM Japan, Tokyo, Japan), and the significance level was set at p = 0.05.

3. Results

The Shapiro–Wilk test confirmed the normality of the collected data from the three fundamental basketball skills (p > 0.10).

Table 2. Mean and standard deviation (mean ± SD) of the selected parameters associated with the defensive slide.

Shoe	Contact Time (ms)	ML Impulse (BWs)	Lateral Stride Length (m)	Ankle Torque (Nm/kg)
S1	0.55 ± 0.17	109.43 ± 15.69	0.80 ± 0.15	2.19 ± 0.37
S2	0.51 ± 0.15	130.71 ± 15.50	0.94 ± 0.18	2.03 ± 0.31
S3	0.48 ± 0.12	131.48 ± 13.93	1.00 ± 0.19	1.45 ± 0.21

S1: Shoe outsole with a friction coefficient of 0.80 ± 0.05. S2: shoe outsole with a friction coefficient of 1.00 ± 0.05. S3: Shoe outsole with a friction coefficient of 1.20 ± 0.05. ML: medio–lateral direction. BW: body weight.

and

Table 3. Significance identified by p-value obtained from ANOVA test associated with the defensive slide (*: significant, p ≤ 0.05; **: highly significant, p ≤ 0.01).

	Contact Time (ms)	ML Impulse (BWs)	Lateral Stride Length (m)	Ankle Torque (Nm/kg)
S1–S2	0.02 *	0.04 *	0.03 *
S1–S3	0.00 **	0.03 *	0.00 **	0.00 **
S2–S3	0.04 *			0.00 **

S1: Shoe outsole with a friction coefficient of 0.80 ± 0.05. S2: Shoe outsole with a friction coefficient of 1.00 ± 0.05. S3: Shoe outsole with a friction coefficient of 1.20 ± 0.05. ML: medio–lateral direction. BW: body weight.

present the results of the defensive slide. The study has shown that, generally, the equal increment in the shoe outsole friction coefficient did not result in equal changes in the selected parameters of motor skill control, indicating a non-linear relationship between the performance quality of essential basketball skills and the shoe friction coefficient. Notably, the contact time exhibited a significant decrease (p < 0.05) as the shoe outsole friction coefficient increased, indicating faster movement. Concerning medio–lateral impulse, a significant increase (p < 0.05) was observed as the friction coefficient increased from 0.8 to 1.0; however, no further significant change was noted when the coefficient increased from 1.0 to 1.2. A similar trend was observed in lateral stride length, mirroring the results of medio–lateral impulse. Regarding ankle torque, an increase in the shoe outsole friction coefficient corresponded to a decrease in torque, suggesting a safer movement pattern. Notably, the change was statistically significant (p < 0.01) only between the friction coefficients of 1.0 and 1.2.

The results for crossover dribbling are presented in

Table 4. Mean and standard deviation (mean ± SD) of the selected parameters associated with the crossover dribbling.

Shoe	Contact Time (s)	AP Impulse (BWs)	ML Impulse (BWs)	Direction Change (°)	Ankle Torque (Nm/kg)
S1	0.25 ± 0.03	62.69 ± 13.71	98.06 ± 12.97	44.8 ± 12.8	3.01 ± 0.32
S2	0.24 ± 0.03	76.83 ± 14.37	101.65 ± 15.11	50.2 ± 11.3	3.32 ± 0.35
S3	0.25 ± 0.03	80.97 ± 15.02	118.72 ± 20.55	50.7 ± 10.7	3.68 ± 0.27

S1: Shoe outsole with a friction coefficient of 0.80 ± 0.05. S2: Shoe outsole with a friction coefficient of 1.00 ± 0.05. S3: Shoe outsole with a friction coefficient of 1.20 ± 0.05. A-P: anterior–posterior direction. ML: medio–lateral direction. BW: body weight.

and

Table 5. Significance identified by p-value obtained from ANOVA test associated with the crossover dribbling (*: significant, p ≤ 0.05; **: highly significant, p ≤ 0.01).

Shoe	Contact Time (s)	AP Impulse (BWs)	ML Impulse (BWs)	Direction Change (°)	Ankle Torque (Nm/kg)
S1–S2		0.03 *			0.02 *
S1–S3		0.00 **	0.01 *		0.00 **
S2–S3			0.03 *		0.03 *

S1: Shoe outsole with a friction coefficient of 0.80 ± 0.05. S2: Shoe outsole with a friction coefficient of 1.00 ± 0.05. S3: Shoe outsole with a friction coefficient of 1.20 ± 0.05. A-P: anterior–posterior direction. M-L: medio–lateral direction. BW: body weight.

, revealing intriguing insights into the relationship between the shoe outsole friction coefficient and control parameters associated with this skill. Similar to the defensive slide, the linear change in the shoe outsole friction coefficient demonstrated non-linear effects on the selected parameters of the skill control. The temporal duration of skill execution, as indicated by contact time, demonstrated minimal responsiveness to variations in the coefficient. Concerning the anterior–posterior impulse, which is responsible for deceleration in forward motion, a notable and statistically significant increase (p < 0.05)—implying a quicker cessation of motion—was observed as the friction coefficient increased from 0.8 to 1.0. However, there was no subsequent significant alteration with a further increase from 1.0 to 1.2. Conversely, the medio–lateral impulse, related to sudden direction change or cutting movement, showed no significant change (p > 0.05) as the coefficient increased from 0.8 to 1.0, but a significant increase was noted with a further coefficient increase from 1.0 to 1.2. The direction change, although required to be 90°, resulted in approximately 45° for the coefficient of 0.8 and about 50° for the other two coefficients, with statistically non-significant changes (p > 0.05). Ankle torque exhibited a significant increase (p < 0.05) as the shoe outsole friction coefficient increased, suggesting an elevated risk of injury with higher coefficients.

Table 6. Mean and standard deviation (mean ± SD) of the selected parameters associated with the full approach jump.

Shoe	Contact Time (s)	AP Impulse (BWs)	Vert Impulse (BWs)	Jump Height (cm)
S1	0.22 ± 0.07	1.38 ± 0.23	491.71 ± 27.08	73.3 ± 4.0
S2	0.20 ± 0.05	1.66 ± 0.23	498.59 ± 23.02	75.4 ± 4.3
S3	0.19 ± 0.03	1.66 ± 0.26	500.20 ± 26.55	75.3 ± 4.6

S1: Shoe outsole with a friction coefficient of 0.80 ± 0.05. S2: Shoe outsole with a friction coefficient of 1.00 ± 0.05. S3: Shoe outsole with a friction coefficient of 1.20 ± 0.05. A-P: anterior–posterior direction. Vert: vertical direction. BW: body weight.

and

Table 7. Significance identified by p-value obtained from ANOVA test associated with the full approach jump (*: significant, p ≤ 0.05; **: highly significant, p ≤ 0.01).

	Contact Time (ms)	AP Impulse (BWs)	Vert Impulse (BWs)	Jump Height (cm)
S1–S2	0.04 *	0.01 **	0.03 *	0.03 *
S1–S3	0.03 *	0.01 **	0.03 *	0.03 *
S2–S3

S1: Shoe outsole with a friction coefficient of 0.80 ± 0.05. S2: Shoe outsole with a friction coefficient of 1.00 ± 0.05. S3: Shoe outsole with a friction coefficient of 1.20 ± 0.05. A-P: anterior–posterior direction. Vert: vertical direction. BW: body weight.

present comprehensive findings related to the full approach jump. Similar to the observations in defensive slide and crossover dribbling, the linear adjustments in the shoe outsole friction coefficient exhibited non-linear effects on the specific parameters governing skill control. In terms of contact time, a substantial and statistically significant reduction (p < 0.05) was evident as the shoe outsole friction coefficient increased from 0.8 to 1.0, indicating a heightened quickness of the jump. However, no further significant decrease (p > 0.05) was noted when the coefficient increased from 1.0 to 1.2. Regarding the anterior–posterior impulse—a crucial factor influencing deceleration in forward motion—we found a significant and noteworthy increase (p < 0.05), signifying a swifter cessation of motion. This was discerned with the rise in friction coefficient from 0.8 to 1.0. Nevertheless, no subsequent significant alteration was observed with a further increase from 1.0 to 1.2. Vertical impulse, associated with jumping height, displayed a comparable pattern, with a significant increase (p < 0.05) observed from 0.8 to 1.0; yet, no subsequent significant change occurred with a further increase from 1.0 to 1.2 (p > 0.05). The jump height exhibited a similar trend to anterior–posterior impulse and vertical impulse.

4. Discussion

The current study undertakes a comprehensive investigation into the intricate relationship between the fundamental skills of basketball—defensive slide, crossover dribbling, and full approach jump—and the shoe outsole friction coefficient. By assessing how variations in shoe friction affect the execution of these skills, the research elucidates the nuanced interplay between motor skill control and footwear characteristics. A straightforward methodology was employed, involving equal increments (from 0.8 to 1.0 to 1.2) of shoe friction coefficient to assess changes in selected motor skill control parameters, aiming to determine whether the influence of the shoe friction coefficient on the motor skill control parameters exhibits linearity. The results indicated that equal increments of the shoe friction coefficient did not yield equal changes in the selected motor skill control parameters, suggesting a possible non-linear relationship. Subsequent ANOVA analyses revealed significant differences among the selected motor skill control parameters, confirming the non-linear nature of the influence. Therefore, one pivotal finding of this study is the validation of the hypothesis proposing a non-linear influence between the performance quality of the fundamental skills of basketball and the shoe friction coefficient, hinting at the potential existence of an optimal value for the shoe friction coefficient conducive to executing various basketball skill maneuvers. This significant evidence contributes novel insights to the existing literature, establishing a foundational understanding of the nuanced relationship between shoe friction and sports performance.

In the realm of sports, the pursuit of heightened human performance invariably involves the execution of faster movements and sudden directional changes, commonly known as speed and agility, as well as more powerful tasks [2,4,31]. One negative consequence of increased agility and power would be an increase in loading on the human body and, consequently, an elevated risk of injury [3,31]. Sports shoes are designed with a dual objective—to boost athletic performance while concurrently minimizing injury risks [32,33]. In this study, 13 parameters from 3 fundamental basketball skills were meticulously selected to assess the influence of shoe friction coefficient on skill quality and injury risk associated with basketball players.

When considering skill quality, the existing literature emphasizes the intricate link between proficiency in fundamental basketball skills and key attributes such as agility, speed, and leg-power-generation capacity [1]. Biomechanically, these aspects can be quantified through parameters such as contact time, impulse, stride length, and jumping height, which constitute 11 out of the 13 parameters selected in the current study. Notably, 9 out of the 11 quality parameters exhibit non-linear influences of the shoe outsole friction coefficient on skill performance quality (Table 2, Table 4 and Table 6). As the friction coefficient increases, both the defensive slide and the full approach jump exhibited faster execution and more powerful actions to various extents, as did the jumping height of the full approach jump. However, the positive influence diminished in seven parameters, suggesting a potential saturation point, where further increases in friction coefficient may not yield proportional improvements in skill quality.

In the context of discussing injury risk, the outcomes associated with the two selected parameters, namely joint torques related to lateral cutting movement in defensive slide and crossover dribbling, present a controversial scenario. The results of the defensive slide present a nuanced narrative that challenges prevailing expectations, while the results of crossover dribbling follow the common expectation. Specifically, common expectations posit that a high shoe friction coefficient is linked to movement conditions that could heighten the risk of soft tissue injury [13,14]. In the case of the defensive slide, a notable pattern emerges wherein an augmentation of the friction coefficient corresponds to a reduction in ankle torque (Table 1 and Table 2), suggesting a potential mitigation of injury risk. However, given the infrequency of pure lateral movements in real-game situations, additional investigations are imperative to validate these findings, particularly in defensive slide in real-game situations that encompass a combination of medial–lateral and anterior–posterior components. This underscores the intricate nature of movements in real-game scenarios and implies that solely examining pure lateral movement may not offer a comprehensive understanding of injury risk factors. Subsequent studies focusing on game-like skill control are requisite to substantiate the potential risk reduction.

Summarizing the discussions above, the current study aligns seamlessly with the open-control nature of basketball skills [10,11], emphasizing the critical role of dynamic balance control in cutting, rapid deceleration, and jumping movements. Considering both skill quality and injury risk, only two out of the nine affected control quality parameters demonstrate that an increase in friction coefficient enhances skill quality without a concurrent increase in injury risk. This intriguing revelation prompts consideration for a trade-off strategy or optimization in selecting the optimal friction coefficient. With only three coefficient manipulations in the current study, the possible optimal value of the shoe outsole friction coefficient may exist between 1.0 and 1.2, underscoring the necessity for further research to pinpoint this optimal range.

Comparing these results with those available in the existing literature [7,8,9], the study significantly contributes to the relatively limited body of research investigating the specific influences of shoe friction coefficients on basketball skills. While previous studies have broadly explored modifications in shoe structure, the present study uniquely focused on the singular impact of friction, offering nuanced insights into the intricate relationship between shoe friction coefficient and skill control alterations, and emphasizing the multifaceted effects of shoe characteristics on skill control biomechanics across various athletic activities.

However, like many research endeavors, the present study is not without its limitations. Notably, this study exhibits the characteristics of a small-sample-size study. It is widely acknowledged that such studies are prone to significant biases and should be undertaken only when achieving a realistically calculated sample size is unfeasible, e.g., in cases involving skilled or elite athletes. However, one advantage of utilizing such subjects is the establishment of highly stable control patterns over time due to their extensive training [34]. Typically, in elite sports, small-sample-size studies entail a limited number of qualified subjects, often ranging from 2 to 9 individuals [35,36,37,38,39]. Our study aligns with this framework, although efforts were made to expand the sample size to 12 participants. An essential consideration in small-sample-size studies pertains to their research goal, whether it prioritizes generalizable inference or informs decisions within or closely aligned with real-world conditions. Our study is explicitly positioned as a case-like investigation, focusing on providing insights rather than drawing broad, generalizable conclusions. The case study approach enables the exploration of complex units comprising multiple variables relevant to understanding the phenomenon under scrutiny [40]. Rooted in real-life contexts, case studies yield comprehensive and nuanced insights into a given phenomenon, which can inform future research endeavors [40].

The second limitation is that the study exhibits a confined focus on male athletes affiliated with a singular university, raising considerations about the generalizability of the findings to a broader population. To enhance the robustness and applicability of the current findings, subsequent research endeavors should prioritize participant diversity, corroborating and potentially extending the insights obtained from this specific cohort. Other limitations pertain to aspects such as training effects, encompassing skill adaptation, and the need for individualized approaches. To address these limitations, forthcoming studies may adopt longitudinal methodologies, providing a temporal dimension to gain deeper insights into skill adaptation and injury occurrence over time. Additionally, exploring optimal friction coefficients tailored to individual players based on their distinct biomechanical profiles would enable the formulation of personalized footwear recommendations, enhancing the applicability of the study’s findings to a broader athletic context [41,42].

5. Conclusions

In summary, this investigation explores the intricate relationship between fundamental basketball skills—defensive slide, crossover dribbling, and full approach jump—and shoe outsole friction coefficient. A significant finding reveals a non-linear influence, suggesting an optimal value for executing these maneuvers. This contributes to understanding the nuanced connection between shoe friction and sports performance.

In sports, achieving higher performance involves faster movements, directional changes, and mitigating injury risks. This study evaluates the impact of shoe friction coefficient on skill quality and injury risk, analyzing 13 parameters from 3 fundamental basketball skills.

The examination aligns with the existing literature, emphasizing proficiency in fundamental skills and attributes like agility and speed. Biomechanically, parameters such as contact time, impulse, and jumping height were quantified. Nine parameters show non-linear influences, enhancing defensive slide and full approach jump execution but indicating diminishing returns.

Regarding injury risk, the study provides insights, particularly challenging expectations related to defensive slide results. Further investigation is necessary given the infrequency of lateral movements in real-game situations.

Comparing with the existing literature, the study contributes significantly to understanding shoe friction coefficients’ specific influences on basketball skills. Considering skill quality and injury risk, it prompts contemplation of optimization in selecting the optimal friction coefficient, potentially between 1.0 and 1.2. Future research could explore tailored friction coefficients for personalized footwear recommendations based on individual biomechanical profiles.