Performance and Asymmetry of Shuffling Tasks at Different Angles and Directions in Collegiate Basketball Players

Performance and Asymmetry of Shuffling Tasks at Different Angles and Directions in Collegiate Basketball Players | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Performance and Asymmetry of Shuffling Tasks at Different Angles and Directions in Collegiate Basketball Players Zhan Li, Mengde Lyu, Ling Ding, Meiling Tao, Peng Wang, Chris Bishop, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7819352/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: This study aims to examine the shuffle performance and asymmetry across different angles and directions among collegiate basketball players. Methods: Forty-two players completed six randomized shuffle tests at two directions (left/right) and three angles (45°/90°/135°). The shuffle asymmetry index was calculated as (dominant – non-dominant) / dominant × 100% . Two-way repeated-measures ANOVA and Kruskal-Wallis tests were used to analyze shuffle performance and asymmetry in different angles. Kappa coefficient evaluated directional asymmetry consistency. Results: Results showed excellent reliability across conditions (ICC = 0.94 – 0.97; CV = 2.4 – 3.2%). A significant main effect of angle (F = 12.334, p < 0.001) and an angle × direction interaction (F = 14.489, p < 0.001) were observed. Left‐ward shuffles at 135° (2.76 ± 0.31) were slower than at 45° and 90° (all p 0.05). No significant difference in the asymmetry of shuffle from different angles (χ² = 2.103, p = 0.349; mean 5.1 – 6.6%), and kappa coefficients indicated poor consistency of directional dominance (k = 0.077 – 0.168). Conclusion: The shuffle performance was jointly influenced by angle and direction. The magnitude of shuffle asymmetry remained consistent across angles, suggesting that movement asymmetry was task-dependent rather than fixed. These findings support the implementation of multi-angle shuffle in training and evaluation protocols to enhance performance. Clinical trial number: not applicable. agility multidirectional between-limb differences movement performance Basketball player Figures Figure 1 Figure 2 1 Introduction Basketball is a sport that frequently involves movement in the frontal plane (Lyu et al., 2025b ). Research indicates that basketball players may perform over 300 lateral movements per game, accounting for 18.1–42.1% of total playing time, with an average movement distance of 2.28–4.24 meters per instance (Taylor et al., 2017 ). Lateral movement refers to high-intensity ‘start-stop’ actions performed in the frontal plane, involving rapid displacements to the left or right to facilitate frequent directional changes within short time frames (Subramanium et al., 2021 ), including shuffling, cuts, and changes of direction (COD). Among these, the shuffle serves as a fundamental component of lateral movement (Ding et al., 2024 ; Lyu et al., 2025b ; a ; Wang et al., 2025 ), often affecting basketball players’ movement and defensive success (Whitting et al., 2013 ). In sports science, asymmetry generally describes performance or functional differences between bilateral body segments, involving morphological (Maloney, 2019 ), strength, flexibility, coordination and functional characteristics. Such inter-limb asymmetries may substantially influence athletic performance and injury risk (Bishop et al., 2023 ). Evidence suggests that greater magnitudes of asymmetry often correlate with poorer outcomes in tasks such as jumping, sprinting, and change of direction (Madruga-Parera et al., 2021 ; Bishop et al., 2022b ; Ding et al., 2024 ). Moreover, larger magnitudes of inter-limb asymmetry have also been shown to relate to an increase in injury occurrence rates (Croisier et al., 2008 ). Consequently, assessing asymmetry and implementing individualized training programs, which, to some extent, aim to reduce imbalances, are crucial for reducing injury risk and optimizing athletic performance (Bishop, Turner and Read, 2018 ; Loturco et al., 2019 ).. In basketball specifically, increasing attention has been focused on lateral movement asymmetry, particularly during shuffle tasks. To our knowledge, in lateral movement contexts, Lyu et al. observed significant shuffle asymmetry (3.3 ± 2.5%, ES = 0.52) in adolescent basketball players during 5-meter tests(Lyu et al., 2025a ), whereas Wang et al. found significant correlations between COD in shuffle asymmetry scores and COD performance ( ρ = 0.37, p < 0.05) among college players(Wang et al., 2025 ). Of note, with this relationship being positive, it indicates that a larger asymmetry is associated with slower COD speed times. However, these studies exclusively evaluated 90° lateral movements (relative to the direction the body is facing), neglecting the multi-angular demands of competitive play. Research from Gonzalo-Skok and Bishop revealed directional inconsistencies in limb dominance across 45°, 90°, 135°, and 180° change-of-direction tests among basketball players (ES = 0.70–1.28; p < 0.05), suggesting traditional single-angle assessments may underestimate in-game performance demands and existing inter-limb asymmetries (Gonzalo-Skok et al., 2023 ). Nevertheless, few studies have systematically analyzed basketball players' shuffle performance and asymmetry across 45°, 90°, and 135° angles. This study aims to examine college basketball players' shuffle performance and shuffle asymmetry across different directions (left/right) and multiple angles (45°, 90°, 135°). We hypothesize that there will be significant differences in shuffle performance and asymmetry across various angles and directions. 2 Materials and Methods 2.1 Participants A priori sample size estimation was conducted using G*Power 3.1 based on a repeated-measures ANOVA design with six within-subject conditions (3 angles × 2 directions). With an assumed medium effect size (f = 0.30), α = 0.05, power = 0.80, and a correlation among repeated measures of 0.50, the analysis indicated a minimum requirement of 14 participants. However, to enhance statistical power, reduce inter-individual variability, and strengthen the robustness of the findings, a total of 42 athletes were recruited. All the participants were college basketball players from the same university, with a mean age of 20.30 ± 1.20 years and a mean height of 178.30 ± 8.60 cm. They were engaged in at least four regular basketball training sessions and two strength training sessions per week, with a minimum of five years of basketball training experience and prior participation in official competitive matches. Exclusion criteria included any history of major injuries within the six months preceding the study, as well as chronic medical conditions (e.g., cardiovascular disease, diabetes) that could potentially impair performance. The study was performed in accordance with the standards set by the 2013 version of the Declaration of Helsinki and was approved by the Institutional Ethics Committee of local university (approval number: 2024409H). All participants provided written informed consent after receiving a full explanation of the study’s purpose, procedures, and potential risks. 2.2 Design and Procedures This descriptive study utilizes a cross-sectional design to investigated the performance and asymmetry of multi-angle lateral shuffle among college basketball players. The independent variables included different movement direction (left/right) and different angular displacement (45°, 90°, 135°), while the dependent variables comprised completion time, shuffle asymmetry index, and angular performance consistency. Participants completed six shuffle tests: left/right 45°, left/right 90°, and left/right 135°. Before the shuffling tests, each participant underwent a specific warm-up routine (Turki et al., 2020), including low-intensity jogging, dynamic stretching, and shuffle at three angle at 60% maximal effort. Three maximal-effort shuffling trials were then performed for each direction and angle, with the best score used for further data analysis. All tests were administered in a randomized order. Prior to the experiment, all participants were familiarized with the testing procedures. Athletes were required to refrain from vigorous exercise (i.e., no basketball training, only light dynamic activities) for 24 hours before testing and to consume their last meal at least three hours prior to testing. 2.3 Shuffle Test The shuffle asymmetry assessment comprised six test conditions (Figure 1) across three angles (45°, 90°, 135°) and two directions (left and right), with the trial order randomly assigned and a 3-minute recovery interval provided between trials. Participants initially assumed a standardized defensive stance facing directly forward behind the starting line, with their body orientation subsequently adjusted to align with predefined angular markers (45°, 90°, 135°) on the floor. Two identical marker posts were positioned at the start and finish lines of each angular path to standardize foot contact accuracy. Upon the auditory "Go" command, participants performed maximal-effort shuffles along the designated angular path while maintaining the required defensive posture throughout the movement. Movement time was recorded using the CODTimer smartphone application (Balsalobre-Fernández et al., 2019; Bishop et al., 2022a), with an iPhone positioned perpendicular to the finish line at a 5-meter distance to ensure full-body kinematic capture. The first frame in which the foot closest to the movement direction left the ground (indicating the start of the shuffle), and the frame in which the same foot crossed the marker post (indicating the end of the shuffle), were selected to calculate shuffle performance. Three successful trials per condition were recorded, excluding attempts where participants failed to touch both marker posts. 2.4 Statistical Analysis The descriptive data are presented as means ± standard deviations (SD). Normality of the data distribution and homogeneity of variance were assessed using the Shapiro-Wilk and Levene’s methods, respectively. Reliability was assessed using a two-way random intra-class correlation coefficient (ICC) with absolute agreement and 95% confidence intervals, typical error of the measurement (TEM), and the coefficient of variation (CV). The magnitude of the CV was interpreted as follows: poor ( > 10%), moderate (5 – 10%) or good ( < 5%) (Banyard et al., 2017). The interpretation of ICC values was based on the lower bound of the 95% confidence interval, following the criteria proposed by Koo and Li (Koo and Li, 2016), where ICC 0.9 excellent. The asymmetry index was calculated using the following formula: asymmetry index = (better-performing side - poorer-performing side) / better - performing side × 100% .(Bishop et al., 2023). The data were analyzed using SPSS 27.0 (IBM Corp., Armonk, NY, USA). A two-way repeated-measures ANOVA [angle (45°, 90°, 135°) × direction (left, right)] was performed to examine the combined effects of angular displacement and movement direction on lateral shuffling speed. Post hoc pairwise comparisons with Bonferroni adjustments were conducted when significant interactions emerged. To assess whether movement angles influenced shuffle asymmetry, a Kruskal-Wallis H test was employed due to the non-normal distribution of asymmetry indices (Shapiro-Wilk p < 0.05). Post hoc test with Bonferroni correction was subsequently applied to determine between-angle differences when a significant main effect was detected. The Kappa coefficient was calculated to evaluate the level of consistency in asymmetry favoring the same side (asymmetry direction) (Bishop, 2021). Kappa values were interpreted as follows: ≤ 0 poor agreement, 0.01 – 0.20 slight agreement, 0.21 – 0.40 fair agreement, 0.41 – 0.60 moderate agreement, 0.61 – 0.80 substantial agreement, and 0.81 – 0.99 almost perfect agreement (Bishop et al., 2023). All statistical analyses were conducted using IBM SPSS software version 26.0 (IBM, Armonk, NY, USA). 3 Results Table 1 presents the performance, shuffle asymmetry, and reliability data of different direction shuffle tests. All tests demonstrated excellent reliability with ICC ranging from 0.94 to 0.97 (all ≥ 0.90). CV values remained within acceptable thresholds ( < 10%), measuring 2.4 – 3.2% across conditions. All measured parameters adhered to normal distributions. The two-way ANOVA results indicated a significant main effect of angle (F = 12.334, p < 0.001, η² = 0.231), no significant main effect of direction (F = 0.040, p = 0.842, η² = 0.001), and a significant angle-direction interaction effect (F = 14.489, p < 0.001, η² = 0.261). Post-hoc analysis revealed that: for the same direction at different angles, the lateral shuffle speeds at left 45° (3.02 ± 0.33) and 90° (2.93 ± 0.31) were both significantly higher than at left 135° (2.76 ± 0.31, p 0.05). For the same angle in different directions, significant differences in lateral shuffle speed were found between left and right sides at both 45° (left 3.02 ± 0.33 vs. right 2.90 ± 0.31) and 135° (left 2.76 ± 0.31 vs. right 2.88 ± 0.32, p 0.05). The Kruskal-Wallis test showed no significant angle-dependent variations in shuffle asymmetry indices (χ² = 2.103, p = 0.349). Shuffle asymmetry magnitudes varied across angular conditions, measuring 5.9 ± 4.0% (45°), 5.1 ± 3.7% (90°), and 6.6 ± 4.7% (135°). Consistency analysis in Table 2 revealed poor agreement between angular variants, evidenced by Kappa coefficients of 0.077 (45° vs 90°), 0.168 (45° vs 135°), and 0.078 (90° vs 135°). Table 1. Shuffle performance, asymmetry scores, and test reliability data. Test Mean ± SD Asymmetry (%) ICC (95%CI) CV S-45° Left 3.02 ± 0.33* † 5.9 ± 4.0 0.96 (0.93 – 0.98) 2.9 (0.3 – 9.9) Right 2.90 ± 0.31 0.94 (0.89 – 0.96) 3.2 (0.8 – 6.6) S-90° Left 2.93 ± 0.31* 5.1 ± 3.7 0.97 (0.94 – 0.98) 2.6 (0.8 – 5.5) Right 2.94 ± 0.27 0.95 (0.92 – 0.97) 2.4 (0.3 – 9.2) S-135° Left 2.76 ± 0.31 † 6.6 ± 4.7 0.96 (0.93 – 0.98) 2.6 (0.5 – 8.2) Right 2.88 ± 0.32 0.94 (0.89 – 0.96) 3.1 (0.4 – 8.0) Abbreviation: ICC, intra-class correlation coefficient; CV, coefficient of variation; S-45° , S-90° and S-135°: shuffle test at 45º, 90º and 135º. * = significantly different with S-135 °; † = significantly different with shuffle on right . Table 2. Kappa coefficients describing how consistently asymmetry favored the same side across shuffle angles (45°, 90°, 135°). Test S-45° S-90° S-135° S-45° 1 0.077 0.168 S-90° 1 0.078 S-135° 1 Abbreviation: S-45° , S-90° and S-135°: shuffle test at 45º, 90º and 135º. 4 Discussion The aims of this study were to examine the shuffle performance and asymmetry across different angles and directions among collegiate basketball players. Our results indicated that: 1) significant differences of shuffle performance were observed in shuffling at different angle; 2) shuffle asymmetry did not vary significantly across angles, and 3) no consistent directional dominance was observed across different shuffle tests. The observed results demonstrated that during left shuffling, the movement speed at 135° was significantly slower than at 45° and 90°. This finding supports our hypothesis, as previous studies have reported similar results (Rouissi et al., 2016; Gonzalo-Skok et al., 2023). Gonzalo-Skok et al. specifically found that basketball players 10-meter multi-angle' COD completion times increased with larger angles (45 – 90°), then gradually stabilized during 135 – 180° maneuvers. Studies in COD tasks have shown that as angles increase, athletes experience reduced approach velocity, prolonged ground contact times, smaller knee flexion angles, and increased joint loading complexity, indicating greater biomechanical demands at sharper angles (Havens and Sigward, 2015; Schreurs et al., 2017; Dos’Santos et al., 2019). Although the shuffle task in our study differs from conventional COD maneuvers, particularly because it does not involve braking or turning phases, it is reasonable to speculate that larger angular displacements may impair movement efficiency due to altered neuromechanical demands. While this evidence originates from COD-based protocols, it may be partially applicable to multi-angled shuffle tasks. Nonetheless, direct empirical evidence on angle-specific demands in lateral shuffling remains limited and warrants further investigation. Notably, no significant inter-angle differences were observed during right shuffling. This finding may reflect greater neuromuscular control stability in the dominant side, potentially developed through long-term habitual movement patterns. Supporting this speculation, previous studies have reported that 94.9% of professional basketball players exhibit right-handed dominance (Lawler and Lawler, 2011). However, since handedness cannot be directly equated with movement lateralization and no sport-specific studies have yet investigated shuffle-dominant sides in basketball players (Virgile and Bishop, 2021), this interpretation should be treated with caution. Nevertheless, the angle-dependent performance variations being exclusively observed on the left side may reveal an underlying mechanism of directional movement asymmetry. These results further emphasize the necessity of implementing multi-angle, bilateral assessment in athletic performance evaluation to more comprehensively capture movement characteristics and potential asymmetric patterns. Furthermore, the observed performance differences between left and right shuffles at 45° and 135° align with expectations, supporting the notion of inherent asymmetry in basketball lateral movements (Lyu et al., 2025a). Notably, in contrast to the significant bilateral differences in 90° shuffling previously reported by Lyu et al. our findings revealed no statistically significant disparities at this particular angle (Lyu et al., 2025a). However, the absence of such differences at 90° may be attributed to participant characteristics. While Lyu et al. examined pre-juvenile basketball players (aged 14 – 15 years) (Lyu et al., 2025a), the current study involved college basketball players (aged 18 + years). The latter group's longer duration of specialized training and systematic exposure to 90° lateral movements may have reduced this asymmetry. Additionally, variations in team training methodologies (e.g., emphasis on bilateral balance vs. unilateral reinforcement) could serve as potential influencing factors, although we recognize that this narrative is somewhat speculative. Asymmetry indices demonstrated no significant variation across angles. While the mean asymmetry values at 45°, 90°, and 135° appeared similar, this statistical non-significance may be more reflective of data variability than an actual absence of true differences. As shown in Table 1, the SD for COD times represent approximately 10% of their means, whereas the SD for asymmetry indices account for 70 – 90% of the mean values. This high relative variability substantially reduces the power to detect meaningful differences. Similar limitations have been highlighted in previous work (Bishop et al., 2019, 2022b; c), where asymmetry comparisons across tasks or sessions often failed to reach significance due to large within-subject variation, rather than the absence of a true effect. These findings emphasize the need for caution when interpreting group-based asymmetry data and reinforces the need to assess asymmetry on an individual basis (Bishop et al., 2021). This result is consistent with recent basketball-specific research by Gonzalo-Skok et al., who reported angle-independent asymmetry profiles in COD tasks (ES = 0.00 – 0.58, p < 0.05) (Gonzalo-Skok et al., 2023). Lyu et al. and Bishop et al. also pointed out that the asymmetry exhibited by athletes in different tasks may vary depending on the type of task (Bishop et al., 2023; Lyu et al., 2025a), emphasizing the necessity of considering task specificity when assessing asymmetry. Additionally, the results demonstrated no consistent directional dominance across all angles. Figure 2 displays the individual asymmetry values at each angle, highlighting the variation in dominant side across conditions. This incongruity implies that limb dominance is task-angle dependent rather than a fixed neuromuscular trait—a critical consideration for asymmetry screening protocols. The significant angle-direction interaction further supports that limb preference is modulated by task constraints rather than inherent physiological asymmetry. Gonzalo-Skok et al. similarly observed that preferred limb dominance can shift depending on the angle of direction change (Gonzalo-Skok et al., 2023). In our data, for example, some athletes exhibited left-side dominance at 45°, yet right-side dominance at 135°, emphasizing the need for angle-stratified asymmetry assessments (Gonzalo-Skok et al., 2023). Coaches should consider specialized training at 45° and 135° directions to specifically address direction-specific movement performance differences, with particular emphasis on strengthening the significantly lagging left-side. Current data shows that the bilateral movement asymmetry index at 45° and 135° remains consistently high. This biomechanical imbalance not only restricts athletic performance but also more easily induces sports injuries (Afonso et al., 2022). Therefore, it is our suggestion that training programs should follow the "Bilateral Strength-Coordination Synchronized Development" principle (Zhao et al., 2023; Cadens et al., 2023). Specifically, an intervention strategy combining bilateral synchronous training with contralateral compensatory reinforcement training can be adopted to effectively reduce asymmetry coefficients (Bettariga et al., 2022), improve movement performance and control injury risks. We recommend using multi-angle assessments instead of traditional single-angle (e.g., only 90°) asymmetry tests to ensure comprehensive capture of contextual neuromuscular imbalance characteristics. Despite methodological advancements, three limitations constrain broader applicability. First, the absence of kinetic/kinematic data (e.g., ground reaction forces, joint angles) precludes mechanistic explanations for angular performance gradients; future studies must integrate force plates and 3D motion capture to delineate load distribution patterns. Second, generalizability to elite or youth cohorts remains unverified due to the exclusive focus on college athletes, necessitating cross-population validations. Third, despite implementing 3-minute inter-trial rest periods, the accumulation of neuromuscular fatigue across 18 maximal-effort trials (6 conditions × 3 repetitions) within a single testing session may have systematically biased performance outcomes in later conditions. To mitigate this confounder, future experimental designs should adopt session-separated protocols. 5 Conclusion In conclusion, the shuffle performance of college basketball players differs by angle, with the 135° shuffle being the slowest. Although asymmetry magnitudes remained relatively stable across angles, no consistent directional advantage was observed at any angle, indicating that limb dominance is influenced by task-specific demands. Declarations Ethics approval and consent to participate The study was conducted in accordance with the standards set by the 2013 revision of the Declaration of Helsinki and was approved by the Institutional Ethics Committee of Beijing Sport University, Beijing, China (approval number: 2024409H). All participants provided written informed consent after receiving a full explanation of the study’s purpose, procedures, and potential risks. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The author(s) declare that no financial support was received for the research and/or publication of this article. Author Contributions ZL and ML: Conceptualization, Writing; LD and MT : Methodology, Data curation; ZL and ML: Software; ZL and YL: Validation; MT : formal analysis; ZL: writing—original draft preparation; ZL, ML and CB: writing—review & editing; PW: visualization; CB : Reviewing; YL: Project administration. Acknowledgments The authors would like to thank the participants and coaches from the university basketball teams for their cooperation throughout the study. We are grateful for all the assistance and support provided by the staff. We also sincerely thank Professor Chris Bishop and Professor Yongming Li for their valuable academic guidance and insightful suggestions during the development of this study. References Afonso, J., Peña, J., Sá, M., Virgile, A., García-de-Alcaraz, A. and Bishop, C. (2022) Why Sports Should Embrace Bilateral Asymmetry: A Narrative Review. Symmetry. 14, 1993. doi: 10.3390/sym14101993 Balsalobre-Fernández, C., Bishop ,Chris, Beltrán-Garrido ,José Vicente, Cecilia-Gallego ,Pau, Cuenca-Amigó ,Aleix, Romero-Rodríguez ,Daniel, et al. (2019) The validity and reliability of a novel app for the measurement of change of direction performance. J Sport Sci. 37, 2420–2424. doi: 10.1080/02640414.2019.1640029 Banyard, H.G., Nosaka, K. and Haff, G.G. (2017) Reliability and Validity of the Load–Velocity Relationship to Predict the 1RM Back Squat. J Strength Cond Res. 31, 1897–1904. doi: 10.1519/jsc.0000000000001657 Bettariga, F., Turner, A., Maloney, S., Maestroni, L., Jarvis, P. and Bishop, C. (2022) The Effects of Training Interventions on Interlimb Asymmetries: A Systematic Review With Meta-analysis. Strength Cond J. 44, 69–86. doi: 10.1519/ssc.0000000000000701 Bishop, C. (2021) Interlimb Asymmetries: Are Thresholds a Usable Concept? Strength Cond J. 43, 32–36. doi: 10.1519/ssc.0000000000000554 Bishop, C., de Keijzer, K.L., Turner, A.N. and Beato, M. (2023) Measuring Interlimb Asymmetry for Strength and Power: A Brief Review of Assessment Methods, Data Analysis, Current Evidence, and Practical Recommendations. J Strength Cond Res. 37, 745–750. doi: 10.1519/JSC.0000000000004384 Bishop, C., Lake, J., Loturco, I., Papadopoulos, K., Turner, A. and Read, P. (2021) Interlimb Asymmetries: The Need for an Individual Approach to Data Analysis. J Strength Cond Res. 35, 695–701. doi: 10.1519/jsc.0000000000002729 Bishop, C., Perez-Higueras Rubio, M., Gullon, I.L., Maloney, S. and Balsalobre-Fernandez, C. (2022a) Jump and Change of Direction Speed Asymmetry Using Smartphone Apps: Between-Session Consistency and Associations With Physical Performance. J Strength Cond Res. 36, 927–934. doi: 10.1519/JSC.0000000000003567 Bishop, C., Read, P., Bromley, T., Brazier, J., Jarvis, P., Chavda, S., et al. (2022b) The Association Between Interlimb Asymmetry and Athletic Performance Tasks: A Season-Long Study in Elite Academy Soccer Players. J Strength Cond Res. 36, 787–795. doi: 10.1519/JSC.0000000000003526 Bishop, C., Read, P., Chavda, S., Jarvis, P., Brazier, J., Bromley, T., et al. (2022c) Magnitude or Direction? Seasonal Variation of Interlimb Asymmetry in Elite Academy Soccer Players. J Strength Cond Res. 36, 1031–1037. doi: 10.1519/JSC.0000000000003565 Bishop, C., Read, P., Chavda, S., Jarvis, P. and Turner, A. (2019) Using Unilateral Strength, Power and Reactive Strength Tests to Detect the Magnitude and Direction of Asymmetry: A Test-Retest Design. Sports. 7, 58. doi: 10.3390/sports7030058 Bishop, C., Turner, A. and Read, P. (2018) Training Methods and Considerations for Practitioners to Reduce Interlimb Asymmetries. Strength Cond J. 40, 40–46. doi: 10.1519/ssc.0000000000000354 Cadens, M., Planas-Anzano, A., Peirau-Terés, X., Bishop, C., Romero-Rodríguez, D. and Madruga-Parera, M. (2023) Relationship between Asymmetry Profiles and Jump Performance in Youth Female Handball Players. J Hum Kinet. 87, 5–16. doi: 10.5114/jhk/163432 Croisier, J.-L., Ganteaume, S., Binet, J., Genty, M. and Ferret, J.-M. (2008) Strength Imbalances and Prevention of Hamstring Injury in Professional Soccer Players: A Prospective Study. Am J Sport Med. 36, 1469–1475. doi: 10.1177/0363546508316764 Ding, L., Lyu, M., Chen, Z., Wu, J., Wang, Y., Bishop, C., et al. (2024) Associations Between Inter-Limb Asymmetry in Lower Limb Strength and Jump Performance in 14–15-Year-Old Basketball Players. Symmetry. 16, 1421. doi: 10.3390/sym16111421 Dos’Santos, T., McBurnie, A., Thomas, C., Comfort, P. and Jones, P. (2019) Biomechanical Determinants of the Modified and Traditional 505 Change of Direction Speed Test. J Strength Cond Res. 34, 1285–1296. doi: 10.1519/JSC.0000000000003439 Gonzalo-Skok, O., Dos’Santos, T. and Bishop, C. (2023) Assessing Limb Dominance and Interlimb Asymmetries Over Multiple Angles During Change of Direction Speed Tests in Basketball Players. J Strength Cond Res. 37, 2423–2430. doi: 10.1519/jsc.0000000000004558 Havens, K.L. and Sigward, S.M. (2015) Whole body mechanics differ among running and cutting maneuvers in skilled athletes. Gait Posture. 42, 240–245. doi: 10.1016/j.gaitpost.2014.07.022 Koo, T.K. and Li, M.Y. (2016) A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med. 15, 155–163. doi: 10.1016/j.jcm.2016.02.012 Lawler, T.P. and Lawler, F.H. (2011) Left-Handedness in Professional Basketball: Prevalence, Performance, and Survival. Percept Motor Skill. 113, 815–824. doi: 10.2466/05.19.25.PMS.113.6.815-824 Loturco, I., Pereira, L.A., Kobal, R., Abad, C.C.C., Rosseti, M., Carpes, F.P., et al. (2019) Do asymmetry scores influence speed and power performance in elite female soccer players? Biol Sport. 36, 209–216.. doi: 10.5114/biolsport.2019.85454 Lyu, M., Chen, Z., Deng, S., Ding, L., Han, J., Bishop, C., et al. (2025a) Asymmetry of the Single Leg Jump and Lateral Shuffle Performance in Pre-Juvenile Basketball Players. J Hum Kinet. 96, 109–119. doi: 10.5114/jhk/196315 Lyu, M., Yin, M., Ding, L., Tang, R., Chen, Z., Deng, S., et al. (2025b) Physiological and Neuromuscular Fatigue after 3-Minute Lateral Shuffle Movement at Different Speeds and Distances. J Hum Kinet. 95, 151–159. doi: 10.5114/jhk/190145 Madruga-Parera, M., Bishop, C., Beato, M., Fort-Vanmeerhaeghe, A., Gonzalo-Skok, O. and Romero-Rodríguez, D. (2021) Relationship Between Interlimb Asymmetries and Speed and Change of Direction Speed in Youth Handball Players. J Strength Cond Res. 35, 3482–3490. doi: 10.1519/jsc.0000000000003328 Maloney, S.J. (2019) The Relationship Between Asymmetry and Athletic Performance: A Critical Review. J Strength Cond Res. 33, 2579–2593. doi: 10.1519/jsc.0000000000002608 Rouissi, M., Chtara ,Moktar, Owen ,Adam, Chaalali ,Anis, Chaouachi ,Anis, Gabbett ,Tim, et al. (2016) Effect of leg dominance on change of direction ability amongst young elite soccer players. J Sport Sci. 34, 542–548. doi: 10.1080/02640414.2015.1129432 Schreurs, M.J., Benjaminse, A. and Lemmink, K.A.P.M. (2017) Sharper angle, higher risk? The effect of cutting angle on knee mechanics in invasion sport athletes. J Biomech. 63, 144–150. doi: 10.1016/j.jbiomech.2017.08.019 Subramanium, A., Honert ,Eric C., Cigoja ,Sasa and and Nigg, B.M. (2021) The effects of shoe upper construction on mechanical ankle joint work during lateral shuffle movements. J Sport Sci. 39, 1791–1799. doi: 10.1080/02640414.2021.1898174 Taylor, J.B., Wright, A.A., Dischiavi, S.L., Townsend, M.A. and Marmon, A.R. (2017) Activity Demands During Multi-Directional Team Sports: A Systematic Review. Sports Med. 47, 2533–2551. doi: 10.1007/s40279-017-0772-5 Turki, O., Dhahbi, W., Padulo, J., Khalifa, R., Ridène, S., Alamri, K., et al. (2020) Warm-Up With Dynamic Stretching: Positive Effects on Match-Measured Change of Direction Performance in Young Elite Volleyball Players. International Journal of Sports Physiology and Performance. 15, 528–533. doi: 10.1123/ijspp.2019-0117 Virgile, A. and Bishop, C. (2021) A Narrative Review of Limb Dominance: Task Specificity and the Importance of Fitness Testing. J Strength Cond Res. 35, 846–858. doi: 10.1519/jsc.0000000000003851 Wang, P., Lyu, M., Geng, N., Wu, Z., Ren, X., Kozinc, Ž., et al. (2025) Asymmetry in college basketball players: change of direction performance in shuffle movement and 505 test. Front Physiol . 16, 1587719. doi: 10.3389/fphys.2025.1587719 Whitting, J.W., de Melker Worms, J.L.A., Maurer, C., Nigg, S.R. and Nigg, B.M. (2013) Measuring Lateral Shuffle and Side Cut Performance. J Strength Cond Res. 27, 3197–3203. doi: 10.1519/jsc.0b013e31828a2c2b Zhao, X., Turner, A.P., Sproule, J. and Phillips, S.M. (2023) The Effect of Unilateral and Bilateral Leg Press Training on Lower Body Strength and Power and Athletic Performance in Adolescent Rugby Players. J Hum Kinet. 86, 235–246. doi: 10.5114/jhk/159626 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7819352","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":547140944,"identity":"f177b320-f70e-401b-8e1b-5d0a33aea3cd","order_by":0,"name":"Zhan Li","email":"","orcid":"","institution":"Shanghai University of Sport","correspondingAuthor":false,"prefix":"","firstName":"Zhan","middleName":"","lastName":"Li","suffix":""},{"id":547140945,"identity":"fd4f59c3-bfdd-4265-a3dc-21dc6d9fcc96","order_by":1,"name":"Mengde Lyu","email":"","orcid":"","institution":"Royal Melbourne Institute of Technology 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09:44:48","extension":"xml","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":96507,"visible":true,"origin":"","legend":"","description":"","filename":"2aa8adafd1d14506b7b81a69b80948a31structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7819352/v1/4195a4ae041f1c5f12c96017.xml"},{"id":96273591,"identity":"1bed3f16-2df5-4ba6-a31a-b40b0f24352e","added_by":"auto","created_at":"2025-11-19 09:44:49","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":106115,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7819352/v1/7565bca0eff2d7c644d14c41.html"},{"id":96273578,"identity":"caa09459-50a9-4e27-9017-2f9e73969617","added_by":"auto","created_at":"2025-11-19 09:44:48","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":68312,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMulti-angle Lateral Shuffle Test Schematic\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7819352/v1/048c490bd38200ad171a41d2.jpeg"},{"id":96363837,"identity":"e08ccdfd-ae9e-456d-a784-6364b0400694","added_by":"auto","created_at":"2025-11-20 10:08:08","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50189,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIndividual shuffle asymmetry data at different angles. Values above 0 indicate better performance on the right side, while values below 0 indicate better performance on the left side.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7819352/v1/ae8b30d3c0f91883717bc715.jpeg"},{"id":105366678,"identity":"28a56dcf-c043-401e-b7ab-f2e9934e6bfe","added_by":"auto","created_at":"2026-03-25 08:43:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":798430,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7819352/v1/3527559f-9980-46e0-9842-1ae049f29fa7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Performance and Asymmetry of Shuffling Tasks at Different Angles and Directions in Collegiate Basketball Players","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eBasketball is a sport that frequently involves movement in the frontal plane (Lyu et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e). Research indicates that basketball players may perform over 300 lateral movements per game, accounting for 18.1\u0026ndash;42.1% of total playing time, with an average movement distance of 2.28\u0026ndash;4.24 meters per instance (Taylor et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Lateral movement refers to high-intensity \u0026lsquo;start-stop\u0026rsquo; actions performed in the frontal plane, involving rapid displacements to the left or right to facilitate frequent directional changes within short time frames (Subramanium et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), including shuffling, cuts, and changes of direction (COD). Among these, the shuffle serves as a fundamental component of lateral movement (Ding et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Lyu et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e; \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003ea\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), often affecting basketball players\u0026rsquo; movement and defensive success (Whitting et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn sports science, asymmetry generally describes performance or functional differences between bilateral body segments, involving morphological (Maloney, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), strength, flexibility, coordination and functional characteristics. Such inter-limb asymmetries may substantially influence athletic performance and injury risk (Bishop et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Evidence suggests that greater magnitudes of asymmetry often correlate with poorer outcomes in tasks such as jumping, sprinting, and change of direction (Madruga-Parera et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bishop et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e; Ding et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Moreover, larger magnitudes of inter-limb asymmetry have also been shown to relate to an increase in injury occurrence rates (Croisier et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Consequently, assessing asymmetry and implementing individualized training programs, which, to some extent, aim to reduce imbalances, are crucial for reducing injury risk and optimizing athletic performance (Bishop, Turner and Read, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Loturco et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)..\u003c/p\u003e\u003cp\u003eIn basketball specifically, increasing attention has been focused on lateral movement asymmetry, particularly during shuffle tasks. To our knowledge, in lateral movement contexts, Lyu et al. observed significant shuffle asymmetry (3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5%, ES\u0026thinsp;=\u0026thinsp;0.52) in adolescent basketball players during 5-meter tests(Lyu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e), whereas Wang et al. found significant correlations between COD in shuffle asymmetry scores and COD performance (\u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.37, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) among college players(Wang et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Of note, with this relationship being positive, it indicates that a larger asymmetry is associated with slower COD speed times. However, these studies exclusively evaluated 90\u0026deg; lateral movements (relative to the direction the body is facing), neglecting the multi-angular demands of competitive play. Research from Gonzalo-Skok and Bishop revealed directional inconsistencies in limb dominance across 45\u0026deg;, 90\u0026deg;, 135\u0026deg;, and 180\u0026deg; change-of-direction tests among basketball players (ES\u0026thinsp;=\u0026thinsp;0.70\u0026ndash;1.28; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting traditional single-angle assessments may underestimate in-game performance demands and existing inter-limb asymmetries (Gonzalo-Skok et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Nevertheless, few studies have systematically analyzed basketball players' shuffle performance and asymmetry across 45\u0026deg;, 90\u0026deg;, and 135\u0026deg; angles.\u003c/p\u003e\u003cp\u003eThis study aims to examine college basketball players' shuffle performance and shuffle asymmetry across different directions (left/right) and multiple angles (45\u0026deg;, 90\u0026deg;, 135\u0026deg;). We hypothesize that there will be significant differences in shuffle performance and asymmetry across various angles and directions.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003ch2\u003e2.1\u0026nbsp; \u0026nbsp; \u0026nbsp;Participants\u003c/h2\u003e\n\u003cp\u003eA priori sample size estimation was conducted using G*Power 3.1 based on a repeated-measures ANOVA design with six within-subject conditions (3 angles \u0026times; 2 directions). With an assumed medium effect size (f = 0.30), \u0026alpha; = 0.05, power = 0.80, and a correlation among repeated measures of 0.50, the analysis indicated a minimum requirement of 14 participants. However, to enhance statistical power, reduce inter-individual variability, and strengthen the robustness of the findings, a total of 42 athletes were recruited. All the participants were college basketball players from the same university, with a mean age of 20.30\u0026nbsp;\u0026plusmn;\u0026nbsp;1.20 years and a mean height of 178.30\u0026nbsp;\u0026plusmn;\u0026nbsp;8.60 cm. They were engaged in at least four regular basketball training sessions and two strength training sessions per week, with a minimum of five years of basketball training experience and prior participation in official competitive matches. Exclusion criteria included any history of major injuries within the six months preceding the study, as well as chronic medical conditions (e.g., cardiovascular disease, diabetes) that could potentially impair performance. The study was performed in accordance with the standards set by the 2013 version of the Declaration of Helsinki and was approved by the Institutional Ethics Committee of local university (approval number: 2024409H). All participants provided written informed consent after receiving a full explanation of the study\u0026rsquo;s purpose, procedures, and potential risks.\u003c/p\u003e\n\u003ch2\u003e2.2\u0026nbsp; \u0026nbsp; \u0026nbsp;Design and Procedures\u003c/h2\u003e\n\u003cp\u003eThis descriptive study utilizes a cross-sectional design to investigated the performance and asymmetry of multi-angle lateral shuffle among college basketball players. The independent variables included different movement direction (left/right) and different angular displacement (45\u0026deg;, 90\u0026deg;, 135\u0026deg;), while the dependent variables comprised completion time, shuffle asymmetry index, and angular performance consistency. Participants completed six shuffle tests: left/right 45\u0026deg;, left/right 90\u0026deg;, and left/right 135\u0026deg;. Before the shuffling tests, each participant underwent a specific warm-up routine (Turki et al., 2020), including low-intensity jogging, dynamic stretching, and shuffle at three angle at 60% maximal effort. Three maximal-effort shuffling trials were then performed for each direction and angle, with the best score used for further data analysis. All tests were administered in a randomized order. Prior to the experiment, all participants were familiarized with the testing procedures. Athletes were required to refrain from vigorous exercise (i.e., no basketball training, only light dynamic activities) for 24 hours before testing and to consume their last meal at least three hours prior to testing.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e2.3\u0026nbsp; \u0026nbsp; \u0026nbsp;Shuffle Test\u003c/h2\u003e\n\u003cp\u003eThe shuffle asymmetry assessment comprised six test conditions (Figure 1) across three angles (45\u0026deg;, 90\u0026deg;, 135\u0026deg;) and two directions (left and right), with the trial order randomly assigned and a 3-minute recovery interval provided between trials. Participants initially assumed a standardized defensive stance facing directly forward behind the starting line, with their body orientation subsequently adjusted to align with predefined angular markers (45\u0026deg;, 90\u0026deg;, 135\u0026deg;) on the floor. Two identical marker posts were positioned at the start and finish lines of each angular path to standardize foot contact accuracy. Upon the auditory \u0026quot;Go\u0026quot; command, participants performed maximal-effort shuffles along the designated angular path while maintaining the required defensive posture throughout the movement. Movement time was recorded using the CODTimer smartphone application (Balsalobre-Fern\u0026aacute;ndez et al., 2019; Bishop et al., 2022a), with an iPhone positioned perpendicular to the finish line at a 5-meter distance to ensure full-body kinematic capture. The first frame in which the foot closest to the movement direction left the ground (indicating the start of the shuffle), and the frame in which the same foot crossed the marker post (indicating the end of the shuffle), were selected to calculate shuffle performance. Three successful trials per condition were recorded, excluding attempts where participants failed to touch both marker posts.\u003c/p\u003e\n\u003ch2\u003e2.4\u0026nbsp; \u0026nbsp; \u0026nbsp;Statistical Analysis\u003c/h2\u003e\n\u003cp\u003eThe descriptive data are presented as means \u0026plusmn; standard deviations (SD). Normality of the data distribution and homogeneity of variance were assessed using the Shapiro-Wilk and Levene\u0026rsquo;s methods, respectively. Reliability was assessed using a two-way random intra-class correlation coefficient (ICC) with absolute agreement and 95% confidence intervals, typical error of the measurement (TEM), and the coefficient of variation (CV). The magnitude of the CV was interpreted as follows: poor ( \u0026gt; 10%), moderate (5 \u0026ndash; 10%) or good ( \u0026lt; 5%) (Banyard et al., 2017). The interpretation of ICC values was based on the lower bound of the 95% confidence interval, following the criteria proposed by Koo and Li (Koo and Li, 2016), where ICC \u0026lt; 0.5 was considered poor, 0.5 \u0026ndash; 0.75 moderate, 0.75 \u0026ndash; 0.9 good, and \u0026gt; 0.9 excellent. The asymmetry index was calculated using the following formula: asymmetry index = (better-performing side - poorer-performing side) / better - performing side \u0026times; 100% .(Bishop et al., 2023). The data were analyzed using SPSS 27.0 (IBM Corp., Armonk, NY, USA). A two-way repeated-measures ANOVA [angle (45\u0026deg;, 90\u0026deg;, 135\u0026deg;) \u0026times; direction (left, right)] was performed to examine the combined effects of angular displacement and movement direction on lateral shuffling speed. Post hoc pairwise comparisons with Bonferroni adjustments were conducted when significant interactions emerged. To assess whether movement angles influenced shuffle asymmetry, a Kruskal-Wallis H test was employed due to the non-normal distribution of asymmetry indices (Shapiro-Wilk \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Post hoc test with Bonferroni correction was subsequently applied to determine between-angle differences when a significant main effect was detected. The Kappa coefficient was calculated to evaluate the level of consistency in asymmetry favoring the same side (asymmetry direction) (Bishop, 2021). Kappa values were interpreted as follows: \u0026le; 0 poor agreement, 0.01 \u0026ndash; 0.20 slight agreement, 0.21 \u0026ndash; 0.40 fair agreement, 0.41 \u0026ndash; 0.60 moderate agreement, 0.61 \u0026ndash; 0.80 substantial agreement, and 0.81 \u0026ndash; 0.99 almost perfect agreement (Bishop et al., 2023). All statistical analyses were conducted using IBM SPSS software version 26.0 (IBM, Armonk, NY, USA).\u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003eTable 1 presents the performance, shuffle asymmetry, and reliability data of different direction shuffle tests. All tests demonstrated excellent reliability with ICC ranging from 0.94 to 0.97 (all \u0026ge; 0.90). CV values remained within acceptable thresholds ( \u0026lt; 10%), measuring 2.4 \u0026ndash; 3.2% across conditions. All measured parameters adhered to normal distributions. The two-way ANOVA results indicated a significant main effect of angle (F = 12.334, p \u0026lt; 0.001, \u0026eta;\u0026sup2; = 0.231), no significant main effect of direction (F = 0.040, p = 0.842, \u0026eta;\u0026sup2; = 0.001), and a significant angle-direction interaction effect (F = 14.489, p \u0026lt; 0.001, \u0026eta;\u0026sup2; = 0.261). Post-hoc analysis revealed that: for the same direction at different angles, the lateral shuffle speeds at left 45\u0026deg; (3.02 \u0026plusmn; 0.33) and 90\u0026deg; (2.93 \u0026plusmn; 0.31) were both significantly higher than at left 135\u0026deg; (2.76 \u0026plusmn; 0.31, p \u0026lt; 0.001), while no significant differences were observed among the three angles on the right side (p \u0026gt; 0.05). For the same angle in different directions, significant differences in lateral shuffle speed were found between left and right sides at both 45\u0026deg; (left 3.02 \u0026plusmn; 0.33 vs. right 2.90 \u0026plusmn; 0.31) and 135\u0026deg; (left 2.76 \u0026plusmn; 0.31 vs. right 2.88 \u0026plusmn; 0.32, p \u0026lt; 0.05), whereas no significant difference was observed at 90\u0026deg; (left 2.93 \u0026plusmn; 0.31 vs. right 2.94 \u0026plusmn; 0.27, p \u0026gt; 0.05). The Kruskal-Wallis test showed no significant angle-dependent variations in shuffle asymmetry indices (\u0026chi;\u0026sup2; = 2.103, p = 0.349).\u003c/p\u003e\n\u003cp\u003eShuffle asymmetry magnitudes varied across angular conditions, measuring 5.9 \u0026plusmn; 4.0% (45\u0026deg;), 5.1 \u0026plusmn; 3.7% (90\u0026deg;), and 6.6 \u0026plusmn; 4.7% (135\u0026deg;). Consistency analysis in Table 2 revealed poor agreement between angular variants, evidenced by Kappa coefficients of 0.077 (45\u0026deg; vs 90\u0026deg;), 0.168 (45\u0026deg; vs 135\u0026deg;), and 0.078 (90\u0026deg; vs 135\u0026deg;).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Shuffle performance, asymmetry scores, and test reliability data.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"584\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eAsymmetry (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eICC (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003eS-45\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e3.02 \u0026plusmn; 0.33*\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e5.9 \u0026plusmn; 4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.96 (0.93 \u0026ndash; 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e2.9 (0.3 \u0026ndash; 9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e2.90 \u0026plusmn; 0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.94 (0.89 \u0026ndash; 0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e3.2 (0.8 \u0026ndash; 6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003eS-90\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e2.93 \u0026plusmn; 0.31*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e5.1 \u0026plusmn; 3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.97 (0.94 \u0026ndash; 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e2.6 (0.8 \u0026ndash; 5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e2.94 \u0026plusmn; 0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.95 (0.92 \u0026ndash; 0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e2.4 (0.3 \u0026ndash; 9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 61px;\"\u003e\n \u003cp\u003eS-135\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e2.76 \u0026plusmn; 0.31\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e6.6 \u0026plusmn; 4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.96 (0.93 \u0026ndash; 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e2.6 (0.5 \u0026ndash; 8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e2.88 \u0026plusmn; 0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.94 (0.89 \u0026ndash; 0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e3.1 (0.4 \u0026ndash; 8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAbbreviation:\u003c/em\u003e\u003cem\u003e\u0026nbsp;ICC, intra-class correlation coefficient; CV, coefficient of variation; S-45\u0026deg;\u003c/em\u003e\u003cem\u003e,\u0026nbsp;\u003c/em\u003e\u003cem\u003eS-90\u0026deg; and S-135\u0026deg;:\u003c/em\u003e\u003cem\u003e\u0026nbsp;shuffle test at\u0026nbsp;\u003c/em\u003e\u003cem\u003e45\u0026ordm;, 90\u0026ordm; and 135\u0026ordm;.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e* = significantly different with S-135\u003c/em\u003e\u003cem\u003e\u0026deg;; \u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;= significantly different with shuffle on right\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Kappa coefficients describing how consistently asymmetry favored the same side across shuffle angles (45\u0026deg;, 90\u0026deg;, 135\u0026deg;).\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eS-45\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eS-90\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eS-135\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eS-45\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eS-90\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eS-135\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eAbbreviation:\u003c/em\u003e\u003cem\u003e\u0026nbsp;S-45\u0026deg;\u003c/em\u003e\u003cem\u003e,\u0026nbsp;\u003c/em\u003e\u003cem\u003eS-90\u0026deg; and S-135\u0026deg;:\u003c/em\u003e\u003cem\u003e\u0026nbsp;shuffle test at\u0026nbsp;\u003c/em\u003e\u003cem\u003e45\u0026ordm;, 90\u0026ordm; and 135\u0026ordm;.\u003c/em\u003e\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe aims of this study were to examine the shuffle performance and asymmetry across different angles and directions among collegiate basketball players. Our results indicated that: 1) significant differences of shuffle performance were observed in shuffling at different angle; 2) shuffle asymmetry did not vary significantly across angles, and 3) no consistent directional dominance was observed across different shuffle tests.\u003c/p\u003e\n\u003cp\u003eThe observed results demonstrated that during left shuffling, the movement speed at 135\u0026deg; was significantly slower than at 45\u0026deg; and 90\u0026deg;. This finding supports our hypothesis, as previous studies have reported similar results (Rouissi et al., 2016; Gonzalo-Skok et al., 2023). Gonzalo-Skok et al. specifically found that basketball players 10-meter multi-angle\u0026apos; COD completion times increased with larger angles (45\u0026nbsp;\u0026ndash;\u0026nbsp;90\u0026deg;), then gradually stabilized during 135\u0026nbsp;\u0026ndash;\u0026nbsp;180\u0026deg; maneuvers. Studies in COD tasks have shown that as angles increase, athletes experience reduced approach velocity, prolonged ground contact times, smaller knee flexion angles, and increased joint loading complexity, indicating greater biomechanical demands at sharper angles\u0026nbsp;(Havens and Sigward, 2015; Schreurs\u0026nbsp;et al.,\u0026nbsp;2017; Dos\u0026rsquo;Santos et al., 2019). Although the shuffle task in our study differs from conventional COD maneuvers, particularly because it does not involve braking or turning phases, it is reasonable to speculate that larger angular displacements may impair movement efficiency due to altered neuromechanical demands. While this evidence originates from COD-based protocols, it may be partially applicable to multi-angled shuffle tasks. Nonetheless, direct empirical evidence on angle-specific demands in lateral shuffling remains limited and warrants further investigation. Notably, no significant inter-angle differences were observed during right shuffling. This finding may reflect greater neuromuscular control stability in the dominant side, potentially developed through long-term habitual movement patterns. Supporting this speculation, previous studies have reported that 94.9% of professional basketball players exhibit right-handed dominance\u0026nbsp;(Lawler and Lawler, 2011). However, since handedness cannot be directly equated with movement lateralization and no sport-specific studies have yet investigated shuffle-dominant sides in basketball players\u0026nbsp;(Virgile and Bishop, 2021), this interpretation should be treated with caution. Nevertheless, the angle-dependent performance variations being exclusively observed on the left side may reveal an underlying mechanism of directional movement asymmetry. These results further emphasize the necessity of implementing multi-angle, bilateral assessment in athletic performance evaluation to more comprehensively capture movement characteristics and potential asymmetric patterns.\u003c/p\u003e\n\u003cp\u003eFurthermore, the observed performance differences between left and right shuffles at 45\u0026deg; and 135\u0026deg; align with expectations, supporting the notion of inherent asymmetry in basketball lateral movements (Lyu et al., 2025a). Notably, in contrast to the significant bilateral differences in 90\u0026deg; shuffling previously reported by Lyu et al. our findings revealed no statistically significant disparities at this particular angle (Lyu et al., 2025a). However, the absence of such differences at 90\u0026deg; may be attributed to participant characteristics. While Lyu et al. examined pre-juvenile basketball players (aged 14 \u0026ndash; 15 years) (Lyu et al., 2025a), the current study involved college basketball players (aged 18 + years). The latter group\u0026apos;s longer duration of specialized training and systematic exposure to 90\u0026deg; lateral movements may have reduced this asymmetry. Additionally, variations in team training methodologies (e.g., emphasis on bilateral balance \u003cem\u003evs.\u003c/em\u003e unilateral reinforcement) could serve as potential influencing factors, although we recognize that this narrative is somewhat speculative.\u003c/p\u003e\n\u003cp\u003eAsymmetry indices demonstrated no significant variation across angles. While the mean asymmetry values at 45\u0026deg;, 90\u0026deg;, and 135\u0026deg; appeared similar, this statistical non-significance may be more reflective of data variability than an actual absence of true differences. As shown in Table 1, the SD for COD times represent approximately 10% of their means, whereas the SD for asymmetry indices account for 70 \u0026ndash; 90% of the mean values. This high relative variability substantially reduces the power to detect meaningful differences. Similar limitations have been highlighted in previous work (Bishop et al., 2019, 2022b; c), where asymmetry comparisons across tasks or sessions often failed to reach significance due to large within-subject variation, rather than the absence of a true effect. These findings emphasize the need for caution when interpreting group-based asymmetry data and reinforces the need to assess asymmetry on an individual basis (Bishop et al., 2021). This result is consistent with recent basketball-specific research by Gonzalo-Skok et al., who reported angle-independent asymmetry profiles in COD tasks (ES = 0.00 \u0026ndash; 0.58, p \u0026lt; 0.05) (Gonzalo-Skok et al., 2023). Lyu et al. and Bishop et al. also pointed out that the asymmetry exhibited by athletes in different tasks may vary depending on the type of task (Bishop et al., 2023; Lyu et al., 2025a), emphasizing the necessity of considering task specificity when assessing asymmetry. Additionally, the results demonstrated no consistent directional dominance across all angles. Figure 2 displays the individual asymmetry values at each angle, highlighting the variation in dominant side across conditions. This incongruity implies that limb dominance is task-angle dependent rather than a fixed neuromuscular trait\u0026mdash;a critical consideration for asymmetry screening protocols. The significant angle-direction interaction further supports that limb preference is modulated by task constraints rather than inherent physiological asymmetry. Gonzalo-Skok et al. similarly observed that preferred limb dominance can shift depending on the angle of direction change (Gonzalo-Skok et al., 2023). In our data, for example, some athletes exhibited left-side dominance at 45\u0026deg;, yet right-side dominance at 135\u0026deg;, emphasizing the need for angle-stratified asymmetry assessments (Gonzalo-Skok et al., 2023).\u003c/p\u003e\n\u003cp\u003eCoaches should consider specialized training at 45\u0026deg; and 135\u0026deg; directions to specifically address direction-specific movement performance differences, with particular emphasis on strengthening the significantly lagging left-side. Current data shows that the bilateral movement asymmetry index at 45\u0026deg; and 135\u0026deg; remains consistently high. This biomechanical imbalance not only restricts athletic performance but also more easily induces sports injuries (Afonso et al., 2022). Therefore, it is our suggestion that training programs should follow the \u0026quot;Bilateral Strength-Coordination Synchronized Development\u0026quot; principle (Zhao et al., 2023; Cadens et al., 2023). Specifically, an intervention strategy combining bilateral synchronous training with contralateral compensatory reinforcement training can be adopted to effectively reduce asymmetry coefficients (Bettariga et al., 2022), improve movement performance and control injury risks. We recommend using multi-angle assessments instead of traditional single-angle (e.g., only 90\u0026deg;) asymmetry tests to ensure comprehensive capture of contextual neuromuscular imbalance characteristics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite methodological advancements, three limitations constrain broader applicability. First, the absence of kinetic/kinematic data (e.g., ground reaction forces, joint angles) precludes mechanistic explanations for angular performance gradients; future studies must integrate force plates and 3D motion capture to delineate load distribution patterns. Second, generalizability to elite or youth cohorts remains unverified due to the exclusive focus on college athletes, necessitating cross-population validations. Third, despite implementing 3-minute inter-trial rest periods, the accumulation of neuromuscular fatigue across 18 maximal-effort trials (6 conditions \u0026times; 3 repetitions) within a single testing session may have systematically biased performance outcomes in later conditions. To mitigate this confounder, future experimental designs should adopt session-separated protocols.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eIn conclusion, the shuffle performance of college basketball players differs by angle, with the 135\u0026deg; shuffle being the slowest. Although asymmetry magnitudes remained relatively stable across angles, no consistent directional advantage was observed at any angle, indicating that limb dominance is influenced by task-specific demands.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the standards set by the 2013 revision of the Declaration of Helsinki and was approved by the Institutional Ethics Committee of Beijing Sport University, Beijing, China (approval number: 2024409H). All participants provided written informed consent after receiving a full explanation of the study\u0026rsquo;s purpose, procedures, and potential risks.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch4\u003eAvailability of data and materials\u003c/h4\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch4\u003eCompeting interests\u003c/h4\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare that no financial support was received for the research and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZL and ML:\u003c/strong\u003e Conceptualization, Writing; \u003cstrong\u003eLD and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMT\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Methodology, Data curation;\u0026nbsp;\u003cstrong\u003eZL and ML:\u003c/strong\u003e Software; \u003cstrong\u003eZL and YL:\u0026nbsp;\u003c/strong\u003eValidation;\u0026nbsp;\u003cstrong\u003eMT\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eformal analysis; \u003cstrong\u003eZL:\u003c/strong\u003e writing\u0026mdash;original draft preparation; \u003cstrong\u003eZL, ML and\u0026nbsp;CB:\u0026nbsp;\u003c/strong\u003ewriting\u0026mdash;review \u0026amp; editing; \u003cstrong\u003ePW:\u0026nbsp;\u003c/strong\u003evisualization; \u003cstrong\u003eCB\u003c/strong\u003e: Reviewing; \u003cstrong\u003eYL:\u003c/strong\u003e Project administration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the participants and coaches from the university basketball teams for their cooperation throughout the study. We are grateful for all the assistance and support provided by the staff. We also sincerely thank Professor Chris Bishop and Professor Yongming Li for their valuable academic guidance and insightful suggestions during the development of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAfonso, J., Pe\u0026ntilde;a, J., S\u0026aacute;, M., Virgile, A., Garc\u0026iacute;a-de-Alcaraz, A. and Bishop, C. (2022) Why Sports Should Embrace Bilateral Asymmetry: A Narrative Review. \u003cem\u003eSymmetry.\u003c/em\u003e 14, 1993. doi: 10.3390/sym14101993\u003c/li\u003e\n\u003cli\u003eBalsalobre-Fern\u0026aacute;ndez, C., Bishop ,Chris, Beltr\u0026aacute;n-Garrido ,Jos\u0026eacute; Vicente, Cecilia-Gallego ,Pau, Cuenca-Amig\u0026oacute; ,Aleix, Romero-Rodr\u0026iacute;guez ,Daniel, et al. (2019) The validity and reliability of a novel app for the measurement of change of direction performance. \u003cem\u003eJ Sport Sci.\u003c/em\u003e 37, 2420\u0026ndash;2424. doi: 10.1080/02640414.2019.1640029\u003c/li\u003e\n\u003cli\u003eBanyard, H.G., Nosaka, K. and Haff, G.G. (2017) Reliability and Validity of the Load\u0026ndash;Velocity Relationship to Predict the 1RM Back Squat. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 31, 1897\u0026ndash;1904. doi: 10.1519/jsc.0000000000001657\u003c/li\u003e\n\u003cli\u003eBettariga, F., Turner, A., Maloney, S., Maestroni, L., Jarvis, P. and Bishop, C. (2022) The Effects of Training Interventions on Interlimb Asymmetries: A Systematic Review With Meta-analysis. \u003cem\u003eStrength Cond J.\u003c/em\u003e 44, 69\u0026ndash;86. doi: 10.1519/ssc.0000000000000701\u003c/li\u003e\n\u003cli\u003eBishop, C. (2021) Interlimb Asymmetries: Are Thresholds a Usable Concept? \u003cem\u003eStrength Cond J.\u003c/em\u003e 43, 32\u0026ndash;36. doi: 10.1519/ssc.0000000000000554\u003c/li\u003e\n\u003cli\u003eBishop, C., de Keijzer, K.L., Turner, A.N. and Beato, M. (2023) Measuring Interlimb Asymmetry for Strength and Power: A Brief Review of Assessment Methods, Data Analysis, Current Evidence, and Practical Recommendations. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 37, 745\u0026ndash;750. doi: 10.1519/JSC.0000000000004384\u003c/li\u003e\n\u003cli\u003eBishop, C., Lake, J., Loturco, I., Papadopoulos, K., Turner, A. and Read, P. (2021) Interlimb Asymmetries: The Need for an Individual Approach to Data Analysis. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 35, 695\u0026ndash;701. doi: 10.1519/jsc.0000000000002729\u003c/li\u003e\n\u003cli\u003eBishop, C., Perez-Higueras Rubio, M., Gullon, I.L., Maloney, S. and Balsalobre-Fernandez, C. (2022a) Jump and Change of Direction Speed Asymmetry Using Smartphone Apps: Between-Session Consistency and Associations With Physical Performance. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 36, 927\u0026ndash;934. doi: 10.1519/JSC.0000000000003567\u003c/li\u003e\n\u003cli\u003eBishop, C., Read, P., Bromley, T., Brazier, J., Jarvis, P., Chavda, S., et al. (2022b) The Association Between Interlimb Asymmetry and Athletic Performance Tasks: A Season-Long Study in Elite Academy Soccer Players. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 36, 787\u0026ndash;795. doi: 10.1519/JSC.0000000000003526\u003c/li\u003e\n\u003cli\u003eBishop, C., Read, P., Chavda, S., Jarvis, P., Brazier, J., Bromley, T., et al. (2022c) Magnitude or Direction? Seasonal Variation of Interlimb Asymmetry in Elite Academy Soccer Players. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 36, 1031\u0026ndash;1037. doi: 10.1519/JSC.0000000000003565\u003c/li\u003e\n\u003cli\u003eBishop, C., Read, P., Chavda, S., Jarvis, P. and Turner, A. (2019) Using Unilateral Strength, Power and Reactive Strength Tests to Detect the Magnitude and Direction of Asymmetry: A Test-Retest Design. \u003cem\u003eSports.\u003c/em\u003e 7, 58. doi: 10.3390/sports7030058\u003c/li\u003e\n\u003cli\u003eBishop, C., Turner, A. and Read, P. (2018) Training Methods and Considerations for Practitioners to Reduce Interlimb Asymmetries. \u003cem\u003eStrength Cond J.\u003c/em\u003e 40, 40\u0026ndash;46. doi: 10.1519/ssc.0000000000000354\u003c/li\u003e\n\u003cli\u003eCadens, M., Planas-Anzano, A., Peirau-Ter\u0026eacute;s, X., Bishop, C., Romero-Rodr\u0026iacute;guez, D. and Madruga-Parera, M. (2023) Relationship between Asymmetry Profiles and Jump Performance in Youth Female Handball Players. \u003cem\u003eJ Hum Kinet.\u003c/em\u003e 87, 5\u0026ndash;16. doi: 10.5114/jhk/163432\u003c/li\u003e\n\u003cli\u003eCroisier, J.-L., Ganteaume, S., Binet, J., Genty, M. and Ferret, J.-M. (2008) Strength Imbalances and Prevention of Hamstring Injury in Professional Soccer Players: A Prospective Study. \u003cem\u003eAm J Sport Med.\u003c/em\u003e 36, 1469\u0026ndash;1475. doi: 10.1177/0363546508316764\u003c/li\u003e\n\u003cli\u003eDing, L., Lyu, M., Chen, Z., Wu, J., Wang, Y., Bishop, C., et al. (2024) Associations Between Inter-Limb Asymmetry in Lower Limb Strength and Jump Performance in 14\u0026ndash;15-Year-Old Basketball Players. \u003cem\u003eSymmetry.\u003c/em\u003e 16, 1421. doi: 10.3390/sym16111421\u003c/li\u003e\n\u003cli\u003eDos\u0026rsquo;Santos, T., McBurnie, A., Thomas, C., Comfort, P. and Jones, P. (2019) Biomechanical Determinants of the Modified and Traditional 505 Change of Direction Speed Test. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 34, 1285\u0026ndash;1296. doi: 10.1519/JSC.0000000000003439\u003c/li\u003e\n\u003cli\u003eGonzalo-Skok, O., Dos\u0026rsquo;Santos, T. and Bishop, C. (2023) Assessing Limb Dominance and Interlimb Asymmetries Over Multiple Angles During Change of Direction Speed Tests in Basketball Players. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 37, 2423\u0026ndash;2430. doi: 10.1519/jsc.0000000000004558\u003c/li\u003e\n\u003cli\u003eHavens, K.L. and Sigward, S.M. (2015) Whole body mechanics differ among running and cutting maneuvers in skilled athletes. \u003cem\u003eGait Posture.\u003c/em\u003e 42, 240\u0026ndash;245. doi: 10.1016/j.gaitpost.2014.07.022\u003c/li\u003e\n\u003cli\u003eKoo, T.K. and Li, M.Y. (2016) A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. \u003cem\u003eJ Chiropr Med.\u003c/em\u003e 15, 155\u0026ndash;163. doi: 10.1016/j.jcm.2016.02.012\u003c/li\u003e\n\u003cli\u003eLawler, T.P. and Lawler, F.H. (2011) Left-Handedness in Professional Basketball: Prevalence, Performance, and Survival. \u003cem\u003ePercept Motor Skill.\u003c/em\u003e 113, 815\u0026ndash;824. doi: 10.2466/05.19.25.PMS.113.6.815-824\u003c/li\u003e\n\u003cli\u003eLoturco, I., Pereira, L.A., Kobal, R., Abad, C.C.C., Rosseti, M., Carpes, F.P., et al. (2019) Do asymmetry scores influence speed and power performance in elite female soccer players? \u003cem\u003eBiol Sport.\u003c/em\u003e 36, 209\u0026ndash;216.. doi: 10.5114/biolsport.2019.85454\u003c/li\u003e\n\u003cli\u003eLyu, M., Chen, Z., Deng, S., Ding, L., Han, J., Bishop, C., et al. (2025a) Asymmetry of the Single Leg Jump and Lateral Shuffle Performance in Pre-Juvenile Basketball Players. \u003cem\u003eJ Hum Kinet.\u003c/em\u003e 96, 109\u0026ndash;119. doi: 10.5114/jhk/196315\u003c/li\u003e\n\u003cli\u003eLyu, M., Yin, M., Ding, L., Tang, R., Chen, Z., Deng, S., et al. (2025b) Physiological and Neuromuscular Fatigue after 3-Minute Lateral Shuffle Movement at Different Speeds and Distances. \u003cem\u003eJ Hum Kinet.\u003c/em\u003e 95, 151\u0026ndash;159. doi: 10.5114/jhk/190145\u003c/li\u003e\n\u003cli\u003eMadruga-Parera, M., Bishop, C., Beato, M., Fort-Vanmeerhaeghe, A., Gonzalo-Skok, O. and Romero-Rodr\u0026iacute;guez, D. (2021) Relationship Between Interlimb Asymmetries and Speed and Change of Direction Speed in Youth Handball Players. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 35, 3482\u0026ndash;3490. doi: 10.1519/jsc.0000000000003328\u003c/li\u003e\n\u003cli\u003eMaloney, S.J. (2019) The Relationship Between Asymmetry and Athletic Performance: A Critical Review. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 33, 2579\u0026ndash;2593. doi: 10.1519/jsc.0000000000002608\u003c/li\u003e\n\u003cli\u003eRouissi, M., Chtara ,Moktar, Owen ,Adam, Chaalali ,Anis, Chaouachi ,Anis, Gabbett ,Tim, et al. (2016) Effect of leg dominance on change of direction ability amongst young elite soccer players. \u003cem\u003eJ Sport Sci.\u003c/em\u003e 34, 542\u0026ndash;548. doi: 10.1080/02640414.2015.1129432\u003c/li\u003e\n\u003cli\u003eSchreurs, M.J., Benjaminse, A. and Lemmink, K.A.P.M. (2017) Sharper angle, higher risk? The effect of cutting angle on knee mechanics in invasion sport athletes. \u003cem\u003eJ Biomech.\u003c/em\u003e 63, 144\u0026ndash;150. doi: 10.1016/j.jbiomech.2017.08.019\u003c/li\u003e\n\u003cli\u003eSubramanium, A., Honert ,Eric C., Cigoja ,Sasa and and Nigg, B.M. (2021) The effects of shoe upper construction on mechanical ankle joint work during lateral shuffle movements. \u003cem\u003eJ Sport Sci.\u003c/em\u003e 39, 1791\u0026ndash;1799. doi: 10.1080/02640414.2021.1898174\u003c/li\u003e\n\u003cli\u003eTaylor, J.B., Wright, A.A., Dischiavi, S.L., Townsend, M.A. and Marmon, A.R. (2017) Activity Demands During Multi-Directional Team Sports: A Systematic Review. \u003cem\u003eSports Med.\u003c/em\u003e 47, 2533\u0026ndash;2551. doi: 10.1007/s40279-017-0772-5\u003c/li\u003e\n\u003cli\u003eTurki, O., Dhahbi, W., Padulo, J., Khalifa, R., Rid\u0026egrave;ne, S., Alamri, K., et al. (2020) Warm-Up With Dynamic Stretching: Positive Effects on Match-Measured Change of Direction Performance in Young Elite Volleyball Players. \u003cem\u003eInternational Journal of Sports Physiology and Performance.\u003c/em\u003e 15, 528\u0026ndash;533. doi: 10.1123/ijspp.2019-0117\u003c/li\u003e\n\u003cli\u003eVirgile, A. and Bishop, C. (2021) A Narrative Review of Limb Dominance: Task Specificity and the Importance of Fitness Testing. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 35, 846\u0026ndash;858. doi: 10.1519/jsc.0000000000003851\u003c/li\u003e\n\u003cli\u003eWang, P., Lyu, M., Geng, N., Wu, Z., Ren, X., Kozinc, Ž., et al. (2025) Asymmetry in college basketball players: change of direction performance in shuffle movement and 505 test. \u003cem\u003eFront Physiol\u003c/em\u003e. 16, 1587719. doi: 10.3389/fphys.2025.1587719\u003c/li\u003e\n\u003cli\u003eWhitting, J.W., de Melker Worms, J.L.A., Maurer, C., Nigg, S.R. and Nigg, B.M. (2013) Measuring Lateral Shuffle and Side Cut Performance. \u003cem\u003eJ Strength Cond Res.\u003c/em\u003e 27, 3197\u0026ndash;3203. doi: 10.1519/jsc.0b013e31828a2c2b\u003c/li\u003e\n\u003cli\u003eZhao, X., Turner, A.P., Sproule, J. and Phillips, S.M. (2023) The Effect of Unilateral and Bilateral Leg Press Training on Lower Body Strength and Power and Athletic Performance in Adolescent Rugby Players. \u003cem\u003eJ Hum Kinet.\u003c/em\u003e 86, 235\u0026ndash;246. doi: 10.5114/jhk/159626\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"agility, multidirectional, between-limb differences, movement performance, Basketball player","lastPublishedDoi":"10.21203/rs.3.rs-7819352/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7819352/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObjective: This study aims to examine the shuffle performance and asymmetry across different angles and directions among collegiate basketball players.\u003c/p\u003e\n\u003cp\u003eMethods: Forty-two players completed six randomized shuffle tests at two directions (left/right) and three angles (45°/90°/135°). The shuffle asymmetry index was calculated as (dominant – non-dominant) / dominant × 100% . Two-way repeated-measures ANOVA and Kruskal-Wallis tests were used to analyze shuffle performance and asymmetry in different angles. Kappa coefficient evaluated directional asymmetry consistency.\u003c/p\u003e\n\u003cp\u003eResults: Results showed excellent reliability across conditions (ICC = 0.94 – 0.97; CV = 2.4 – 3.2%). A significant main effect of angle (F = 12.334, p \u0026lt; 0.001) and an angle × direction interaction (F = 14.489, p \u0026lt; 0.001) were observed. Left‐ward shuffles at 135° (2.76 ± 0.31) were slower than at 45° and 90° (all p \u0026lt; 0.001), whereas right‐ward performance did not differ by angle (p \u0026gt; 0.05). No significant difference in the asymmetry of shuffle from different angles (χ² = 2.103, p = 0.349; mean 5.1 – 6.6%), and kappa coefficients indicated poor consistency of directional dominance (k = 0.077 – 0.168).\u003c/p\u003e\n\u003cp\u003eConclusion:\u003cem\u003e \u003c/em\u003eThe shuffle performance was jointly influenced by angle and direction. The magnitude of shuffle asymmetry remained consistent across angles, suggesting that movement asymmetry was task-dependent rather than fixed. These findings support the implementation of multi-angle shuffle in training and evaluation protocols to enhance performance.\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e","manuscriptTitle":"Performance and Asymmetry of Shuffling Tasks at Different Angles and Directions in Collegiate Basketball Players","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-19 09:44:43","doi":"10.21203/rs.3.rs-7819352/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8a337208-c010-4849-8b94-05df531c0a72","owner":[],"postedDate":"November 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-25T08:42:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-19 09:44:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7819352","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7819352","identity":"rs-7819352","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}