ECSS Paris 2023: OP-AP20
INTRODUCTION: Boxing and Taekwondo are two of the most popular Olympic combat sports; both are striking disciplines with a similar work-rest ratio and match structure, but they are characterized by opposing limb involvement[1,2]. Given the need for discipline-specific athlete training prescriptions, our aim is to compare these two distinct sport-skills (kicking and punching) to assess the possible specific technique-adapted test[3]. Therefore, an existing taekwondo-specific test was modified to examine its validity for boxing by comparison with a maximal incremental treadmill ramp test (RampT)[4]. METHODS: 17 national-level boxing athletes (F=1;M=16; 27±5 years; 177.5±4.6 cm; 73.9±9,4 kg; 8±5 years of training experience) took part in the study. The assessments utilized were the RampT and the Intermittent Specific Test (IST), boxing-specific adaptation of the Short Intermittent Taekwondo Test (SITT)[4]; it includes 10 intermittent all-out stages performed at maximal hit frequency with alternating limbs, structured in 3 rounds with 30s rests: R1 with 4 progressive stages (10–25s), R2 and R3 with 3x25s stages and 5s inter-stage recovery. Subjects perform the two tests on separate days spaced by 7 to 15 days. Primary outcomes included VO2max, RER, blood lactate concentration after 3 min, HRmax, HR at 1 min recovery, and maximal perceived exertion (RPE 6-20 scale); the secondary outcome was the decline in striking frequency: Hit Fatigue Index (HFI). A Paired Samples T-Test and intraclass correlation coefficients (ICC) for reliability were performed. RESULTS: Compared with RampT, IST elicited significantly lower VO₂max (-10.8%, -5.6 mL·kg⁻¹·min⁻¹, p =0.006, d= 0.76), La⁺ (-16.1%, -1.7 mmol·L⁻¹, p = 0.038, d= 0.55), HRmax (-2.6%, -4.9 bpm, p= 0.002, d= 0.93), HR at 1 min recovery (-4.3%, -6.8 bpm, p=0.038, d= 0.55), and RER (-11.6%, -0.10, p=0.013, d= 0.68), whereas RPE was significantly higher (+7.3%, +1.2 AU, p=0.009, d= -0.72). HFI showed a limited decline in striking frequency (−3%). Agreement between IST and RampT was poor (ICC(2,1)= 0.467; 95% CI: 0.003–0.764). CONCLUSION: In national-level boxers, the boxing-adapted IST elicited lower maximal physiological responses than RampT but higher perceived exertion, indicating that it does not reproduce treadmill-derived maximal cardiorespiratory and metabolic responses. Agreement between tests was poor, suggesting limited concurrent validity of IST as a proxy of maximal aerobic fitness. The minimal decline in striking frequency further questions its sensitivity as a fatigue or profiling metric. The IST may nonetheless serve as a sport-specific, perceptually demanding assessment; however, its current structure may limit maximal aerobic involvement, and future work should explore modifications to work-rest ratios, test duration, or the integration of lower-limb actions prior to application in training prescription. [1] Davis 2015 [2] Santos 2011 [3] Chaabene 2018 [4] Panascì 2023
Read CV Alessandro PileriECSS Paris 2023: OP-AP20
INTRODUCTION: Studies have shown that pole vault performance is jointly influenced by key performance factors including approach run speed, take-off technique and physical strength [1-2]. However, a comprehensive model for predicting performance by integrating physical strength and approach run characteristics has not yet been established. This study aimed to construct and validate a model that synthesizes approach run characteristics and physical strength test indicators to predict athletes' pole vault performance using the principal component regression method. METHODS: Thirty-nine adolescent pole vaulters aged 12–16 years completed the Isometric Mid-thigh Pull (IMTP), hip adduction and abduction test, Athletic Shoulder Test (ASH) and CMJ test. The sprint speed and gait parameters of the last three steps at their optimal performance were also measured and calculated. After the indicators were standardized by Z-score, principal components with eigenvalues greater than 1 were extracted and subjected to varimax orthogonal rotation. A principal component regression model was then established, with the rotated factor scores as the independent variables and pole vault performance as the dependent variable. RESULTS: Principal component analysis yielded a KMO of 0.877. Three components were extracted, cumulatively explaining 79.5% of the variance. F1 (approach run characteristics) mainly loaded on the speed and step length of the last three steps; F2 (physical muscle strength) on peak hip abduction/adduction force, multi-directional upper limb peak force, and peak isometric mid-thigh pull force; F3 (lower limb explosive power) on average/peak propulsive force and power in the CMJ. All three components showed a significant correlation with pole vault performance (p<0.001). The regression model based on these components demonstrated strong predictive power (R²=0.833, adjusted R²=0.818, p<0.001). Approach run characteristics had the strongest predictive effect (β=0.56), followed by physical muscle strength (β=0.344), and lower limb explosive power (β=0.138). CONCLUSION: The results of this study indicated that approach run characteristics are the primary factor influencing pole vault performance, followed by muscle strength. It is suggested that in the pole vault training of adolescents, priority should be given to developing approach run speed and gait quality, while systematically improving the isometric strength of the upper and lower limbs. In addition, lower limb explosive power training should be used as a supplement to basic abilities, so as to achieve the coordinated improvement of technical skills and physical fitness. [1] Linthorne 2012 / [2] Li 2024
Read CV zhou yongECSS Paris 2023: OP-AP20
INTRODUCTION: Athletes who specialize in one sport do not seem to have an advantage in task-related performance compared to athletes who participate in multiple sports [1] while years of structured training in other sports seems to have a positive effect on performance [2]. Additionally, the maturation stage in which adolescent athletes are currently in influence the anthropometrical [3] and physical parameters [4]. Therefore, the aim of this study is to analyse the impact of sport diversification or specialization on anthropometrical, physical and biological characteristics of adolescent male athletes aged 12-16 years old. METHODS: 428 male athletes aged 12 (n=109), 13 (n=73), 14 (n=91), 15 (n=70), and 16 (n=85) years old were assessed and analysed from team and individual sports. Factorial Anova was used to investigate the differences. Body mass and height, age at peak height velocity (APHV), training age in other sports, speed (20m), strength (hand grip), and endurance (20m shuttle run test), were analysed by chronological age and by sport diversification or specialization. RESULTS: Better performances were observed for sport diversification at the age of 12 in body height [159.55 6.65cm. vs. 155.39 8.35cm., p=.025], in strength [27.12 8.91kg. vs. 23.26 5.23kg. p=.003], and in speed [3.73 0.43sec. vs. 3.89 0.39sec., p=.013], at 13 in endurance [1115.00 479.78m. vs. 911.80 375.42m., p=.041], at 14 in body height [179.03 6.67cm. vs. 171.11 8.61cm., p=.011] and in strength [43.18 12.15kg. vs. 36.87 8.95kg., p=.042], at 15 in body height [185.00 5.57cm vs. 174.06 7.00cm., p<.001] and mass [77.65 9.64kg. vs. 68.14 10.41kg., p=.027], and at 16 in endurance [1602.22 307.81m. vs. 1330.53 348.05m., p=.015]. Adolescent boys participating in multiple sports were more biologically mature at the age of 14 [13.42 0.42APHV vs. 14.05 0.78APHV, p = .014] and 15 [13.40 0.77APHV vs. 14.14 0.64APHV, p = .002]. While at the age of 12 [4.20 2.13y. vs. 2.82 2.27y., p=.014], 13 [5.97 2.77y. vs. 3.35 2.82y., p=.003], 14 [6.63 2.73y. vs. 3.49 2.64y., p=.006], and 15 [7.40 2.51y. vs. 3.39 2.95y., p=.007], multiple sport participation athletes have spent more years in structured training of other sports. CONCLUSION: Adolescent boys choose sport diversification, spent more training years in other sports, are taller and reveal a better performance, even with earlier biological maturity at 14 and 15 years old. 1 Kliethermes, et al. (2020) 2. Fransen et al. (2022) 3. Almeida-Neto et al. (2023) 4. Vaeyens et al. (2008).
Read CV Elisavet VelentzaECSS Paris 2023: OP-AP20