European journal of sport science最新文献

In sports, injury prevention is a key factor for success. Although injuries are challenging to predict, new technologies and the application of data science can provide valuable insights. This study aimed to predict injury risk among professional rugby union players using machine learning (ML) models. We analyzed data from 63 professional rugby union players during three seasons, categorized them into forwards and backs, and further classified them into five specific positions (tight five, back row, scrum-half, inside backs, outside backs). The dataset included GPS data and derived metrics such as total workload in the 1, 2, and 3 weeks prior to injury, acute-to-chronic workload ratio over different time windows, monotony, and strain. Injury prediction was assessed separately for different player positions using five ML classification models: logistic regression, naïve Bayes (NB), support vector machine, random forest (RF), and eXtreme gradient boosting (XGBoost). RF performed best for forwards overall, with XGBoost excelling in the tight five and SVM in the back row, whereas among backs, RF led for inside backs and NB for outside backs. Additionally, feature importance plots were used to examine the impact of various factors on injury occurrence. In conclusion, our ML-based approach can effectively predict injuries, with average F1 scores up to 0.66 (± 0.14), particularly when applying a combination of GPS-derived metrics. Additionally, key characteristics indicative of injury for players in various positions have been successfully identified. These findings underscored the potential of ML to enhance injury prediction and inform tailored training strategies for athletes.

A novel method for estimating V̇O₂peak using seismocardiography (SCG eV̇O₂peak) at rest was developed some years ago, and this study investigates an updated version using data from a trained population. Forty five subelite female and Sixty seven elite male football players were tested and included in a cross-sectional accuracy comparison between SCG eV̇O₂peak and V̇O₂peak obtained from an incremental cardiopulmonary exercise test (CPET) performed on a treadmill. In addition, the ability of the method to detect changes over time was assessed by comparison of changes in V̇O₂peak over 3 months (female and male, n = 60), 6 months (female, n = 17), and 1 year (male, n = 18) for CPET and SCG, respectively. No difference and a fair agreement were found between combined sex cross-sectional SCG eV̇O₂peak and CPET V̇O₂peak (bias ± 95% CI: −1.0 ± 0.9 mL·min⁻¹·kg⁻¹ and limits of agreement [95%]: ± 9.1 mL·min⁻¹·kg⁻¹), with similar agreement between sexes. The standard error of estimation and mean absolute percentage error were 4.8 mL·min⁻¹·kg⁻¹ and 7.4%, respectively. V̇O₂peak was only increased over 6 months for females (CPET: 2.2 ± 1.1 mL·min⁻¹·kg⁻¹, SCG: 1.2 ± 1.1 mL·min⁻¹·kg⁻¹, and p < 0.05) with no difference between methods (p = 0.170). A correlation between ΔV̇O₂peak for CPET and SCG was found for 1-year analyses (male, R² = 0.62, and P < 0.05) but no other correlations were significant. The SCG method is accurate in estimating V̇O₂peak in both subelite and elite football players, with fair agreement and low estimation errors. The SCG method was able to detect an association of 1-year changes but not for changes over shorter times; however, these results require more investigation due to small sample sizes.

Increasing the length of the biceps femoris long head (BFlh) fascicle is one of the objectives of hamstring injury prevention programs. This study aimed to investigate training-induced adaptations in BFlh architecture and performance measures after a six-week resistance training program with gravitational or inertial 45° hip extension (HE) exercise and a subsequent detraining period. Thirty-two resistance-trained males were assigned to a group doing a HE training program with gravitational loading (HE-G), HE by inertial loading (HE-I), or to a control group (CG). BFlh architecture, knee flexion and hip extension strength, jumping performance by means of the countermovement (CMJ) and squat jump (SJ) tests, and soreness before and after each training session were evaluated. HE-I participants modified the initial length of the BHlh fascicle (9.86 cm), increasing it by 1.64 cm at the end of the intervention and remaining 1.48 cm longer than baseline after the detraining period. Both HE modalities improved hip extensor strength (51.2 N for HE-G and 65.0 N) and only HE-I improved knee flexor strength (69.9 N). Soreness for HE-I exercise showed lower values than gravity-loaded performance, with at least one point difference across sessions, and more than two in some of the final sessions. This study provides evidence suggesting that HE performed with inertial loading is an effective exercise for lengthening the BFlh fascicle and promoting improvements in knee flexion strength and SJ performance, aspects not modifiable by the gravitational modality.

Caffeine and taurine are commonly co-ingested pre-exercise but elicit different thermoregulatory responses; however, their combined effect on thermoregulation is unknown. Therefore, we evaluated the effects of oral caffeine and taurine co-ingestion on time to exhaustion (TTE) and thermoregulatory responses to cycling in the heat at the gas exchange threshold (GET). Ten healthy nonheat acclimated participants took part in a double-blind crossover study, completing a TTE in the heat (35°C; 40% relative humidity), cycling at a power output associated with the GET and 1 h after ingesting: caffeine (5 mg/kg) and taurine (50 mg/kg) combined or placebo. Pulmonary gas exchange, core and mean skin temperatures and whole-body sweat rate (WBSR) were recorded throughout. Heat production was determined using partitional calorimetry. There were no differences in TTE between conditions (p = 0.608); however, the rate of oxygen consumption (p = 0.017), minute ventilation (p = 0.029) and heat production (p = 0.019) were higher following the supplement. There were no differences between conditions for skin (p = 0.539) and core temperature (p = 0.699), mean skin blood flow (p = 0.119), respiratory exchange ratio (p = 0.546) and WBSR (p = 0.897). Pre-exercise co-ingestion of caffeine and taurine in the heat had no ergogenic effect despite increasing the ventilatory and metabolic demand. Collectively, these data indicate minimal effects on whole-body thermoregulation.

This study investigated the associations between ovarian hormones, symptoms, sleep characteristics and nocturnal physiology in female athletes. Twenty-four National Rugby League Indigenous Women's Academy athletes (naturally cycling: n = 11 and mean age: 21 ± 3 years; hormonal contraception: n = 13 and mean age: 22 ± 3 years) completed a 5-week training camp. During the camp, oestradiol and progesterone concentrations were analysed at three timepoints according to naturally cycling and hormonal contraception groups. Symptoms and subjective sleep were measured daily. Athletes were instructed to wear an Oura ring throughout the camp for sleep and nocturnal heart rate (HR) and HR variability (HRV) measures. Statistical analyses included linear mixed models and Pearson's correlations. Neither objective (Oura ring) nor subjective (survey) sleep characteristics were associated with oestradiol or progesterone concentrations. In the naturally cycling group, a higher number of total symptoms were associated with a longer sleep onset latency (r = 0.88, 95% CI [0.60, 0.97]) and increased light sleep (r = 0.75, 95% CI [0.28, 0.93]). Higher oestradiol concentrations were significantly associated with fewer symptoms (estimate ± SE: −0.007 ± 0.002 symptoms, p = 0.003). Luteal days were associated with higher average nocturnal HR and lower HRV than follicular menstrual cycle days (estimate ± SE: 4 ± 0.57 bpm, p < 0.001; estimate ± SE: −7 ± 2.13 ms, p < 0.001, respectively). Negligible to moderate correlations were observed between sleep and total symptoms experienced by athletes using hormonal contraception. In conclusion, sleep measures were not significantly associated with ovarian hormone concentrations. A higher number of total symptoms were associated with sleep disturbance in naturally cycling athletes. To optimise sleep, female athletes may benefit from monitoring and managing menstrual cycle symptoms.

This study investigated the effects of high-intensity interval training (HIIT) with different work-to-rest ratios during the same training duration on the specific physical fitness of Chinese adolescent taekwondo athletes (N = 30, 16–20 years, 18 males and 12 females, and provincial champion/runner-up or national top 6). Athletes were randomly allocated to HIIT-20S (20 s work: 10 s rest), HIIT-30S (30 s work: 10 s rest), and a control group (2 min actual combat competitive: 1 min rest). An 8-week intervention (24 sessions, 30 min/session). Specific physical fitness was assessed using the progressive specific taekwondo test, frequency speed of kick test, 10-s high roundhouse kick test, 60-s double chop kick test, heart rate recovery (HRR), 1 repetition maximum (1-RM) squat test, and improved Illinois agility test. Statistical significance was defined as p < 0.05. Compared with the HIIT-20S (1.96%) and control (0.47%) groups, the HIIT-30S group demonstrated a significantly greater improvement in VO2peak (4.72%). In the FSKT10S test, the HIIT-20S group performed better than the HIIT-30S group (2.24% vs. 1.34%), whereas the HIIT-30S group showed higher gains in FSKTtotal (5.09% vs. 2%) and a steeper decline in KDI (−21.7% vs. −12.1%). Similarly, the HIIT-20S group outperformed the HIIT-30S group in the 10S-HRK test (3.62% vs. 0.91%), whereas the HIIT-30S group outperformed the 60S-DCK test (3.45% vs. 1.91%). Improvements in agility favored the HIIT-20S group (−8.26% vs. HIIT-30S: −4.01%; control: −0.85%). Both HIIT groups showed enhanced heart rate recovery (HIIT-30S, 2.74% and HIIT-20S, 2.57%), although no significant differences were observed in lower limb maximal strength. These findings confirm the specificity of the work-to-rest ratio: HIIT-30S effectively enhances cardiorespiratory endurance and repeated kicking endurance, whereas HIIT-20S appears to be more beneficial for optimizing explosive strength, agility, kick speed, and frequency.

The purpose of this study was to evaluate the evolution of jump and sprint force-production capacities with maturation in young soccer players. One hundred sixteen young elite male soccer players aged 11–17 years were assigned to six different groups according to their maturity status. The force–velocity (F–V) profiles in jumping and sprinting performances were compared among groups. The results show a significant, progressive, and linear improvement in the majority of F–V profile determinants of jumping and sprinting performances in parallel with maturation. When comparisons were carried out between consecutive groups, significant differences between PHV−1 and PHV groups in H_max (p < 0.05), H₆₀ (p < 0.05), VT-F0 (p < 0.05), and VT-P_max (p < 0.05) were observed but disappeared when these variables were expressed relative to body mass. Regarding the F–V profile determinants of sprinting performance, we observed significantly shorter sprint times in PHV compared to PHV−1 and in PHV+2 in comparison with the PHV+1 group. These between-group differences were associated with significant greater HZT-F0 kg⁻¹ (p < 0.05) and HZT-P_max kg⁻¹ (p < 0.001). However, significantly more negative value of HZT-Sfv kg⁻¹ was observed in PHV−1 compared to PHV−2 (p < 0.05), in PHV+1 in comparison with PHV (p < 0.05) and in PHV+3 when compared to the PHV+2 group (p < 0.05). Thus, these findings revealed an alternation of accelerated periods of development in force and velocity qualities, expressing sprinting performance, with maturation during the physical development process of young soccer players. Trainers and coaches should be aware of the distinct mechanical characteristics related to each maturity stage and design specific programs accordingly.

Load carriage training is universal during military training, regardless of sex or physical characteristics, and may contribute to the 1.3-2.2× higher incidence of patellofemoral pain (PFP) in female versus male recruits. This study aimed to assess sex differences in patellofemoral joint (PFJ) stress during load carriage, controlling for anthropometrics and quadriceps strength. Twenty males and 20 females walked (1.35 m/s) on an instrumented treadmill with 0-kg, 20.4-kg, and 34.0-kg of load carriage. An inverse-dynamics musculoskeletal model estimated peak, impulse, and cumulative PFJ stress. To assess quadriceps strength, peak isometric knee extensor torque normalized to body mass was measured via dynamometry. Analyses of covariance (ANCOVA) adjusting for body mass, height, and quadriceps strength assessed the effects of load (0-kg, 20.4-kg, and 34.0-kg) and biological sex (male, female) on PFJ stress and gait parameters. Females were shorter, had lower mass, and lower quadriceps strength (all p < 0.001; d = 1.50–1.54, indicating large effect sizes). Peak, impulse per step, and cumulative PFJ stress increased with load carriage, with greater increases in females compared to males (sex × load interactions p = 0.002–0.005; η_p² = 0.12–0.13, indicating moderate effect sizes) after controlling for body mass, height, and quadriceps strength. These data indicate that anthropometrics and quadriceps strength do not explain the substantially greater increases in per step and cumulative PFJ stress in females versus males with load carriage. Female recruits may benefit from targeted prevention efforts, such as slower progressions of load carriage training, either in amount carried or distance trained, to reduce their risk of PFP.

To assess whether certain players are more vulnerable to postmatch sleep disturbances by examining the relationship between match demands—collision frequency and locomotor load—and sleep in professional male rugby union players. A linear mixed-effects regression examined the relationship between match variables and sleep in 13 rugby players across three matches. Match variables included six physical demand variables derived from video analysis and GPS data (collision frequency, total distance, high-speed distance, sprint distance, acceleration load and fast acceleration count) and two contextual variables (location and kick-off time). Sleep variables collected via home-based polysomnography included total sleep time, sleep efficiency, sleep onset/offset, sleep onset latency, wake after sleep onset, number of awakenings and sleep stages (light, deep and rapid eye movement sleep [REM], evaluated both by proportion [%] and time [min]). Each match collision decreased total sleep time (β = −4 ± 1 min and p = 0.006) and REM sleep (time: β = −2 ± 0 min and p < 0.001; proportion: β = −0.6 ± 0.2% and p = 0.021). Conversely, every 500 m increase in locomotor load (total distance) increased REM sleep (time: β = +6 ± 2 min and p = 0.014; proportion: β = +2.7 ± 0.6% and p = 0.002). Every 100 m increase in high-speed distance was associated with decreased REM sleep time (β = −7 ± 3 min and p = 0.020). Match demands, including collision frequency and locomotor load, were associated with changes in postmatch sleep architecture in professional rugby players, particularly REM sleep. Furthermore, greater number of collisions was associated with reduced sleep quantity. Practitioners can leverage GPS and video analysis data to tailor additional sleep strategies aimed at improving postmatch sleep based on individual match demands.