Visual Behavior in Inline Speed Skating: An Eye-Tracking Evaluation for Performance Analysis.

ObjectiveThis study aimed to describe the endurance training and incidence of illnesses reported by a group of well-trained cross-country (XC) skiers throughout their transition from junior to senior level.MethodsChanges in self-reported training and performance, from 31 well-trained XC skiers, were analyzed from the start of the season they turned 16 y until the end of the season they turned 22 y, using linear mixed-effects models. Differences in the incidence of self-reported illness episodes were analyzed using incidence rate ratios, and the relationships between self-reported illness and training volumes were analyzed using linear mixed-effects models in a sub-group of 23 of the skiers.ResultsIn total, 145 seasons of training data (including 85,846 h of endurance training) and 109 person-years of illness data (including 380 self-reported illness episodes) were analyzed. The athletes progressively increased their annual endurance training volume from age 16 to 22 y in a linear fashion, from ~ 470 to 730 h. Low- and high-intensity training volumes increased by 51.4 ± 2.4 h·y-1 (p < .001) and 4.9 ± 0.6 h·y-1 (p < .001), respectively. Sport-specific and non-specific training increased by 50.0 ± 2.2 h·y-1 (p < .001) and 4.6 ± 2.0 h·y-1 (p < .001), respectively. The athletes reported a median (range) of 3 (0–8) illness episodes and 17 (0–80) days of illness per year, and there was an inverse relationship between self-reported illness days and annual training volume (-0.046 ± 0.013 d·h-1; p < .001).ConclusionsThis group of well-trained XC skiers increased their endurance training volume in a linear fashion by ~ 55 h annually. This was primarily achieved through an increase in low-intensity and sport-specific training. Furthermore, higher training volumes were associated with a lower number of self-reported illness days.

Waldron, M, Gray, A, Furlan, N, and Murphy, A. Predicting the sprint performance of adolescent track cyclists using the 3-minute all-out test. J Strength Cond Res 30(8): 2299-2306, 2016-This study aimed to predict 500-m time trial (TT) and 2,000-m pursuit speed of adolescent cyclists (age range = 13-15 years) using mechanical parameters derived from a critical power (CP) test and anthropometric variables. Ten well-trained competitive cyclists were assessed for body composition, body mass, stature, and frontal surface area (FSA), as well as completing the CP test. The personal best speed (km·h) of each rider during competition in 500-m TT and 2,000-m pursuit races was predicted based on the CP test data and anthropometric profiles using multiple regression analysis. A combination of the CP·FSA and internal (predicted) to external work ratio performed by the cyclists (Wint:Wext) predicted 500-m TT speed (R = 0.97; standard error of the estimate (SEE) = 0.82, P ≤ 0.001), whereas a combination of mean power·FSA (mean power) and body fat percentage predicted 2,000-m pursuit speed (R = 0.90; SEE = 1.5, p < 0.001). Between 90 and 97% of the variance in the sprint performance of adolescent cyclists can be explained by mechanical and anthropometric parameters, derived from a single visit to the laboratory. The tests and equations provided can be adopted by coaches to predict performance and set appropriate training intensities.

Many factors, both external and internal, subjective and objective affect athletic performance. The most effective external factors in inline speed skating were identified by conducting a survey and pedagogical observation, and analysis of competitive activity. There are: wet asphalt (33.9 %), poor quality of asphalt (26.6 %) and a headwind (18.34 %). In general, more than 15 external factors, as well as such internal factor as feeling of well-being affect athletes.

Six world-class Chinese male rowers (age: 28.2 ± 3.2 years; height: 1.93 ± 0.02 m; body mass: 94.7 ± 3.9 kg) participated in the study. The training volume in different modalities and intensities were recorded over 44 weeks. To evaluate rowing performance, rowers completed four 2000 m and 5000 m maximum effort time trials and two incremental step tests. Total training time for the season was 907 h, which consisted of 67.5% of rowing training, 16.9% of strength training, 15.2% of warm-up and flexibility, and 0.4% of non-specific endurance training. The rowing training intensity distribution (TID) was 87.0% performed at low intensity (LIT), 8.4% at moderate intensity (MIT), and 4.6% at high intensity (HIT). There was no significant difference in average weekly rowing training volume (distance) at LIT across four phases (p = 0.12), as well as rowing training at MIT (p = 0.07) and HIT (p = 0.97). The fourth 2000 m time trials performance significantly improved from the first trial (−6.4 s, p = 0.02). The fourth 5000 m time trial performance was significantly improved from the first (−13.4 s, p = 0.02) and second trial (−14.1 s, p = 0.01). The final-step mean power output (W) in the second incremental step test improved significantly (p = 0.04). In the 2018–19 season, China's world-class rowers conducted considerable LIT rowing. The training volume distribution and rowing TID were similar in all phases.

Purpose: Peripheral adaptations, as assessed via near-infrared spectroscopy (NIRS) derived changes in muscle oxygenation (SmO2), are good predictors of sprint kayak performance. Therefore, the goal of the present study was to assess changes in SmO2 and O2 following a training camp in elite sprint kayakers to evaluate if the training prescribed elicits peripheral adaptations, and to assess associations between training-induced changes in physiological responses and performance.Methods: Eight male elite sprint kayakers, members of the Canadian National Team, performed a 200-m and 1,000-m on-water time trial (TT) before and after a 3-weeks winter training camp. Change in performance, O2 and SmO2 of the biceps brachii were assessed in relation to training load.Results: Training load and intensity were increased by ~20% over the course of the training camp, which resulted in a 3.7 ± 1.7% (ES 1.2) and 2.8 ± 2.4% (ES 1.3) improvement in 200-m and 1,000-m performance, respectively. Performance improvement in the 200-m was concomitant to a reduced SmO2, an increased O2 peak and an increased reoxygenation rate after the TT. The 1,000-m TT performance improvement was concurrent with a reduced SmO2 in the last half of the TT and an increased O2 in the first minute of the TT.Conclusion: Our results strongly suggest that peripheral skeletal muscle adaptations occurred in these athletes with the proposed training plan. This further attests the benefit of using portable NIRS as a monitoring tool to track training-induced adaptations in muscle oxygen extraction in elite athletes.

While current research offers evidence-based strength training approaches to enhance endurance running performance, numerous popular strength training models have not been empirically tested in this context. PURPOSE: Compare the effects of periodized lower body strength training versus high intensity circuit strength training on running performance and related variables in experienced runners. METHODS: Participants (N = 19) were randomized to 8 weeks of periodized lower body strength training (PLB), n = 9, or high intensity circuit training (CT), n = 10. All participants strength trained 2 d·wk-1 and followed their typical running schedule. PLB sessions included 2 sets of the back squat, standing calf raise, leg press, and dumbbell lunge, with intensity linearly periodized. PLB initially completed sets at 10-repetition maximum (10-RM) and progressed each 2 weeks to 8-RM, 6-RM, and 4-RM. CT sessions included a high intensity, whole body resistance circuit followed by 2-4 heavy (>10-RM) sets of a compound lift, simulating CrossFit©-style programming. 3-km time trial (TT), VO2 max, relative leg press 1-RM, running economy (RE) at 2 standard submaximal velocities (SV1, SV2) between 11 and 14 km·hr-1, RPE at SV1/SV2, and peak/mean power during the Wingate Anaerobic Test were assessed pre and post-intervention. RESULTS: Two-way ANOVA showed a significant main effect of time on RE at 11 km·hr-1 (F = 8.31, p = .02, ηp2 = 0.51) and RPE at SV1 (F = 11.2, p = .004, ηp2 = .40), and a significant group*time interaction on 1-RM (F = 7.66, p = .015, ηp2 = .35) and RPE at SV2 (F = 5.30, p = .037, ηp2 = .28). Similar (p ≤ .02) increases occurred in RE at 11 km·hr-1 (36.4 ± 3.1 to 35.4 ± 2.4 ml·kg-1·min-1) and RPE at SV 1 (12.5 ± 1.3 to 11.4 ± 1.6). Relative 1-RM (2.54 ± 0.41 to 3.40 ± 0.72) and RPE at SV2 (14.1 ± 1.3 to 12.9 ± 1.8) improved in both groups (p ≤ .03). However, PLB showed larger improvements in 1-RM (0.43 ± 0.18 vs. 0.2 ± 1.9, t = 2.75, p = .015) and RPE at SV2 (-1.75 ± 0.9 vs. -0.63 ± 1.1, t = 2.30, p = .037). TT, VO2 max, RE at 12-14 km·hr-1, and power were unchanged (p ≥ .27). CONCLUSIONS: Both modalities enhanced lower body strength, RE at 11 km·hr-1 and submaximal RPE at submaximal, but neither improved TT performance, VO2 max, power, or RE at faster velocities. PLB resulted in greater improvements in lower body strength and RPE at higher submaximal running velocity.

Running velocity reached at maximal oxygen uptake (vVO2(max)) can be a useful measure to prescribe training intensity for aerobic conditioning. Obtaining it in the laboratory is often not practical, and average velocities from time trials are an attractive alternative. To date, the efficacies of such practices for team sport players are unknown. This study aimed to assess the relationship between vVO2(max) obtained in the laboratory against two time-trial estimates (1500 m and 3200 m). During the early preseason, elite Australian Rules football players (n = 23, 22.7 +/- 3.4 y, 187.7 +/- 8.2 cm, 75.5 +/- 9.2 kg) participated in a laboratory test on a motorized treadmill and two outdoor time trials. Based on average velocity the 1500-m time-trial performance (5.01 +/- 0.23 m x s(-1)) overestimated (0.36 m x s(-1), d = 1.75), whereas the 3200-m time trial (4.47 +/- 0.23 m x s(-1)) underestimated (0.17 m x s(-1), d = 0.83) the laboratory vVO2(max) (4.64 +/- 0.18 m x s(-1)). Despite these differences, both 1500-m and 3200-m time-trial performances correlated with the laboratory measure (r = -0.791; r = -0.793 respectively). Both subsequent linear regressions were of good fit and predicted the laboratory measure within +/- 0.12 m x s(-1). Estimates of vVO2(max) should not be used interchangeably, nor should they replace the laboratory measure. When laboratory testing is not accessible for team sports players, prescription of training intensity may be more accurately estimated from linear regression based on either 1500-m or 3200-m time-trial performance than from the corresponding average velocity.

Background: High-intensity interval training (HIIT) is an effective and efficient method for training Paralympic athletes with cerebral palsy, particularly in intermittent sports and those requiring aerobic and anaerobic capacity, speed, and strength to delay fatigue onset and optimize athletic performance. Objectives: This study aimed to analyze the effects of four weeks of HIIT on the estimated VO2max, anaerobic power, and athletic performance in cyclists with cerebral palsy. Materials and Methods: This quasi-experimental study included three male athletes (Athletes A, B, and C) with cerebral palsy from the Paracycling Departmental Commission of Cauca, Colombia. The estimated VO2max was assessed using an incremental test on a cycling ergometer. Anaerobic power was measured using the 30 s long Wingate Anaerobic Test (WAnT_30 s. Specific performance was evaluated with an individual time trial of 14 km for class T1 and 20 km for class T2. HIIT training was performed on a cycling ergometer over four weeks (two sessions per week). The training intensity was based on watts (W) measured in the incremental test for long HIIT sessions and in the WAnT_30 s test for short HIIT sessions. The training load was monitored through heart rate (HR) responses and the subjective perceived exertion (RPE) at the end of the training. Results: After the HIIT intervention, percentage changes in the estimated VO2max were observed in Athlete A (+7%) and Athlete C (+9.4%). In the WAnT_30 s, there were increases in the maximal and mean power in Athlete A (>31%, 282.3 vs. 370.4 W), Athlete B (>15%, 272.5 vs. 312.6 W), and Athlete C (>9%, 473.7 vs. 516.2 W). Individual time trial performance improved, with reduced completion times for Athlete A (−6.7%, 2492 vs. 2325 s), Athlete B (−3.7%, 2486 vs. 2390 s), and Athlete C (−3.7%, 2775 vs. 2674 s). Conclusions: This study found that eight sessions of high-intensity interval training (HIIT) over a four-week period had a positive effect on the estimated VO2max in Athletes A and C. Moreover, all three paracyclists demonstrated improvements in their maximal and average power output during the 30 s Wingate Anaerobic Test (WAnT_30 s), as well as enhanced performance in the time trial test.

Background: Previous research has individually investigated how different types of training affect the physical, physiological, and training characteristics of distance runners. However, there is a lack of studies that collectively examine the effects of interval and power training programs on these factors in trained distance runners. Objectives: This study aims to provide a more comprehensive and up-to-date understanding of how combined training approaches may impact the physical, physiological, and training characteristics of competitive distance runners. Methods: A census sampling approach was used, with all 108 athletes (100%) participating in the study. Participants were divided into three parallel training groups: The interval training group (ITG), the power training group (PTG), and the control training group (CTG). Each group contained 36 participants, and a randomized block design was implemented within each group, with 12 athletes in each block. The intervention lasted for 32 weeks, with three training sessions per week, on non-consecutive days, lasting 45 - 60 minutes per session. The intensity of the training sessions was maintained between 50 - 70% of the participants' exercise capacity. The measured physical characteristics included demographic and anthropometric variables such as age, sex, height, weight, Body Mass Index (BMI), fat and fat-free mass, and various circumferences. The physiological characteristics assessed included resting heart rate, exercise heart rate, maximum oxygen consumption, measures of leg strength (LS) and power, endurance performance metrics such as time trials (TTs), and aerobic thresholds. The training characteristics assessed included living and training altitude, training habits, training experience, training volume, training sessions, recovery practices, and nutritional intake. Statistical significance was determined with a P-value of &lt; 0.05, and effect size was calculated (η² &gt; 0.14). Results: Interval and power training led to improvements in several physical characteristics, including chronological age (P = 0.02), Body Mass Index (P = 0.03), fat-free mass (P = 0.000), and maximum thigh circumference (P = 0.000). However, no significant changes were observed in certain physical characteristics such as sex, field, and weight (P = 1.000). Interval and power training also resulted in significant improvements in various physiological characteristics, including 400 m sprint performance (P = 0.000), 1.5 km Kosmin test (P = 0.000), 3 km maximum speed TT (P = 0.000), LS (P = 0.000), Sprint Bounding Index (SBI) (P = 0.000), and maximum exercise heart rate (P = 0.000). In contrast, the post-test (POT) results for the ITG and PTG groups, when compared to the CTG, showed no significant differences in certain areas of physiological characteristics, including Balke V̇O2Max (P = 0.000), leg press (P = 0.000), and squat (p = 0.000). Regarding the third subgroup analysis of training characteristics, all POT results showed a decrease, except for the habit of sleeping (P = 0.04). In general, the POT results of the CTG demonstrated less change in all subgroup analyses of performance indices compared to the ITG and PTG. Conclusions: Our key findings emphasize the importance of combined interval and power training in improving V̇O2Max, overall strength endurance, speed endurance, running economy (RE), and muscle adaptation compared to the control group. These factors are vital for enhancing physical and physiological characteristics. Future research should explore additional factors, such as nutrition and psychological needs, which may influence athletic performance.

BackgroundThis study explored the deloading practices of competitive strength and physique athletes. A 55-item anonymised web-based survey was distributed to a convenience-based, cross-sectional sample of competitive strength and physique athletes (n = 246; males = 181 [73.6%], females = 65 [26.4%]; age = 29.5 ± 8.6 years) who had 8.2 ± 6.2 years of resistance training and 3.8 ± 3.1 years of competition experience.ResultsAll athletes deloaded within training with energy and fatigue management being the main reasons to do so. The typical duration of a deload was 6.4 ± 1.7 days, integrated into the training programme every 5.6 ± 2.3 weeks. Deloading was undertaken using a proactive, pre-planned strategy (or in combination with an autoregulated approach) and undertaken when performance stalled or during periods of increased muscle soreness or joint aches. Athletes reported that training volume would decrease (through a reduction in both repetitions per set and sets per week), but training frequency would remain unchanged during deloads. Additionally, athletes reported that training intensity (load lifted) would decrease, and effort would be reduced (facilitated through an increase in repetitions in reserve). Athletes would generally maintain the same exercise selection during deloading. For athletes that supplemented deloading with additional recovery modalities (n = 118; 48%), the most reported strategies were massage, static stretching and foam rolling.ConclusionResults from this research might assist strength and physique athletes and coaches to plan their deloading. Future research should empirically investigate the findings from this study to further evaluate the potential utility of deloading in strength and physique sports.

Soccer performance is determined by a number of physiological adaptations that can be altered by high intensity training. However, the effectiveness of using an uphill sprint based protocol has not been demonstrated for soccer players. We sought to determine the effectiveness of an in-season uphill sprint training (UST) programme on soccer related physiological outcomes. Fourteen male soccer players (age: 22±8 years, height: 1.81±8 m, body mass: 76±12 kg) underwent testing (5-10-5 agility drill, Yo-Yo Intermittent Recovery Test Level 1, leg and back dynamometry and 3 km time trial) at baseline and after 6 weeks of UST or normal activity. Participants were allocated to a control (N.=7) or UST (N.=7) group. The UST group took part in twice weekly training consisting of 10 x 10 sec sprints with 60s recovery on a 7% gradient for six weeks. The control group maintained normal activity patterns. 3 km time trial, strength, agility and Yo-Yo performance were all significantly improved pre to post following 6 weeks of UST (agility 3%, d=1.3; strength 10%, d=-3.2; VO2max 3%, d=-1.4; 3-km TT 4%, d=1.3). In the control group 3 km time trial, strength, agility and Yo-Yo performance remained unchanged after 6 weeks (agility 0.1%, d=-0.2; strength 2%, d=0.0; VO2max -0.1%, d=0.0; 3-km TT 1.3%, d=0.3). Therefore in-season short duration UST is an effective way to improve soccer fitness in a time efficient manner.

This study aimed to systematically review training methods prescribed to develop lower-body power, determine their effectiveness for the development of lower-body mechanical power and their implementation in an annual training cycle amongst team-sport athletes. The absolute and relative outcome values of concentric mean power, peak power and mean propulsive power were extracted from 19 studies. Outcomes were assessed using baseline to post intervention percent change, effect sizes, and the level of evidence concerning the method's effectiveness. A thorough analysis of the literature indicated that, based on the high level of evidence, traditional (e.g., strength training alone) and combination training (e.g., complex and contrast) methods should be considered. Further, optimal load and velocity-based training can be implemented if coaches have access to the appropriate equipment to monitor movement velocity and mechanical power in every session. This is of particular importance in periods of the season where high volumes of technical-tactical training and congested fixture periods are present. Also, flywheel, eccentric overload and weightlifting methods have been shown to be effective although the level of evidence is low. Future research should expand on current training practices whilst adequately reporting actual training loads from sport-specific training and games alongside strength-power training protocols.

Collegiate rowing performance is often assessed by a cardiopulmonary exercise test (CPET). Rowers’ on-water performance involves non-linear dynamic interactions and synergetic reconfigurations of the cardiorespiratory system. Cardiorespiratory coordination (CRC) method measures the co-variation among cardiorespiratory variables. Novice (n = 9) vs. Intermediate (n = 9) rowers’ CRC (H0: Novice CRC = Intermediate CRC; HA: Novice CRC < Intermediate CRC) was evaluated through principal components analysis (PCA). A female NCAA Division II team (N = 18) grouped based on their off-water performance on 6000 m time trial. Rowers completed a customized CPET to exhaustion and a variety of cardiorespiratory values were recorded. The number of principal components (PCs) and respective PC eigenvalues per group were computed on SPSS vs28. Intermediate (77%) and Novice (33%) groups showed one PC1. Novice group formed an added PC2 due to the shift of expired fraction of oxygen or, alternatively, heart rate/ventilation, from the PC1 cluster of examined variables. Intermediate rowers presented a higher degree of CRC, possible due to their increased ability to utilize the bicarbonate buffering system during the CPET. CRC may be an alternative measure to assess aerobic fitness providing insights to the complex cardiorespiratory interactions involved in rowing during a CPET.

Women have a disadvantage for performance in long-distance running compared with men. To elaborate on inherent characteristics, 12 subelite women were matched with 12 men for training volume (M-Tm) (56.6 ± 18 vs. 55.7 ± 17 km/wk). The women were also matched to other men for a 10 km staged outdoor time trial (M-Pm) (42:36 min:s) to determine which factors could explain equal running performance. Anthropometry and treadmill tests were done. Fiber type (% Type I and Type IIA) and citrate synthase activities were analyzed in muscle biopsy samples. Consistent sex differences for both comparisons included height, weight, % body fat (P < 0.01), and hematocrit (P < 0.05). Women had lower V̇o2max and peak treadmill speed (PTS) compared with both M-Tm and M-Pm (P < 0.01). Training matched pairs had no sex difference in % PTS at race pace but compared with M-Pm women ran at a higher % PTS (P < 0.05) and %HRmax (P < 0.01) at race pace. On average, the women trained 22.9 km/wk more than M-Pm (+67.5%, P < 0.01). This training was not associated with higher V̇o2max or better running economy. Muscle morphology and oxidative capacity did not differ between groups. Percentage body fat remained significantly higher in women. In conclusion, women matched to men for training volume had slower 10 km performance (-10.5% P < 0.05). Higher training volume, more high-intensity sessions/wk, and time spent training in the 95%-100% HRmax zone may explain the higher % PTS and %HRmax at race pace in women compared with performance-matched men.NEW & NOTEWORTHY When subelite women 10 km runners were matched with male counterparts for 10 km race performance, inherent differences in % body fat, V̇o2max, Hct, and peak treadmill speed were counteracted by significantly higher training volume, more time training at higher %HRmax and consequently, higher %HRmax and %PTS at race pace. Citrate synthase activity and muscle fiber types did not differ. When women and men matched for training, 10 km performance of men was 10.5% faster.

Lateral lymph node metastasis (LLNM) is associated with poor prognosis in patients with papillary thyroid cancer (PTC). The purpose of this study was to determine the risk factors for LLNM and establish prediction models that could individually assessed the risk of LLNM. A total of 619 PTC patients were retrospectively analyzed in our study. Univariate and multivariate analysis were performed for male and female patients, respectively, to assess relationships between clinicopathological features and LLNM. By integrating independent predictors selected by binary logistic regression modeling, preoperative and postoperative nomograms were developed to estimate the risk of LLNM. LLNM was detected in 80 of 216 male patients. Of 403 female patients, 114 had LLNM. The preoperative nomogram of male patients included three clinical variables: the number of foci, tuner size, and echogenic foci. In addition to the above three variables, the postoperative nomogram of male patients included extrathyroidal extension (ETE) detected in surgery, central lymph node metastasis (CLNM) and high-volume CLNM. The preoperative nomogram of female patients included the following variables: age, chronic lymphocytic thyroiditis (CLT), BRAF V600E, the number of foci, tumor size and echogenic foci. Variables such as CLT, BRAF V600E, the number of foci, tumor size, ETE detected in surgery, CLNM, high-volume CLNM and central lymph node ratio were included in the postoperative nomogram. Above Nomograms show good discrimination. Considering the difference in the incidence rate of LLNM between men and women, a separate prediction system should be established for patients of different genders. These nomograms are helpful in promoting the risk stratification of PTC treatment decision-making and postoperative management.