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Purpose: Antarctic expeditions are exceptional physiological challenges. Sleep plays a critical role in athletic performance, recovery, and wellness, with sleep disturbances having a negative impact on health and performance. Methods: The authors investigated sleep, fatigue, and recovery profiles of the longest solo unsupported one-way polar ski journey across Antarctica. A 33-year-old woman covered 1484.53 km from Hercules Inlet to the South Pole, finishing at the Ross Ice Shelf, in 70 days and 16 hours. Questionnaires on sleep (Pittsburgh Insomnia Rating Scale and Karolinska Sleepiness Scale), fatigue (Subjective Assessment of Fatigue), recovery (Total Quality Recovery), and wellness were completed at different time points (before, during, and after the expedition). Results: Average daily sleep time was between 4 and 5 hours, increasing to 7 hours for the final part of the expedition. Satisfaction of sleep and lack of energy deteriorated as the expedition progressed, alongside signs of clinical insomnia. Fatigue and muscle soreness increased with increasing milage, with extreme levels and very poor recovery toward the end of the expedition. Despite this, the adventurer continued to perform on extremely high levels. Postexpedition scores returned to baseline, demonstrating the incredible adaptation and ability to recovery. The postexpedition interview showed that prior experience of an Antarctic expedition may have prepared the athlete and made her more resilient for this challenge. Conclusions: The data provide unique insights into Antarctic expeditions and may help us understand the limits of human performance when planning future expeditions of this nature. Female athletes are capable of extreme challenges, breaking established performance boundaries.

Purpose: The purpose of this study was to investigate the effects of acute ischemic preconditioning (IPC) on tennis skill and physical exercise performance, as well as to explore whether 7-day repeated IPC (RIPC) accelerated fatigue recovery after a simulated tennis match. Methods: Twenty-nine male tennis-specific current students were randomly allocated into 1 of 2 groups: SHAM (n = 14, 3 × 5 min at 20 mm Hg) and IPC (n = 15, 3 × 5 min at 220 mm Hg). Participants in both groups engaged in acute IPC and RIPC interventions. After the first acute IPC intervention, assessments were conducted to evaluate tennis-specific skills and overall physical exercise capacity. Following completion of chronic RIPC interventions, all participants competed in a simulated tennis match specifically designed to induce fatigue. To evaluate recovery from this induced fatigue, physical exercise capacity tests were conducted at 24 and 48 hours postmatch, allowing for an assessment of the participants’ recovery capabilities over time. Results: After the first acute intervention, notable differences were observed between the IPC and SHAM groups in their performance on the repeated-sprint ability test. Specifically, the total times recorded were significantly shorter in the IPC group compared with the SHAM group (IPC: 109.05 [2.70] vs SHAM: 114.57 [7.45] s, P = .012), and this trend was also reflected in their best times (IPC: 4.20 [0.18] s vs SHAM: 4.39 [0.30] s, P = .042), indicating an immediate benefit of the IPC intervention on sprint performance. After a 7-day RIPC intervention, significant changes were noted in the SHAM group’s performance metrics postmatch. There was an increase (P < .001) in fatigue index from 22% (8%) to 30% (9%) during repeated-sprint ability test and a decrease in serve speed from 120.2 (17.5) to 106.7 (13.0) km/h (P = .002) and knee peek torque from 196.0 (49.0) to 162.7 (39) N (extension, 60°/s, P < .001) in the SHAM group 24 hours postmatch, relative to the IPC group. Moreover, compared with the SHAM group, the IPC group showed a lower rate of perceived exertion during the match (P < .001) and a decrease in visual analog scale score (P = .026) 24 hours postmatch, suggesting enhanced recovery and reduced perception of pain relative to the SHAM group. Conclusion: IPC could serve as a strategy to generate an ergogenic effect and recovery during training and competition.

Purpose: To gather information on practices and perceptions of high-performance experts regarding their athletes’ muscle fiber-type composition (MFTC) and its estimation. Methods: A questionnaire on the noninvasive versus invasive estimation of MFTC was completed by 446 experts including coaches and sport-science/sports-medicine staff. Moreover, the perceived importance of MFTC for training and performance optimization was assessed. Differences between sport types (individual and team sports) were analyzed using chi-square tests. Results: Forty percent of the experts implemented MFTC assessment in pursuit of performance optimization, while 50% did not know their athletes’ MFTC but expressed a desire to implement it if they would be able to assess MFTC. Ten percent did not perceive value in MFTC assessment. Only 18% of experts believed that their athletes would undergo a muscle biopsy, leading to the adoption of alternative noninvasive techniques. Experts primarily relied on their experience to estimate MFTC (65%), with experts working in individual sports using their experience more frequently than those working in team sports (68% vs 51%; P = .009). Jump tests emerged as the second-most commonly employed method for estimating MFTC (56%). When only considering experts who are currently using MFTC, 87% use MFTC to individualize training volume and 84% to individualize training intensity. Conclusions: Experts value MFTC assessment primarily to individualize training but mainly rely on noninvasive methods to estimate MFTC. Some of these methods lack scientific validity, suggesting a continuing need for education and further research in this area.

Purpose: Jump and linear sprint performances both correlate with pro-agility performance. However, correlation does not imply causation, and potential confounders may affect the correlation. Therefore, this study aimed to determine the relationship between change-of-direction (COD) performance and COD deficits (COD-D) in linear-sprint and countermovement-jump (CMJ) -related performance using multiple stepwise linear-regression models. Methods: The study included 42 female national-level intercollegiate athletes. The 10- and 20-m linear-sprint and pro-agility times, COD-D, CMJ height, and phase-specific force production and rate of force development during eccentric unloading, eccentric braking, and the concentric phases of CMJ were measured. Stepwise linear-regression analyses were used to predict the factors related to COD and COD-D. Results: CMJ height was the sole predictor in the 10-m pro-agility model (adjusted R ² = .234, P = .001). Modified Reactive Strength Index (standardized coefficient, −.710) and the lowest center-of-mass depth during the CMJ (standardized coefficient, .323) were predictors in the 20-m pro-agility model (adjusted R ² = .330, P < .001). For the 10- and 20-m COD-D models, the rate of force development at 30 and 60 milliseconds, respectively, during the concentric phase was the only predictor of performance (adjusted R ² = .183, P = .003 and .237, P = .001, respectively). Conclusions: These results suggest that athletes should concentrate on improving their CMJ height, increasing their ability to lower their center of mass more deeply, and increasing their instantaneous force-production abilities immediately after the eccentric braking phase of CMJ to improve their COD performance.

Purpose: This study compared the physiological profiles and energy-system contributions of trained football players engaged in regular-passing and third-man-passing small-sided games (SSGs) that included 4 versus 4 and a goalkeeper. Methods: Ten male trained football players participated in this crossover study. All participants were randomly assigned to either regular-passing SSG or third-man-passing SSG (4 vs 4 with a goalkeeper, 35-m × 17-m pitch size, and 6-min match duration). During these SSGs, physiological parameters including peak and mean heart rate, oxygen uptake ( $\dot{\mathrm{V}}{\mathrm{O}}_2\text{peak}$ and $\dot{\mathrm{V}}{\mathrm{O}}_2\text{mean}$ ), metabolic equivalents in $\dot{\mathrm{V}}{\mathrm{O}}_2\text{peak}$ and $\dot{\mathrm{V}}{\mathrm{O}}_2\text{mean}$ , and blood lactate concentrations (peak La⁻ and delta La⁻ [Δ La⁻]), were measured. Energy contributions (oxidative [W _Oxi], glycolytic [W _Gly], and phosphagen [W _PCr] systems) and Global Positioning System (GPS) variables (total distance, total acceleration counts, mean speed, and maximum speed) were also analyzed. Results: No significant differences in physiological parameters and GPS variables were found between regular- and third-man-passing SSGs. W _Oxi in kilojoules and percentages was significantly higher during both SSGs than W _PCr and W _Gly (P < .0001, respectively). W _PCr and W _PCr + W _Gly values during third-man-passing SSGs were significantly higher than those during regular-passing SSGs (P < .05). Additionally, low to moderate positive correlations were observed between W _Oxi, W _Gly in kilojoules, $\dot{\mathrm{V}}{\mathrm{O}}_2\text{peak}$ , $\dot{\mathrm{V}}{\mathrm{O}}_2\text{mean}$ , peak La⁻, Δ La⁻, total acceleration counts, and mean speed (r = .39–.64). Conclusions: Third-man-passing SSGs may be useful for increasing anaerobic capacity. More third-man-passing SSG sessions in preparation for football games may support high metabolic power and repeated powerful anaerobic performances in trained football players.

Purpose: To characterize the time structure of K1 kickboxing matches of Glory World Series (Glory) and to determine potential differences between winners and losers. Methods: Seventeen matches of Glory 2019 (17 first rounds, 13 second rounds, and 8 third rounds) were video-analyzed to quantify (1) the time expended in high- and low-intensity activity and pauses, (2) the number and pattern of attacks, and (3) the number of effective attacks. Fighters were professional male athletes (age 27.9 [2.7] y) of the middle-weight category (85 kg). The number and the pattern of attacks and the number of effective attacks were compared between winners and losers. Results: The mean times expended in high- and low-intensity activity and pauses were 234.6 (133.9) seconds, 97.4 (60.1) seconds, and 36.0 (19.9) seconds, respectively, resulting in an effort-to-pause ratio of ∼1.8:1. Compared with losers, winners presented (1) a greater number of attacks in the second round (P = .004) and entire match (P = .009), (2) a greater number of attacks containing 3 attacks in sequence in the second round (P = .001) and attacks containing >3 attacks in the third round (P = .049), and (3) a greater number of effective attacks in the second round (P = .011) and entire match (P = .008). Conclusions: The findings of the present study indicate that K1 kickboxing in Glory matches presents a ∼1.8:1 effort-to-pause ratio and that winners perform more attacks, effective attacks, and attacks in sequence. These data provide useful insights to improve the training specificity of kickboxing athletes.

Purpose: This study aimed to compare running economy across habituated and nonhabituated advanced footwear technology (AFT) in trained long-distance runners. Methods: A total of 16 participants completed up to six 5-minute trials in 1 to 3 pairs of their own habituated shoes and 3 different and standardized AFTs at individual marathon pace. We measured oxygen uptake and carbon dioxide production and expressed running economy as oxygen uptake (in milliliters oxygen per kilogram per minute), oxygen cost of transport (oxygen per kilogram per minute), energetic cost (in watts per kilogram), and energetic cost of transport (in joules per kilogram per kilometer). We used linear mixed-effect models to evaluate differences. Relative shoe weight and shoe mileage (distance worn during running) were covariates. Results: Forty-eight standardized and 29 individual AFT conditions were measured (mileage 117.0 [128.8] km, range 0–522 km; 25 habituated 135.7 [129.2] km, range 20–522 km; 4 nonhabituated 0 [0] km, range 0–0 km). Rating of perceived exertion, blood [La], and respiratory exchange ratio ranged from 9 to 15, 1.11 to 4.54 mmol/L, and 0.76 to 1.01. There was no effect for habituation on energetic cost of transport (t _habituation = −.232, P = .409, b = −0.006; 95% CI, −0.058 to 0.046) or other running economy metrics. Neither shoe weight nor shoe mileage had an effect. Conclusions: Our results suggest that habituation to AFTs does not result in greater benefits in the use of AFTs. This means that implementation in training may not be needed, even if we cannot rule out any other possible benefits of habituation at this stage, such as adaptation of the musculoskeletal system.