Browse

Purpose: Prediction of athlete wellness is difficult—or, many sports-medicine practitioners and scientists would argue, impossible. Instead, one settles for correlational relationships of variables gathered at fixed moments in time. The issue may be an inherent mismatch between usual methods of data collection and analysis and the complex nature of the variables governing athlete wellness. Variables such as external load, stress, muscle soreness, and sleep quality may affect each other and wellness in a dynamic, nonlinear, way over time. In such an environment, traditional data-collection methods and statistics will fail to capture causal effects. If we are to move this area of sport science forward, a different approach is required. Methods: We analyzed data from 2 different soccer teams that showed no significance between player load and wellness or among individual measures of wellness. Our analysis used methods of attractor reconstruction to examine possible causal relationships between GPS/accelerometer-measured external training load and wellness variables. Results: Our analysis showed that player self-rated stress, a component of wellness, seems a fundamental driving variable. The influence of stress is so great that stress can predict other components of athlete wellness, and, in turn, self-rated stress can be predicted by observing a player’s load data. Conclusion: We demonstrate the ability of nonlinear methods to identify interactions between and among variables to predict future athlete stress. These relationships are indicative of the causal relationships playing out in athlete wellness over the course of a soccer season.

Purpose: To describe the self-reported menstrual health, symptomatology, and perceived effects of the menstrual cycle on athletic performance for national and international Australian football (soccer) players. Methods: Players from national and domestic teams were invited to complete an online questionnaire regarding menstrual health, use of hormonal contraceptives (HCs), negative symptomatology, and perceived disruption of the menstrual cycle to performance. Descriptive statistics and binomial regressions with odds ratios (OR) were used to report the relationship of menstrual-related variables with perceived performance disruption. Results: A total of 199 players (20.9 [5.1] y) completed the questionnaire, with 18% of players reporting using HCs. One primary amenorrhea case was detected, and 26% of players reported menarche at age ≥15 years. For non-HC users, the prevalence of secondary amenorrhea was 2%, oligomenorrhea was 19%, and heavy menstrual bleeding was 11%. Ninety-seven percent of players reported experiencing physical or affective menstrual symptoms (5 [1.3] per player), and 40% of all players reported that menstrual symptoms impacted their ability to work, study, train, or compete. Furthermore, 40% of players perceived their training or performance to be disrupted by the menstrual cycle. Increasing number of menstrual symptoms (OR = 1.43; 95% CI, 1.28–1.62; P < .001), heavy menstrual bleeding (OR = 12.73; 95% CI, 3.4–82.8; P < .001), and pelvic pain (OR = 3.40; 95% CI, 1.7–7.2; P < .001) increased the likelihood of perceiving the menstrual cycle to disrupt performance. Conclusion: Heavy menstrual bleeding and HC use were low among this cohort of national and international footballers, whereas amenorrhea and oligomenorrhoea were comparable with other football populations. Nearly all players reported menstrual symptoms, and increased symptomatology was associated with greater perceived effects on performance.

Purpose: Travel fatigue impacts cognitive and physiologic systems, but its association with elite soccer match performance is unclear. In this retrospective observational study, we aimed to explore the association between travel and match outcomes in elite North American soccer. Methods: Travel data and match outcomes (team points or goals scored and conceded) and physical performance outcomes from 26 elite professional soccer teams and their players were analyzed (148 matches [team-based data] and 1252 player matches from 297 players; age 22.7 [4.5] y). Player- and match-level correlations between performance measures and both acute and cumulated travel metrics were analyzed. Results: Cumulative travel metrics were positively associated with team (travel distance [r = .20; 95% CI, .03–.25], travel time [r = .20; .06–.37], and time away [r = .20; .06–.37]) and individual player (travel distance, [r = .14; .08–.19], travel time [r = .17–.23], and time away [r = .13; .07–.18]) high-intensity running. Cumulative time away was negatively associated with team points (r = −.14; −.28 to −.001) and positively associated with goals conceded (r = .14; .01–.27); no clear association between acute travel metrics and match outcomes or physical performance was observed. Conclusions: As travel cumulated, away teams and their players ran more but for less reward (team points), although the magnitude of these associations was small. These data are exploratory and do not imply a causal relationship; however, further research should consider cumulation of travel.

Purpose: The study validated variables corresponding to lactate threshold (LT) in swimming. Speed (sLT), blood lactate concentration (BL_LT), oxygen uptake (VO_2LT), and heart rate (HR_LT) corresponding to LT were calculated by 2 different incremental protocols and validated in comparison with maximal lactate steady state (MLSS). Methods: Ten competitive swimmers performed a 7 × 200-m front-crawl incremental “step test” with 2 protocols: (1) with 30-second rests between repetitions (short-rest incremental protocols) and (2) on a 5-minute cycle (swim + rest time, long-rest incremental protocols). Five methods were used for the assessment of sLT and corresponding BL_LT, VO_2LT, and HR_LT: intersection of 2 lines, D_max, modified D_max, visual inspection, and intersection of combined linear and exponential regression lines. Subsequently, swimmers performed two to three 30-minute continuous efforts to identify speed (sMLSS) and physiological parameters corresponding to MLSS. Results: Both protocols resulted in similar sLT and corresponding physiological variables (P > .05). Bland–Altman plots showed agreement between protocols (sLT, bias: −0.017 [0.002] m·s⁻¹; BL_LT, bias: 0.0 [0.5] mmol·L⁻¹; VO_2LT, bias: −0.1 [2.2] mL·kg⁻¹·min⁻¹; HR_LT. bias: −2 [8] beats·min⁻¹). However, sLT calculated by modified D_max using short rest was higher compared with speed at MLSS (1.346 [0.076] vs 1.300 [0.101] m·s⁻¹; P < .05). Conclusions: Calculated sLT, BL_LT, VO_2LT, and HR_LT using all other methods in short-rest and long-rest incremental protocols were no different compared with MLSS (P > .05). Both 7 × 200-m protocols are valid for determination of sLT and corresponding physiological parameters, but the modified D_max method may overestimate sLT.

Purpose: To assess the effect of 2 work-matched efforts of different intensities on subsequent performance in well-trained cyclists. Methods: The present study followed a randomized controlled crossover design. Twelve competitive junior cyclists volunteered to participate (age, 17 [1] y; maximum oxygen uptake, 71.0 [4.7] mL·kg⁻¹·min⁻¹). The power–duration relationship was assessed through 2-minute, 5-minute, and 12-minute field tests under fresh conditions (control). On subsequent days and following a randomized order, participants repeated the aforementioned tests after 2 training sessions matched for mechanical work (∼15 kJ/kg) of different intensities (ie, a moderate-intensity continuous-training [60%–70% of critical power; CP] session or a session including high-intensity intervals [3-min repetition bouts at 110%–120% of the CP interspersed by 3-min rest periods]). Results: A significantly lower power output was found in the 2-minute test after the high-intensity training session compared not only with the control condition (−8%, P < .001) but also with the moderate-intensity continuous-training session (−7%, P = .003), with no significant differences between the latter conditions. No significant differences between conditions were found for the remaining tests. As a consequence, the high-intensity training session resulted in significantly lower W′ values compared to both the control condition (−27%, P = .001) and the moderate-intensity continuous-training session (−26%, P = .012), with no differences between the 2 latter conditions and with no differences for CP. Conclusion: A session including high-intensity intermittent efforts induces a greater fatigue, particularly in short-duration efforts and W′, than a work-matched continuous-training session of moderate intensity.

Purpose: To describe and compare the race characteristics, demands, and durability profile of a male and a female Grand Tour winner. Methods: Overall and stage-type-specific (ie, time trials, flat, semimountainous, and mountain) demands and race characteristics during 2 Grand Tours were determined and compared between the female and male cyclists. In addition, relative power output distribution and pacing, percentage of functional threshold power (FTP), and changes in maximal mean power outputs (MMPs) with increasing levels of kilojoules burned were determined. Results: Although many differences were found between course and absolute racing demands between the male (FTP: 413 W; critical power: 417 W) and female (FTP: 297 W; critical power: 297 W) cyclists, similar power distributions and pacing strategies were found if data were expressed relatively. However, the female cyclist rode a higher percentage of her FTP during the first 2 quarters of flat stages (14.7%–15.1%) and the last quarter of mountain stages (9.8%) than the male cyclist. Decrements in MMPs were only observed after burning 30 kJ·kg⁻¹ in the female and 45 kJ·kg⁻¹ in the male Grand Tour winner. Conclusions: Both the male and female Grand Tour winners produced very high 20- to 60-minute MMPs, whereas decrements in MMPs were only observed after having burned 75% (female) and 80% (male) of total kilojoules burned during a stage. These are the latest and lowest in MMPs reported in the scientific literature and highlight the importance of durability in combination with excellent climbing and time-trial skills, which are needed to be able to win a Grand Tour.

Purpose: This study aimed to quantify training and match-day (MD) load during 3-, 4-, and 5-day microcycles in professional adult football, as well as to analyze the effect of the microcycle length on training load produced the day after the match (MD + 1) and the day before the match (MD − 1). Methods: The study involved 20 male professional football players whose external and internal loads were monitored for a whole season. The training exposure, total distance covered, high-speed-running distance, sprint distance (SD), individual SD above 80% of the individual maximum velocity (D > 80%), and the number of accelerations and decelerations were quantified, as well as rating of perceived exertion and session rating of perceived exertion training load. Results: Microcycle length affected most of the variables of interest: high-speed-running distance (F = 9.04, P < .01), SD (F = 13.90, P < .01), D > 80% (F = 20.25, P < .01), accelerations (F = 10.12, P < .01), and decelerations (F = 6.01, P < .01). There was an interaction effect between the training day and microcycle type for SD (F = 5.46, P < .01), D > 80% (F = 4.51, P < .01), accelerations (F = 2.24, P = .06), and decelerations (F = 3.91, P < .01). Conclusions: Coaches seem to be influenced by shorter microcycles in their training proposal, preferring sessions with a reduced muscle impact during shorter microcycles. Independent of the length of the congested fixture microcycle, the daily load seems to decrease when MD approaches.

Purpose: We examined changes in stride temporal parameters and spring-mass model characteristics during repeated sprints following a 3-week period of “live high–train low and high” (LHTLH) altitude training in team-sport players. Methods: While residing under normobaric hypoxia (≥14 h/d; inspired oxygen fraction [FiO₂] 14.5%–14.2%) for 14 days, elite field hockey players performed, in addition to their regular field hockey practice in normoxia, 6 sessions (4 × 5 × 5-s maximal sprints; 25-s passive recovery; 5-min rest) under either normobaric hypoxia (LHTLH; FiO₂ ∼14.5%, n = 11) or normoxia (live high–train low; FiO₂ 20.9%, n = 12). A control group (live low–train low; FiO₂ ∼20.9%, n = 9) residing in normoxia without additional repeated-sprint training was included. Before (Pre) and a few days (Post-1) and 3 weeks (Post-2) after the intervention, stride mechanics were assessed during an overground repeated-sprint test (8 × 20 m, 20-s recovery). Two-way repeated-measures analysis of variance (time [Pre, Post-1, and Post-2] × condition [LHTLH, live high–train low, and live low–train low]) were conducted. Results: Peak sprinting speed increased in LHTLH from Pre to Post-1 (+2.2% [2.0%]; P = .002) and Post-2 (+2.0% [2.4%]; P = .025), with no significant changes in live high–train low and live low–train low. There was no main effect of time (all P ≥ .062), condition (all P ≥ .771), or a significant time × condition interaction (all P ≥ .230) for any stride temporal variable (contact time, flight time, stride frequency, and stride length) or spring-mass model characteristics (vertical and leg stiffness). Conclusions: Peak sprinting speed improved in elite field hockey players following LHTLH altitude training, while stride mechanical adjustments to repeated overground sprints remained unchanged for at least 3 weeks postintervention.