The increasing participation of female contestants starting from 2

Purpose: To assess the effects of cycling cadence, exercise intensity, and preload on blood lactate concentration (BLC), carbohydrate oxidation (CHO), and gross efficiency (GE) during 60-minute cycling sessions. Methods: Eleven male triathletes (age: 28.2 [9.2] y, height: 179.9 [6.0] cm, body mass: 73.1 [4.8] kg, performance level 3) completed 2 incremental load tests to determine peak power (P-peak) and 4 prolonged cycling tests including 20-minute warm-up at 40% P-peak followed by a 20-minute load phase at 60% and 70% P-peak with a subsequent cooldown at 40% P-peak, all at 60 and 100 rpm, respectively. BLC, oxygen uptake, and carbon dioxide production were measured, and GE, CHO, and the fraction of oxygen uptake utilized for CHO (relCHO) were calculated. Results: The higher cadence lowered GE and increased BLC, oxygen uptake, and CHO (P < .05). RelCHO increased with exercise intensity (P < .05), but no cadence-related increase was confirmed. CHO and relCHO were lower (P < .05) at cooldown than at warm-up without changes in BLC. Conclusions: The lack of evidence for a cadence effect on relCHO supports the suggestion that a higher cadence enables a lower CHO at given metabolic demand and given BLC, particularly at lower exercise intensity. A preload-induced decrease in CHO and relCHO may appear at unchanged availability of pyruvate and lactate as indicated by the BLC. In elite cyclists, where GE remains stable or even improves at higher cadences, the ability to sustain CHO stores by higher cadences could provide a significant performance advantage.

Purpose: To assess (1) whether and how a higher maximal lactate steady state (MLSS) at higher cycling cadence (RPM) comes along with higher absolute and/or fractional carbohydrate combustion (CHOMLSS), respectively, and (2) whether there is an interrelation between potential RPM-dependent MLSS effects and the maximally achievable RPM (RPMMAX). Methods: Twelve healthy males performed incremental load tests to determine peak power, peak oxygen uptake, and 30-minute MLSS tests at 50 and 100 per minute, respectively, to assess RPM-dependent MLSS, corresponding power output, CHOMLSS responses, and 6-second sprints to measure RPMMAX. Results: Peak power, peak carbon dioxide production, and power output at MLSS were lower (P = .000, ω2 = 0.922; P = .044, ω2 > 0.275; and P = .016, ω2 = 0.373) at 100 per minute than at 50 per minute. With 6.0 (1.5) versus 3.8 (1.2) mmol·L−1, MLSS was higher (P = .000, ω2 = 0.771) at 100 per minute than at 50 per minute. No corresponding RPM-dependent differences were found in oxygen uptake at MLSS, carbon dioxide production at MLSS, respiratory exchange ratio at MLSS, CHOMLSS, or fraction of oxygen uptake used for CHO at MLSS, respectively. There was no correlation between the RPM-dependent difference in MLSS and RPMMAX. Conclusions: The present study extends the previous finding of a consistently higher MLSS at higher RPM by indicating (1) that at fully established MLSS conditions, respiration and CHOMLSS management do not differ significantly between 100 per minute and 50 per minute, and (2) that linear correlation models did not identify linear interdependencies between RPM-dependent MLSS conditions and RPMMAX.

Purpose : To develop and evaluate a theory on the frequent observation that cyclists prefer cadences ( RPMs ) higher than those considered most economical at submaximal exercise intensities via modeling and simulation of its mathematical description. Methods : The theory combines the parabolic power-to-velocity ( v ) relationship, where v is defined by crank length, RPM -dependent ankle velocity, and gear ratio, RPM effects on the maximal lactate steady state ( MLSS ), and lactate-dependent carbohydrate oxidation ( CHO ). It was tested against recent experimental results of 12 healthy male recreational cyclists determining the v -dependent peak oxygen uptake ( VO 2PEAKv ), MLSS ( MLSS v ), corresponding power output ( P MLSSv ), oxygen uptake at P MLSSv ( VO 2MLSSv ), and CHO MLSSv -management at 100 versus 50 per minute, respectively. Maximum RPM ( RPM MAX ) attained at minimized pedal torque was measured. RPM -specific maximum sprint power output ( P MAXv ) was estimated at RPMs of 100 and 50, respectively. Results : Modeling identified that MLSS v and P MLSSv related to P MAXv ( IP MLSSv ) promote CHO and that VO 2MLSSv related to VO 2PEAKv inhibits CHO . It shows that cycling at higher RPM reduces IP MLSSv . It suggests that high cycling RPMs minimize differences in the reliance on CHO at MLSS v between athletes with high versus low RPM MAX . Conclusions : The present theory-guided modeling approach is exclusively based on data routinely measured in high-performance testing. It implies a higher performance reserve above IP MLSSv at higher RPM . Cyclists may prefer high cycling RPMs because they appear to minimize differences in the reliance on CHO at MLSS v between athletes with high versus low RPM MAX .

PURPOSE:To investigate differences in athletes' knowledge, beliefs, and training practices during COVID-19 lockdowns with reference to sport classification and sex. This work extends an initial descriptive evaluation focusing on athlete classification.METHODS:Athletes (12,526; 66% male; 142 countries) completed an online survey (May-July 2020) assessing knowledge, beliefs, and practices toward training. Sports were classified as team sports (45%), endurance (20%), power/technical (10%), combat (9%), aquatic (6%), recreational (4%), racquet (3%), precision (2%), parasports (1%), and others (1%). Further analysis by sex was performed.RESULTS:During lockdown, athletes practiced body-weight-based exercises routinely (67% females and 64% males), ranging from 50% (precision) to 78% (parasports). More sport-specific technical skills were performed in combat, parasports, and precision (∼50%) than other sports (∼35%). Most athletes (range: 50% [parasports] to 75% [endurance]) performed cardiorespiratory training (trivial sex differences). Compared to prelockdown, perceived training intensity was reduced by 29% to 41%, depending on sport (largest decline: ∼38% in team sports, unaffected by sex). Some athletes (range: 7%-49%) maintained their training intensity for strength, endurance, speed, plyometric, change-of-direction, and technical training. Athletes who previously trained ≥5 sessions per week reduced their volume (range: 18%-28%) during lockdown. The proportion of athletes (81%) training ≥60 min/session reduced by 31% to 43% during lockdown. Males and females had comparable moderate levels of training knowledge (56% vs 58%) and beliefs/attitudes (54% vs 56%).CONCLUSIONS:Changes in athletes' training practices were sport-specific, with few or no sex differences. Team-based sports were generally more susceptible to changes than individual sports. Policy makers should provide athletes with specific training arrangements and educational resources to facilitate remote and/or home-based training during lockdown-type events.

There is no convincing evidence for the idea that a high power output at the maximal lactate steady state (PO_MLSS) and a high fraction of $$\dot{V}$$ O2max at MLSS (% $$\dot{V}$$ O2_MLSS) are decisive for endurance performance. We tested the hypotheses that (1) % $$\dot{V}$$ O2_MLSS is positively correlated with the ability to sustain a high fraction of $$\dot{V}$$ O2max for a given competition duration (% $$\dot{V}$$ O2_TT); (2) % $$\dot{V}$$ O2_MLSS improves the prediction of the average power output of a time trial (PO_TT) in addition to $$\dot{V}$$ O2max and gross efficiency (GE); (3) PO_MLSS improves the prediction of PO_TT in addition to $$\dot{V}$$ O2max and GE. Twenty-one recreationally active participants performed stepwise incremental tests on the first and final testing day to measure GE and check for potential test-related training effects in terms of changes in the minimal lactate equivalent power output (∆PO_LEmin), 30-min constant load tests to determine MLSS, a ramp test and verification bout for $$\dot{V}$$ O2max, and 20-min time trials for % $$\dot{V}$$ O2_TT and PO_TT. Hypothesis 1 was tested via bivariate and partial correlations between % $$\dot{V}$$ O2_MLSS and % $$\dot{V}$$ O2_TT. Multiple regression models with $$\dot{V}$$ O2max, GE, ∆PO_LEmin, and % $$\dot{V}$$ O2_MLSS (Hypothesis 2) or PO_MLSS instead of % $$\dot{V}$$ O2_MLSS (Hypothesis 3), respectively, as predictors, and PO_TT as the dependent variable were used to test the hypotheses. % $$\dot{V}$$ O2_MLSS was not correlated with % $$\dot{V}$$ O2_TT (r = 0.17, p = 0.583). Neither % $$\dot{V}$$ O2_MLSS (p = 0.424) nor PO_MLSS (p = 0.208) did improve the prediction of PO_TT in addition to $$\dot{V}$$ O2max and GE. These results challenge the assumption that PO_MLSS or % $$\dot{V}$$ O2_MLSS are independent predictors of supra-MLSS PO_TT and % $$\dot{\text{V}}$$ O2_TT.

Purpose The aim of the study was to evaluate distinct performance indicators and energy system contributions in 3 different, new sport-specific finger flexor muscle exercise tests. Methods The tests included the maximal strength test, the all-out test (30 s) as well as the continuous and intermittent muscle endurance test at an intensity equaling 60% of maximal force, which were performed until target force could not be maintained. Gas exchange and blood lactate were measured in 13 experienced climbers during, as well as pre and post the test. The energy contribution (anaerobic alactic, anaerobic lactic, and aerobic) was determined for each test. Results The contribution of aerobic metabolism was highest during the intermittent test (59.9 ± 12.0%). During continuous exercise, this was 28.1 ± 15.6%, and in the all-out test, this was 19.4 ± 8.1%. The contribution of anaerobic alactic energy was 27.2 ± 10.0% (intermittent), 54.2 ± 18.3% (continuous), and 62.4 ± 11.3% (all-out), while anaerobic lactic contribution equaled 12.9 ± 6.4, 17.7 ± 8.9, and 18.2 ± 9.9%, respectively. Conclusion The combined analysis of performance predictors and metabolic profiles of the climbing test battery indicated that not only maximal grip force, but also all-out isometric contractions are equally decisive physical performance indices of climbing performance. Maximal grip force reflects maximal anaerobic power, while all-out average force and force time integral of constant isometric contraction at 60% of maximal force are functional measures of anaerobic capacity. Aerobic energy demand for the intermittent exercise is dominated aerobic re-phosphorylation of high-energy phosphates. The force-time integral from the intermittent test was not decisive for climbing performance.

Artistic gymnastics is a popular Olympic discipline where female athletes compete in four and male athletes in six events with floor exercise having the longest competition duration in Women’s and Men’s artistic gymnastics (WAG, MAG). To date no valid information on the energetics of floor gymnastics is available although this may be important for specific conditioning programming. This study evaluated the metabolic profile of a simulated floor competition in sub-elite gymnasts. 17 (9 male, 8 female) sub-elite gymnasts aged 22.5 ± 2.6y took part in a floor-training-competition where oxygen uptake was measured during and until 15 min post-exercise. Additionally, resting and peak blood lactate concentration after exercise were obtained. The PCr-LA-O2 method was used to calculate the metabolic energy and the relative aerobic (WAER), anaerobic alactic (WPCr) and anaerobic lactic (WBLC) energy contribution. Further, the athletes completed a 30 s Bosco-jumping test, a countermovement jump and a drop jump. The competition scores were 9.2 (CI:8.9–9.3) in WAG and 10.6 (CI:10.4–10.9) in MAG. The metabolic profile of the floor routine was mainly aerobic (58.9%, CI: 56.0–61.8%) followed by the anaerobic alactic (24.2%, CI: 21.3–27.1%) and anaerobic lactic shares (16.9%, CI:14.9–18.8%). While sex had a significant (p = .010, d = 1.207) large effect on energy contribution, this was not the case for competition duration (p = .728, d = 0.061). Relative energy contribution of WAG and MAG differed in WAER (64.0 ± 4.7% vs. 54.4 ± 6.8%, p = .004, d = 1.739) but not in WPCr (21.3 ± 6.1% vs. 26.7 ± 8.0%, p = .144, d = 0.801) and WBLC (14.7 ± 5.4% vs. 18.9 ± 4.2%, p = .085, d = 0.954). Further no correlation between any energy share and performance was found but between WPCr and training experience (r = .680, p = .044) and WBLC and competition level (r = .668, p = .049). The results show a predominant aerobic energy contribution and a considerable anaerobic contribution with no significant difference between anaerobic shares. Consequently, gymnastic specific aerobic training should not be neglected, while a different aerobic share in WAG and MAG strengthens sex-specific conditioning. All in all, the specific metabolic share must secure adequate energy provision, while relative proportions of the two anaerobic pathways seem to depend on training and competition history.

PURPOSE:To assess the test-retest reliability of the continuous (PCr-LA-O2) and intermittent (PCr-LA-O2int) version of the 3-component model of energy distribution in an applied setting.METHODS:Sixteen male handball players (age 23 [3] y, height 185 [7] cm, weight 85 [14] kg) completed the 30-15 Intermittent Fitness Test (30-15IFT) twice. Performance was assessed by peak speed (speed of the last successfully completed stage of the 30-15IFT [VIFT], in kilometers per hour) and time to exhaustion (in seconds). Oxygen uptake (in milliliters per kilogram per minute) and blood lactate concentrations (in millimoles per liter) were obtained before, during, and until 15 minutes after exercise. Total metabolic energy (in joules per kilogram), total metabolic power (in watts per kilogram), and energy shares (in joules per kilogram and percentage) of the aerobic (energy contribution of the aerobic system [WAERint]), anaerobic lactic, and anaerobic alactic (anaerobic alactic energy [WPCrint]) systems were calculated using both model versions, respectively.RESULTS:Test-retest reliability was very good for VIFT (limits of agreement [LoA]: -1.13 to 0.63 km·h-1, coefficient of variation [CV%] 1.68), time to exhaustion (LoA: -101 to 38 s, CV% 2.92), peak oxygen uptake (LoA: -2.68 to 4.04 mL·min-1·kg-1, CV% 1.48), and peak heart rate (-6.9 to 7.7 beats·min-1, CV% 1.1), but moderate for change in blood lactate concentration (LoA: -3.84 to 4.07 mmol·L-1, CV% 11.43). Reliability of the modeled total energy and its fractions were high for total metabolic energy (LoA: -1489 to 1177 J·kg-1, CV% 2.88), total metabolic power (LoA: -2.0 to 1.9 W·kg-1, CV% 3.58), contribution of aerobic (LoA: -1673 to 1283 J·kg-1, CV% 3.62), WAERint (LoA: -1760 to 2160 J·kg-1, CV% 6.04), and moderate for anaerobic alactic (LoA: -368 to 439 J·kg-1, CV% 14.85), WPCrint (LoA: -1707 to 988 J·kg-1, CV% 9.98), and energy share of anaerobic lactic concentration (LoA: -229 to 235 J·kg-1, CV% 11.43).CONCLUSION:Considering the inherent fluctuations of the underlying energetics, the reliabilities of both versions of the 3-component model of energy distribution are acceptable for applied settings.