Field- and Laboratory-derived Power-Cadence Profiles in World-Class and Elite Track Sprint Cyclists.

Previous investigations comparing Torque-Cadence (T-C) and Power-Cadence (P-C) profiles derived from seated and standing positions and field and laboratory conditions are not congruent with current methodological recommendations. Consequently, the aim of this investigation was to compare seated and standing T-C and P-C profiles generated from field and laboratory testing. Thirteen world-class and elite track sprint cyclists (n = 7 males, maximal power output (Pmax) = 2112 ± 395 W; n = 6 females, Pmax = 1223 ± 102 W) completed two testing sessions in which field- and laboratory-derived T-C and P-C profiles were identified. Standing P-C profiles had significantly (p < 0.05) greater Pmax than seated profiles, however there were no significant differences in optimal cadence (Fopt) between seated and standing positions. Pmax and Fopt were significantly lower in field-derived profiles in both positions compared to laboratory-derived profiles. However, there was no significant difference in the goodness-of-fit (R2) of the P-C profiles between laboratory (0.985 ± 0.02) and field-testing (0.982 ± 0.02) in each position. Valid T-C and P-C profiles can be constructed from field and laboratory protocols; however, the mechanical variables derived from the seated and standing and field and laboratory profiles cannot be used interchangeably. Both field and laboratory-derived profiles provide meaningful information and provide complementary insights into cyclists' capacity to produce power output.

Match Running Performance in Australian Football Is Related to Muscle Fiber Typology.

PURPOSE: To examine the association between muscle fiber typology and match running performance in professional Australian football (AF) athletes. METHODS: An observational time-motion analysis was performed on 23 professional AF athletes during 224 games throughout the 2020 competitive season. Athletes were categorized by position as hybrid, small, or tall. Athlete running performance was measured using Global Navigation Satellite System devices. Mean total match running performance and maximal mean intensity values were calculated for moving mean durations between 1 and 10 minutes for speed (in meters per minute), high-speed-running distance (HSR, >4.17 m·s-1), and acceleration (in meters per second squared), while intercept and slopes were calculated using power law. Carnosine content was quantified by proton magnetic resonance spectroscopy in the gastrocnemius and soleus and expressed as a carnosine aggregate z score (CAZ score) to estimate muscle fiber typology. Mixed linear models were used to determine the association between CAZ score and running performance. RESULTS: The mean (range) CAZ score was -0.60 (-1.89 to 1.25), indicating that most athletes possessed a greater estimated proportion of type I muscle fibers. A greater estimated proportion of type I fibers (ie, lower CAZ score) was associated with a larger accumulation of HSR (>4.17 m·s-1) and an increased ability to maintain HSR as the peak period duration increased. CONCLUSION: AF athletes with a greater estimated proportion of type I muscle fibers were associated with a greater capacity to accumulate distance running at high speeds, as well as a greater capacity to maintain higher output of HSR running during peak periods as duration increases.

The Relevance of Muscle Fiber Type to Physical Characteristics and Performance in Team-Sport Athletes.

PURPOSE: The aim of this systematic review was to (1) determine the muscle fiber-type composition (or muscle fiber typology [MFT]) of team-sport athletes and (2) examine associations between MFT and the physical characteristics and performance tasks in team-sport athletes. METHODS: Searches were conducted across numerous databases-PubMed, SPORTDiscus, MEDLINE, and Google Scholar-using consistent search terms. Studies were included if they examined the MFT of team-sport athletes. Included studies underwent critical appraisal using the McMasters University critical appraisal tool for quantitative research. RESULTS: A total of 10 studies were included in the present review, wherein the MFT of athletes was measured from 5 different team sports (soccer, rugby union, rugby league, handball, and volleyball). There was large variability in the MFT of team-sport athletes both within (up to 27.5%) and between sports (24.0% relative difference). Male football players with a higher proportion of type II fibers had faster 10- and 30-m sprint times, achieved a greater total distance sprinting (distance at >6.67 m·s-1), and a greater peak 1-minute sprint distance. CONCLUSIONS: MFT varies considerably between athletes both within and between different team sports. The results from some studies suggest that variation in MFT is associated with high-intensity running performance in a football match, as well as 10- and 30-m sprint times. Further experimental studies should focus on how determination of the MFT of team-sport athletes could be utilized to influence talent identification, team selection, and the individualization of training.

The influence of cadence on fatigue during maximal sprint cycling in world-class and elite sprint cyclists.

Optimising cadence through appropriate gear selection is a key consideration for track sprint cycling performance, yet the influence of cadence on fatigue (i.e., decrement in power output) within a maximal sprint is not well understood. The aim of this study was to identify the influence of cadence on fatigue during maximal sprint cycling. Eleven world-class and elite track sprint cyclists (n = 6 men, maximal power output (Pmax) = 1894 ± 351 W, optimal cadence (Fopt) = 134 ± 8 rev∙min-1: n = 5 women, Pmax = 1114 ± 80 W, Fopt = 124 ± 8 rev∙min-1) completed two testing sessions where power-cadence profiles were constructed to determine the Fopt associated with Pmax. Cyclists also performed three maximal 15-s sprints (Fopt, ±15%Fopt) to identify fatigue per pedal stroke across these cadence ranges. There was no significant difference (p = 0.2) in the absolute fatigue per pedal stroke when cadence was fixed 15% above (16.7 ± 6.1 W∙stroke-1) and below (15.3 ± 5.1 W∙stroke-1) Fopt. Similarly, there was no significant difference in the relative fatigue per pedal stroke (% peak power∙stroke-1) across Fopt and ± 15%Fopt trials (p = 0.12). The relative decrement in power output is equivalent across the ± 15%Fopt cadence range. As such, a higher-geared, lower-cadence approach to maximal sprint cycling could be a viable method to minimise maximal pedal strokes and reduce the decrement in power output.

Behind enemy lines: Expressing locomotor movements of athletes in the National Rugby League Women's (NRLW) competition relative to opposition data.

We provide a novel analysis of the locomotor movements of athletes in the National Rugby League Women's (NRLW) competition by presenting the data of opposing teams expressed as a relative (%) difference and explore the association with match outcome. 117 rugby league athletes from the four NRLW clubs participated in this study. Mean speed (m·min-1), mean high-speed running (>12 km·h-1; m·min-1), and mean acceleration (m·s-2) were measured in 12 matches (370 individual match files) using the Global Navigation Satellite System (GNSS). Individual GNSS-derived data from each match-half were summed across each team and the association with total points and the points differential in each match-half was determined using linear mixed models. Greater high-speed running and lower mean acceleration were associated with more points being scored. A greater relative difference in mean high-speed running between competing teams was associated with a higher points differential. That is, if a team completed 10% more high-speed running than their opposition, they were likely to score an average of 3.2 points more during a given match-half. This unique analysis of GNSS-derived data may assist coaches and performance support staff to interpret the locomotor movements of female rugby league players with the appropriate considerations for the opposition team.

The balancing act: Identifying multivariate sports performance using Pareto frontiers.

Athletes often require a mix of physical, physiological, psychological, and skill-based attributes that can be conflicting when competing at the highest level within their sport. When considering multiple variables in tandem, Pareto frontiers is a technique that can identify the observations that possess an optimal balance of the desired attributes, especially when these attributes are negatively correlated. This study presents Pareto frontiers as a tool to identify athletes who possess an optimal ranking when considering multiple metrics simultaneously. This study explores the trade-off relationship between batting average and strike rate as well as bowling strike rate, economy, and average in Twenty 20 cricket. Eight hundred ninety-one matches of Twenty 20 cricket from the men's (MBBL) and women's (WBBL) Australian Big Bash Leagues were compiled to determine the best batting and bowling performances, both within a single innings and across each player's Big Bash career. Pareto frontiers identified 12 and seven optimal batting innings performances in the MBBL and WBBL respectively, with nine and six optimal batting careers respectively. Pareto frontiers also identified three optimal bowling innings in both the MBBL and WBBL and five and six optimal bowling careers in MBBL and WBBL, respectively. Each frontier identified players that were not the highest ranked athlete in any metric when analyzed univariately. Pareto frontiers can be used when assessing talent across multiple metrics, especially when these metrics may be conflicting or uncorrelated. Using Pareto frontiers can identify athletes that may not have the highest ranking on a given metric but have an optimal balance across multiple metrics that are associated with success in a given sport.

The Utility of Mixed Models in Sport Science: A Call for Further Adoption in Longitudinal Data Sets.

PURPOSE: Sport-science research consistently contains repeated measures and imbalanced data sets. This study calls for further adoption of mixed models when analyzing longitudinal sport-science data sets. Mixed models were used to understand whether the level of competition affected the intensity of women's rugby league match play. METHODS: A total of 472 observations were used to compare the mean speed of female rugby league athletes recorded during club-, state-, and international-level competition. As athletes featured in all 3 levels of competition and there were multiple matches within each competition (ie, repeated measures), the authors demonstrated that mixed models are the appropriate statistical approach for these data. RESULTS: The authors determined that if a repeated-measures analysis of variance (ANOVA) were used for the statistical analysis in the present study, at least 48.7% of the data would have been omitted to meet ANOVA assumptions. Using a mixed model, the authors determined that mean speed recorded during Trans-Tasman Test matches was 73.4 m·min-1, while the mean speeds for National Rugby League Women and State of Origin matches were 77.6 and 81.6 m·min-1, respectively. Random effects of team, athlete, and match all accounted for variations in mean speed, which otherwise could have concealed the main effects of position and level of competition had less flexible ANOVAs been used. CONCLUSION: These data clearly demonstrate the appropriateness of applying mixed models to typical data sets acquired in the professional sport setting. Mixed models should be more readily used within sport science, especially in observational, longitudinal data sets such as movement pattern analyses.

The Muscle Typology of Elite and World-Class Swimmers.

PURPOSE: To examine whether the muscle typology of elite and world-class swimmers could discriminate between their best distance event, swimming stroke style, or performance level. METHODOLOGY: The muscle carnosine content of 43 male (860 [76] FINA [Fédération Internationale de Natation] points) and 30 female (881 [63] FINA points) swimmers was measured in the soleus and gastrocnemius by proton magnetic resonance spectroscopy and expressed as a carnosine aggregate Z score (CAZ score) to estimate muscle typology. A higher CAZ score is associated with a higher estimated proportion of type II fibers. Swimmers were categorized by their best stroke, distance category (sprinters, 50-100 m; middle distance, 200-400 m; or long distance, 800 m-open water), and performance level (world-class, world top 10, or elite and world top 100 swimmers outside of the world top 10). RESULTS: There was no significant difference in the CAZ score of sprint- (-0.08 [0.55]), middle- (-0.17 [0.70]), or long-distance swimmers (-0.30 [0.75], P = .693). World-class sprint swimmers (all strokes included) had a significantly higher CAZ score (0.37 [0.70]) when compared to elite sprint swimmers (-0.25 [0.61], P = .024, d = 0.94). Breaststroke swimmers (0.69 [0.73]) had a significantly higher CAZ score compared to freestyle (-0.24 [0.54], P < .001, d = 1.46), backstroke (-0.16 [0.47], P = .006, d = 1.42), and butterfly swimmers (-0.39 [0.53], P < .001, d = 1.70). Furthermore, within the cohort of breaststroke swimmers, there was a significant positive correlation between FINA points and CAZ score (r = .728, P = .011); however, this association was not evident in other strokes. CONCLUSION: While there was no clear association between muscle typology and event distance specialization, world-class sprint swimmers possess a greater estimated proportion of type II fibers compared to elite sprint swimmers, as well as breaststroke swimmers compared to freestyle, backstroke, and butterfly swimmers.

Effects of Acute Sleep Loss on Physical Performance: A Systematic and Meta-Analytical Review.

BACKGROUND: Sleep loss may influence subsequent physical performance. Quantifying the impact of sleep loss on physical performance is critical for individuals involved in athletic pursuits. DESIGN: Systematic review and meta-analysis. SEARCH AND INCLUSION: Studies were identified via the Web of Science, Scopus, and PsycINFO online databases. Investigations measuring exercise performance under 'control' (i.e., normal sleep, > 6 h in any 24 h period) and 'intervention' (i.e., sleep loss, ≤ 6 h sleep in any 24 h period) conditions were included. Performance tasks were classified into different exercise categories (anaerobic power, speed/power endurance, high-intensity interval exercise (HIIE), strength, endurance, strength-endurance, and skill). Multi-level random-effects meta-analyses and meta-regression analyses were conducted, including subgroup analyses to explore the influence of sleep-loss protocol (e.g., deprivation, restriction, early [delayed sleep onset] and late restriction [earlier than normal waking]), time of day the exercise task was performed (AM vs. PM) and body limb strength (upper vs. lower body). RESULTS: Overall, 227 outcome measures (anaerobic power: n = 58; speed/power endurance: n = 32; HIIE: n = 27; strength: n = 66; endurance: n = 22; strength-endurance: n = 9; skill: n = 13) derived from 69 publications were included. Results indicated a negative impact of sleep loss on the percentage change (%Δ) in exercise performance (n = 959 [89%] male; mean %Δ = - 7.56%, 95% CI - 11.9 to - 3.13, p = 0.001, I2 = 98.1%). Effects were significant for all exercise categories. Subgroup analyses indicated that the pattern of sleep loss (i.e., deprivation, early and late restriction) preceding exercise is an important factor, with consistent negative effects only observed with deprivation and late-restriction protocols. A significant positive relationship was observed between time awake prior to the exercise task and %Δ in performance for both deprivation and late-restriction protocols (~ 0.4% decrease for every hour awake prior to exercise). The negative effects of sleep loss on different exercise tasks performed in the PM were consistent, while tasks performed in the AM were largely unaffected. CONCLUSIONS: Sleep loss appears to have a negative impact on exercise performance. If sleep loss is anticipated and unavoidable, individuals should avoid situations that lead to experiencing deprivation or late restriction, and prioritise morning exercise in an effort to maintain performance.

The influence of exercise training volume alterations on the gut microbiome in highly-trained middle-distance runners.

The aim of this study was to determine the influence of training volume alterations on diversity and composition of the gut microbiome in a free-living cohort of middle-distance runners. Fourteen highly-trained middle-distance runners (n = 8 men; V˙O2peak = 70.1 ± 4.3 ml·kg·min-1; n = 6 women, V˙O2peak: 59.0 ± 3.2 ml·kg·min-1) completed three weeks of normal training (NormTr), three weeks of high-volume training (HVolTr; a 10, 20 and 30% increase in training volume during each successive week from NormTr), and a one-week taper (TaperTr; 55% exponential reduction in training volume from HVolTr week three). Faecal samples were collected before and immediately after each training phase to quantify alpha-diversity and composition of the gut microbiome. A three-day diet record was collected during each training phase and a maximal incremental running test was completed after each training phase. Results showed no significant changes in nutritional intake, alpha-diversity, or global microbial composition following HVolTr or TaperTr compared to NormTr (p's > 0.05). Following HVolTr, there was a significant decrease in Pasterellaceae (p = 0.03), Lachnoclostridium (p = 0.02), Haemophilus (p = 0.03), S. parasagunis (p = 0.02), and H. parainfluenzae (p = 0.03), while R. callidus (p = 0.03) significantly increased. These changes did not return to NormTr levels following TaperTr. This study shows that the alpha-diversity and global composition of the gut microbiome were unaffected by changes in training volume. However, an increase in training volume led to several changes at the lower taxonomy levels that did not return to pre-HVolTr levels following a taper period.

Strong, Fast, Fit, Lean, and Safe: A Positional Comparison of Physical and Physiological Qualities Within the 2020 Australian Women's Rugby League Team.

ABSTRACT: Minahan, C, Newans, T, Quinn, K, Parsonage, J, Buxton, S, and Bellinger, P. Strong, Fast, Fit, Lean, and Safe: A positional comparison of physical and physiological qualities within the 2020 Australian Women's Rugby League team. J Strength Cond Res 35(12S): S11-S19, 2021-The purpose of the present study was to report the physical and physiological characteristics of elite women Rugby League (RL) players. Thirty-nine women (25.6 ± 4.3 years, 171.3 ± 7.7 cm, 83.5 ± 13.9 kg) from the 2020 Australian women's RL squad were recruited for this study. Players were categorized as adjustables (n = 7), backs (n = 15), or forwards (n = 17) for analysis. Each player was assessed for anthropometry, body composition (dual-energy X-ray absorptiometry), speed (5, 10 and 20 m sprint times), lower-body power (countermovement jump), upper-body power (medicine ball throw and explosive push up force), estimated one repetition maximum (e1RM) bench press, squat and bench pull, isometric mid-thigh pull strength, eccentric knee flexor strength, isometric hip abduction and adduction, and intermittent endurance performance (30-15 intermittent fitness test; 30-15 IFT). Linear mixed models were performed to compare positional groups. Forwards were significantly heavier and had greater fat mass, fat-free mass, and body fat percentage compared with backs and adjustables (P < 0.01). Backs were faster over 20 m compared with forwards (P = 0.025), whereas forwards had a lower 30-15 IFT peak velocity and estimated V̇o2peak compared with backs and adjustables. Nonetheless, when including body mass in the model, there were no differences between groups in 30-15 IFT peak velocity. There were no significant differences in other variables. These results provide contemporary benchmark physical, physiological, and anthropometric data for elite women RL players, which can inform recruitment, selection, training, and testing.

Determinants of Performance in Paced and Maximal 800-m Running Time Trials.

PURPOSE: We aimed to identify the underpinning physiological and speed/mechanical determinants of different types of 800-m running time trials (i.e., with a positive or negative pacing strategy) and key components within each 800-m time trial (i.e., first and final 200 m). METHODS: Twenty trained male 800-m runners (800-m personal best time (min:s): 1:55.10 ± 0:04.44) completed a maximal 800-m time trial (800MAX) and one pacing trial, whereby runners were paced for the first lap, and speed was reduced by 7.5% (800PACE) relative to 800MAX, whereas the last lap was completed in the fastest time possible. Anaerobic speed reserve, running economy, the velocity corresponding with V˙O2peak (VV˙O2peak), maximal sprint speed (MAXSS), maximal accumulated oxygen deficit, and sprint force-velocity-power profiles were derived from laboratory and field testing. Carnosine content was quantified by proton magnetic resonance spectroscopy in the gastrocnemius and soleus and expressed as a carnosine aggregate Z (CAZ) score to estimate muscle typology. Data were analyzed using multiple stepwise regression analysis. RESULTS: MAXSS and vV˙O2peak largely explained the variation in 800MAX time (r2 = 0.570; P = 0.020), whereas MAXSS was the best explanatory variable for the first 200-m time in 800MAX (adjusted r2 = 0.661, P < 0.001). Runners with a higher CAZ score (i.e., higher estimated percentage of type II fibers) reduced their last lap time to a greater extent in 800PACE relative to 800MAX (adjusted r2 = 0.413, P < 0.001), whereas better maintenance of mechanical effectiveness during sprinting, a higher CAZ score and vV˙O2peak was associated with a faster final 200-m time during 800PACE (adjusted r2 = 0.761, P = 0.001). CONCLUSIONS: These findings highlight that diversity in the physiological and speed/mechanical characteristics of male middle-distance runners may be associated with their suitability for different 800-m racing strategies to have the best chance of winning.

The Influence of Muscle Fiber Typology on the Pacing Strategy of 200-m Freestyle Swimmers.

PURPOSE: To determine the influence of muscle fiber typology (MFT) on the pacing strategy of elite swimmers competing in the 200-m freestyle event. METHOD: The top 3 career-best performances from 25 elite 200-m freestyle swimmers were analyzed-12 women (1:58.0 [0:01.3] min:s) and 13 men (1:48.4 [0:02.5]). Muscle carnosine concentration was quantified by proton magnetic resonance spectroscopy in the gastrocnemius and soleus muscles and expressed as a carnosine aggregate z score (CAZ score) relative to an age- and gender-matched nonathlete control group to estimate MFT. Linear regression models were employed to examine the influence of MFT on the percentage of overall race time spent in each 50-m lap. RESULTS: Swimmers with a higher CAZ score spent a greater percentage of race time in lap 3 compared with swimmers with a lower CAZ score (0.1%, 0.0% to 0.2%; mean, 90% confidence interval, P = .02). For every 1% increase in the percentage of race time spent in lap 1, the percentage of race time spent in lap 3 decreased by 0.4% for swimmers with a higher CAZ score (0.2% to -0.5%, P = .00, r = -.51), but not for swimmers with a lower CAZ score (-0.1%, -0.3% to 0.1%, P = .28, r = -.18). The percentage of race time spent in lap 4 decreased by 0.8% for higher-CAZ-score swimmers (-0.5% to -1.0%, P = .00, r = -.66) and by 0.9% for lower-CAZ-score swimmers (-0.6% to -1.3%, P = .00, r = -.65) when lap 1 percentage increased by 1%. CONCLUSION: MFT may influence the pacing strategy of swimmers in the 200-m freestyle event, which provides an avenue for maximizing individualized pacing strategies of elite swimmers.

Movement Patterns and Match Statistics in the National Rugby League Women's (NRLW) Premiership.

As women's rugby league grows, the need for understanding the movement patterns of the sport is essential for coaches and sports scientists. The aims of the present study were to quantify the position-specific demographics, technical match statistics, and movement patterns of the National Rugby League Women's (NRLW) Premiership and to identify whether there was a change in the intensity of play as a function of game time played. A retrospective observational study was conducted utilizing global positioning system, demographic, and match statistics collected from 117 players from all NRLW clubs across the full 2018 and 2019 seasons and were compared between the ten positions using generalized linear mixed models. The GPS data were separated into absolute (i.e., total distance, high-speed running distance, and acceleration load) and relative movement patterns (i.e., mean speed, mean high speed (> 12 km·h-1), and mean acceleration). For absolute external outputs, fullbacks covered the greatest distance (5,504 m), greatest high-speed distance (1,081 m), and most ball-carry meters (97 m), while five-eighths recorded the greatest acceleration load (1,697 m·s-2). For relative external outputs, there were no significant differences in mean speed and mean high speed between positions, while mean acceleration only significantly differed between wingers and interchanges. Only interchange players significantly decreased in mean speed as their number of minutes played increased. By understanding the load of NRLW matches, coaches, high-performance staff, and players can better prepare as the NRLW Premiership expands. These movement patterns and match statistics of NRLW matches can lay the foundation for future research as women's rugby league expands. Similarly, coaches, high-performance staff, and players can also refine conditioning practices with a greater understanding of the external output of NRLW players.

Quantifying the Activity Profile of Female Beach Volleyball Tournament Match-Play.

Effective time-motion analysis can provide information directly applicable to the design of physical conditioning and testing programmes. The aim of the present study was to determine the external output of female beach volleyball players during tournament match-play and to assess the effect of competition level, margin of score differential and alterations of external output within matches. The external output profile of ten adult level (age 27 ± 3 y) and ten under 23 ('U23'; age 19 ± 2 y) female beach volleyball players were determined using GPS technology (10 Hz) during 60 matches (n = 50 first and second sets and 20 third sets files) played during their respective Australian Beach Volleyball Championship tournaments. Comparisons between groups and the influence of contextual factors on the external output within matches were analysed using linear mixed models. Adult beach volleyball players covered a greater relative distance (i.e., m·min-1) in speed zone 2 (1.0-1.99 m·s-1; 42.0% of total relative distance) and zone 3 (≥2.0 m·s-1; 10.9% of total relative distance) compared to U23 players. Relative distance, mean acceleration/deceleration and the relative distance covered in acceleration zone 2 and deceleration zone 2 and 3 was greater in set 1 compared to set 2. Sets that were decided by smaller score margins (<6-point score differential) were comprised of a greater relative distance, peak speed, greater mean acceleration and deceleration output and a greater relative distance in speed zone 1 and 3 compared to sets decided by larger score margins (>5-point score differential). The findings from this study suggest that there are contextual factors that influence the speed and acceleration/deceleration profile of female beach volleyball players such as tournament level, score margin and set-to-set variations that may have implications for the physiological and mechanical requirements of female players preparing for competition.

Muscle Fiber Typology and Its Association With Start and Turn Performance in Elite Swimmers.

PURPOSE: To determine the association between estimated muscle fiber typology and the start and turn phases of elite swimmers during competition. METHODS: International and national competition racing performance was analyzed from 21 female (FINA points = 894 ± 39: 104.5 ± 1.8% world record ratio [WRR]) and 25 male (FINA points = 885 ± 54: 104.8 ± 2.1% WRR) elite swimmers. The start, turn, and turn out times were determined from each of the swimmers' career best performance times (FINA points = 889 ± 48: 104.7 ± 2.0% WRR). Muscle carnosine concentration was quantified by proton magnetic resonance spectroscopy in the gastrocnemius and soleus and was expressed as a carnosine aggregate z score relative to an age- and gender-matched nonathlete control group to estimate muscle fiber typology. Linear mixed models were employed to determine the association between muscle fiber typology and the start and turn times. RESULTS: While there was no significant influence of carnosine aggregate z score on the start and turn times when all strokes and distance events were entered into the model, the swimmers with a higher carnosine aggregate z score (ie, faster muscle typology) had a significantly faster start time in 100-m events compared with the swimmers with a lower carnosine aggregate z score (P = .02, F = 5.825). The start and turn times were significantly faster in the male compared with the female swimmers in the 100-m events compared with other distances, and between the 4 different swimming strokes (P < .001). CONCLUSION: This study suggests that start times in sprint events are partly determined (and limited) by muscle fiber typology, which is highly relevant when ∼12% of the overall performance time is determined from the start time.

The Effect of Consuming Carbohydrate With and Without Protein on the Rate of Muscle Glycogen Re-synthesis During Short-Term Post-exercise Recovery: a Systematic Review and Meta-analysis.

BACKGROUND: Rapid restoration of muscle glycogen stores is imperative for athletes undertaking consecutive strenuous exercise sessions with limited recovery time (e.g. ≤ 8 h). Strategies to optimise muscle glycogen re-synthesis in this situation are essential. This two-part systematic review and meta-analysis investigated the effect of consuming carbohydrate (CHO) with and without protein (PRO) on the rate of muscle glycogen re-synthesis during short-term post-exercise recovery (≤ 8 h). METHODS: Studies were identified via the online databases Web of Science and Scopus. Investigations that measured muscle glycogen via needle biopsy during recovery (with the first measurement taken ≤ 30 min post-exercise and at least one additional measure taken ≤ 8 h post-exercise) following a standardised exercise bout (any type) under the following control vs. intervention conditions were included in the meta-analysis: part 1, water (or non-nutrient beverage) vs. CHO, and part 2, CHO vs. CHO+PRO. Publications were examined for methodological quality using the Rosendal scale. Random-effects meta-analyses and meta-regression analyses were conducted to evaluate intervention efficacy. RESULTS: Overall, 29 trials (n = 246 participants) derived from 21 publications were included in this review. The quality assessment yielded a Rosendal score of 61 ± 8% (mean ± standard deviation). Part 1: 10 trials (n = 86) were reviewed. Ingesting CHO during recovery (1.02 ± 0.4 g·kg body mass (BM)-1 h-1) improved the rate of muscle glycogen re-synthesis compared with water; change in muscle glycogen (MGΔ) re-synthesis rate = 23.5 mmol·kg dm-1 h-1, 95% CI 19.0-27.9, p < 0.001; I2 = 66.8%. A significant positive correlation (R2 = 0.44, p = 0.027) was observed between interval of CHO administration (≤ hourly vs. > hourly) and the mean difference in rate of re-synthesis between treatments. Part 2: 19 trials (n = 160) were reviewed. Ingesting CHO+PRO (CHO: 0.86 ± 0.2 g·kg BM-1 h-1; PRO: 0.27 ± 0.1 g·kg BM-1 h-1) did not improve the rate of muscle glycogen re-synthesis compared to CHO alone (0.95 ± 0.3 g·kg BM-1 h-1); MGΔ re-synthesis rate = 0.4 mmol·kg dm-1 h-1, 95% CI -2.7 to 3.4, p = 0.805; I2 = 56.4%. CONCLUSIONS: Athletes with limited time for recovery between consecutive exercise sessions should prioritise regular intake of CHO, while co-ingesting PRO with CHO appears unlikely to enhance (or impede) the rate of muscle glycogen re-synthesis. TRIAL REGISTRATION: Registered at the International Prospective Register of Systematic Reviews (PROSPERO) (identification code CRD42020156841 ).

Relationships between Lower Limb Muscle Characteristics and Force-Velocity Profiles Derived during Sprinting and Jumping.

PURPOSE: This study aimed to identify the relationships between lower limb muscle characteristics and mechanical variables derived from the vertical (jumping) and horizontal (sprinting) force-velocity-power (FVP) profiles. METHODS: Nineteen subelite male rugby league players performed a series of squat jumps and linear 30-m sprints to derive the vertical and horizontal FVP profiles, respectively. The theoretical maximal force (F0), velocity (V0), and power (Pmax) were derived from both the vertical (i.e., vF0, vV0, and vPmax) and the horizontal (i.e., hF0, hV0, and hPmax) FVP profiles. Vastus lateralis (VL), biceps femoris long head, and gastrocnemius medialis (GM) and lateralis muscle fascicle length, pennation angle, and thickness were measured using B-mode ultrasonography. Magnetic resonance imaging was used to calculate volumes of major lower limb muscles, whereas proton magnetic resonance spectroscopy was used to quantify the carnosine content of the GM to estimate muscle fiber typology. RESULTS: Variation in vPmax was best explained by GM muscle fiber typology (i.e., greater estimated proportion of Type II fibers) and VL volume (adjusted r2 = 0.440, P = 0.006), whereas adductor and vastus medialis volume and GM muscle fiber typology explained the most variation in hPmax (adjusted r2 = 0.634, P = 0.032). Rectus femoris and VL volume explained variation in vF0 (r2 = 0.430, P = 0.008), whereas adductor and vastus medialis volume explained variation in hF0 (r2 = 0.432, P = 0.007). Variations in vV0 and hV0 were best explained by GM muscle fiber typology (adjusted r2 = 0.580, P < 0.001) and GM muscle fiber typology and biceps femoris short head volume (adjusted r2 = 0.590, P < 0.001), respectively. CONCLUSION: Muscle fiber typology and muscle volume are strong determinants of maximal muscle power in jumping and sprinting by influencing the velocity- and force-oriented mechanical variables.

Quantification of maximal power output in well-trained cyclists.

This study aimed to compare mechanical variables derived from torque-cadence and power-cadence profiles established from different cycle ergometer modes (isoinertial and isokinetic) and modelling procedures (second- and third-order polynomials), whilst employing a novel method to validate the theoretical maximal power output (Pmax). Nineteen well-trained cyclists (n = 12 males) completed two experimental sessions comprising six, 6-s maximal isoinertial or isokinetic cycling sprints. Maximal pedal strokes were extracted to construct power-cadence relationships using second- and third-order polynomials. A 6-s sprint at the optimal cadence (Fopt) or optimal resistance (Topt) was performed to assess construct validity of Pmax. No differences were found in the mechanical parameters when derived from isokinetic (Pmax = 1311 ± 415, Fopt = 118 ± 12) or isoinertial modes (Pmax = 1320 ± 421, Fopt = 116 ± 19). However, R2 improved (P < 0.02) when derived from isoinertial sprints. Third-order polynomial modelling improved goodness of fit values (Standard Error, adjusted R2), but derived similar mechanical parameters. Finally, peak power output during the optimised sprint did not significantly differ from the theoretical Pmax in both cycling modes, thus providing construct validity. The most accurate P-C profile can be derived from isoinertial cycling sprints, modelled using third-order polynomial equations.