Oxygen uptake kinetics and speed-time correlates of modified 3-minute all-out shuttle running in soccer players

The Relationship Between the Moderate-Heavy Boundary and Critical Speed in Running

PURPOSE

Training characteristics such as duration, frequency, and intensity can be manipulated to optimize endurance performance, with an enduring interest in the role of training-intensity distribution to enhance training adaptations. Training intensity is typically separated into 3 zones, which align with the moderate-, heavy-, and severe-intensity domains. While estimates of the heavy- and severe-intensity boundary, that is, the critical speed (CS), can be derived from habitual training, determining the moderate-heavy boundary or first threshold (T1) requires testing, which can be costly and time-consuming. Therefore, the aim of this review was to examine the percentage at which T1 occurs relative to CS.

RESULTS

A systematic literature search yielded 26 studies with 527 participants, grouped by mean CS into low (11.5 km·h-1; 95% CI, 11.2-11.8), medium (13.4 km·h-1; 95% CI, 11.2-11.8), and high (16.0 km·h-1; 95% CI, 15.7-16.3) groups. Across all studies, T1 occurred at 82.3% of CS (95% CI, 81.1-83.6). In the medium- and high-CS groups, T1 occurred at a higher fraction of CS (83.2% CS, 95% CI, 81.3-85.1, and 84.2% CS, 95% CI, 82.3-86.1, respectively) relative to the low-CS group (80.6% CS, 95% CI, 78.0-83.2).

CONCLUSIONS

The study highlights some uncertainty in the fraction of T1 relative to CS, influenced by inconsistent approaches in determining both boundaries. However, our findings serve as a foundation for remote analysis and prescription of exercise intensity, although testing is recommended for more precise applications.

3-min All-out Test to Evaluate Aerobic and Anaerobic Indexes in Court Team Sports

This study aimed to test the reproducibility of the 3-min all-out effort applied using shuttle running and compare its values to aerobic parameters. On the first day, 14 futsal players underwent an exhaustive test to determine the maximal incremental speed (MIS) and anaerobic threshold (AnT). On the second day, the participants performed the 3-min all-out effort (n=14), which was repeated after 48 h (third day) to test its reproducibility (n=11). Peak oxygen consumption (V̇ O2PEAK) and peak blood lactate concentrations ([La-]) were determined from 3-min all-out efforts performed through a 20-m shuttle run on the official court. The distance covered, mean speed, and critical speed (CS) during the 3-min all-out presented direct relationships with aerobic parameters determined through the incremental test (r>0.62). The distance covered above CS (D') presented a direct relationship with peak lactate concentrations induced by a 3-min all-out effort (r=0.81). Despite the acceptable levels of reproducibility observed for most of the 3-min all-out variables, the minimal detectable change for D' was high (72%). Our results demonstrated the potential use of mean speed to evaluate aerobic fitness. However, the applicability of the 3-min all-out shuttle run test to monitor training adaptations should be avoided, at least in nonexperienced athletes.

Effect of the Fran CrossFit Workout on Oxygen Uptake Kinetics, Energetics, and Postexercise Muscle Function in Trained CrossFitters

PURPOSE

Fran is one of the most popular CrossFit benchmark workouts used to control CrossFitters' improvements. Detailed physiological characterization of Fran is needed for a more specific evaluation of CrossFitters' training performance improvements. The aim of the study was to analyze the oxygen uptake (V˙O2) kinetics and characterize the energy system contributions and the degree of postexercise fatigue of the unbroken Fran.

METHODS

Twenty trained CrossFitters performed Fran at maximal exertion. V˙O2 and heart-rate kinetics were assessed at baseline and during and post-Fran. Blood lactate and glucose concentrations and muscular fatigue were measured at baseline and in the recovery period.

RESULTS

A marked increase in V˙O2 kinetics was observed at the beginning of Fran, remaining elevated until the end (V˙O2peak: 49.2 [3.7] mL·kg-1·min-1, V˙O2 amplitude: 35.8 [5.2] mL·kg-1·min-1, time delay: 4.7 [2.5] s and time constant: 23.7 [11.1] s; mean [SD]). Aerobic, anaerobic lactic, and alactic pathways accounted for 62% (4%), 26% (4%), and 12% (2%) of energy contribution. Reduction in muscle function in jumping ability (jump height: 8% [6%], peak force: 6% [4%], and maximum velocity: 4% [2%]) and plank prone test (46% [20%]) was observed in the recovery period.

CONCLUSIONS

The Fran unbroken workout is a high-intensity effort associated with an elevated metabolic response. This pattern of energy response highlights the primary contribution of aerobic energy metabolism, even during short and very intense CrossFit workouts, and that recovery can take >24 hours due to cumulative fatigue.

Application of the Force-velocity-power Concept to the 3-Min all-out Running Test

Force-velocity-power (FVP) profiling offers insights related to key factors that may enhance or hinder sprinting performances. Whether the same FVP principles could be applied to the sprinting portion of the 3-minute all-out test for running (3MT) has not been previously investigated. Twenty moderately trained participants volunteered for the study (age: 24.75 ± 3.58 yrs; height: 1.69±0.11 m; mass: 73.74±12.26 kg). After familiarization of all testing procedures, participants completed: (i) a 40-m all-out sprint test, and (ii) a 3MT. Theoretical maximal force and power, but not velocity, were significantly higher for the 40-m sprint test. Most FVP variables from the two tests were weakly to moderately correlated, with the exception of maximal velocity. Finally, maximal velocity and relative peak power were predictive of D', explaining approximately 51% of the variance in D'. Although similar maximal velocities are attained during both the 40-m sprint and the 3MT, the underlying mechanisms are markedly different. The FVP parameters obtained from either test are likely not interchangeable but do provide valuable insights regarding the potential mechanisms by which D' may be improved.

Comparison of parameters derived from a three-minute all-out test with classical benchmarks for running exercise

This study aimed to compare four constructs from the three-minute all-out test (AO3)–end power (EP), the area above EP (WEP), maximum power (Pmax), and attained V˙O2peak−to those derived from the classical CP model in tethered running. Seventeen male recreational runners underwent two experiments to test for reliability and agreement of AO3 parameters with those obtained from the classical CP model (Wꞌ and CP), a graded exercise test (V˙O2max) and a 30-second all-out test (AO30s; Pmax); all performed on a non-motorized treadmill (NMT). Significance levels were set at p<0.05. There were no significant differences between test-retest for Pmax (p = 0.51), WEP (p = 0.39), and EP (p = 0.64), showing generally close to zero bias. Further, retest ICC were high for Pmax and EP (ICC > 0.86) but moderate for WEP (ICC = 0.69). Pmax showed no difference between AO3 and AO30s (p = 0.18; CV% = 9.5%). EP and WEP disagreed largely with their classical critical power model counterparts (p = 0.05; CV%>32.7% and p = 0.23; CV%>39.7%, respectively), showing greater error than their test-retest reliability. V˙O2peak from AO3 was not different (p = 0.13) and well related (CV% = 8.4; ICC = 0.87) to the incremental test V˙O2max. Under the studied conditions, the agreement of EP and WEP to CP and Wꞌ was not strong enough to assure their use interchangeably. Pmax and V˙O2max were closer to their criterion parameters.

Comparison of Physiological and Perceptional Responses to 5-m Forward, Forward-Backward, and Lateral Shuttle Running

Purpose

The aim of this study was to investigate the physiological and perceptional responses to forward, forward-backward, and lateral shuttle running.

Methods

Twenty-four eligible male subjects performed a maximal oxygen uptake (VO_2max) test and three directional modes (i.e., forward, forward-backward, and lateral) of 5-m shuttle running at the speed of 6 km⋅h^–1 for 5 min on separate days. Heart rate (HR) and oxygen uptake (VO₂) were continuously measured during the whole tests. Rating of perceived exertion (RPE) was inquired and recorded immediately after the test. Capillary blood samples were collected from the earlobe during the recovery to determine the peak value of blood lactate concentration ([La^–]_peak).

Results

Running directional mode had significant effects on HR (F = 72.761, P < 0.001, η²_p = 0.760), %HR_max (F = 75.896, P < 0.001, η²_p = 0.767), VO₂ (F = 110.320, P < 0.001, η²_p = 0.827), %VO_2max (F = 108.883, P < 0.001, η²_p = 0.826), [La^–]_peak (F = 55.529, P < 0.001, η²_p = 0.707), and RPE (F = 26.268, P < 0.001, η²_p = 0.533). All variables were significantly different between conditions (P ≤ 0.026), with the variables highest in lateral shuttle running and lowest in forward shuttle running. The effect sizes indicated large magnitude in the differences of all variables between conditions (ES = 0.86–2.83, large) except the difference of RPE between forward and forward-backward shuttle running (ES = 0.62, moderate).

Conclusion

These findings suggest that the physiological and perceptional responses in shuttle running at the same speed depend on the directional mode, with the responses highest in lateral shuttle running, and lowest in forward shuttle running.

Optimization of the Critical Speed Concept for Tactical Professionals: A Brief Review

Tactical professionals often depend on their physical ability and fitness to perform and complete occupational tasks to successfully provide public services or survive on the battlefield. Critical speed (CS), or maximal aerobic steady-state, is a purported measure that predicts performance, prescribes exercise, and detects training adaptions with application to tactical professionals. The CS concept has the versatility to adapt to training with load carriage as an integrated bioenergetic system approach for assessment. The aims of this review are to: (1) provide an overview of tactical populations and the CS concept; (2) describe the different methods and equipment used in CS testing; (3) review the literature on CS associated with tactical occupational tasks; and (4) demonstrate the use of CS-derived exercise prescriptions for tactical populations.

Comparing critical speed modelling approaches and exploring relationships with match-play variables in elite male youth soccer players

Background

A novel bi-exponential method has emerged to estimate critical speed (CS) and D-prime (D') from a 3-min all-out test (3MT).

Objectives

To compare CS analysis methods to determine whether parameter estimations were interchangeable. Reference values and relationships with key soccer match-play variables were explored.

Methods

Thirteen elite male youth (14-15 years old) players completed a 30 m shuttle run 3MT to estimate CS, D', rate of speed decline time constant, maximal speed (S _max), time to S _max (t _max), and fatigue index (FI), using the traditional method and bi-exponential model on average (Bi-Exp_Average) and max speed settings (Bi-Exp_Max-Speed). High-speed running (HSR) and sprinting distances and counts, and the number of accelerations were collected from two matches. Magnitude-based inferences (p < 0.05) with smallest worthwhile change of 0.2 effect sizes were used to analyse differences. Pearson's and Spearman's correlation coefficients were used to measure associations between CS model variables and match-play parameters.

Results

There were significant differences between the traditional method and both bi-exponential models for CS and D', as well as between the bi-exponential models for all variables except t _max. Using the Bi-Exp_Average model, strong correlations (r = 0.70-0.73; p < 0.05) were observed for D' and FI with the number of standardised and individualised HSRs, respectively. With the Bi-Exp_Max-Speed model, there were strong correlations (r/ρ = 0.64-0.68; p < 0.05) between D' and the number of standardised HSRs and sprints, and the number of individualised sprints.

Conclusion

There is a lack of interchangeability between analysis methods. It appears that D' and FI from the bi-exponential models could be associated with high-intensity actions in soccer match-play.

Is a verification phase useful for confirming maximal oxygen uptake in apparently healthy adults? A systematic review and meta-analysis

BACKGROUND

The 'verification phase' has emerged as a supplementary procedure to traditional maximal oxygen uptake (VO2max) criteria to confirm that the highest possible VO2 has been attained during a cardiopulmonary exercise test (CPET).

OBJECTIVE

To compare the highest VO2 responses observed in different verification phase procedures with their preceding CPET for confirmation that VO2max was likely attained.

METHODS

MEDLINE (accessed through PubMed), Web of Science, SPORTDiscus, and Cochrane (accessed through Wiley) were searched for relevant studies that involved apparently healthy adults, VO2max determination by indirect calorimetry, and a CPET on a cycle ergometer or treadmill that incorporated an appended verification phase. RevMan 5.3 software was used to analyze the pooled effect of the CPET and verification phase on the highest mean VO2. Meta-analysis effect size calculations incorporated random-effects assumptions due to the diversity of experimental protocols employed. I2 was calculated to determine the heterogeneity of VO2 responses, and a funnel plot was used to check the risk of bias, within the mean VO2 responses from the primary studies. Subgroup analyses were used to test the moderator effects of sex, cardiorespiratory fitness, exercise modality, CPET protocol, and verification phase protocol.

RESULTS

Eighty studies were included in the systematic review (total sample of 1,680 participants; 473 women; age 19-68 yr.; VO2max 3.3 ± 1.4 L/min or 46.9 ± 12.1 mL·kg-1·min-1). The highest mean VO2 values attained in the CPET and verification phase were similar in the 54 studies that were meta-analyzed (mean difference = 0.03 [95% CI = -0.01 to 0.06] L/min, P = 0.15). Furthermore, the difference between the CPET and verification phase was not affected by any of the potential moderators such as verification phase intensity (P = 0.11), type of recovery utilized (P = 0.36), VO2max verification criterion adoption (P = 0.29), same or alternate day verification procedure (P = 0.21), verification-phase duration (P = 0.35), or even according to sex, cardiorespiratory fitness level, exercise modality, and CPET protocol (P = 0.18 to P = 0.71). The funnel plot indicated that there was no significant publication bias.

CONCLUSIONS

The verification phase seems a robust procedure to confirm that the highest possible VO2 has been attained during a ramp or continuous step-incremented CPET. However, given the high concordance between the highest mean VO2 achieved in the CPET and verification phase, findings from the current study would question its necessity in all testing circumstances.

PROSPERO REGISTRATION ID

CRD42019123540.

Predicting Maximal Oxygen Uptake Using the 3-Minute All-Out Test in High-Intensity Functional Training Athletes

Maximal oxygen uptake (VO2max) and critical speed (CS) are key fatigue-related measurements that demonstrate a relationship to one another and are indicative of athletic endurance performance. This is especially true for those that participate in competitive fitness events. However, the accessibility to a metabolic analyzer to accurately measure VO2max is expensive and time intensive, whereas CS may be measured in the field using a 3 min all-out test (3MT). Therefore, the purpose of this study was to examine the relationship between VO2max and CS in high-intensity functional training (HIFT) athletes. Twenty-five male and female (age: 27.6 ± 4.5 years; height: 174.5 ± 18.3 cm; weight: 77.4 ± 14.8 kg; body fat: 15.7 ± 6.5%) HIFT athletes performed a 3MT as well as a graded exercise test with 48 h between measurements. True VO2max was determined using a square-wave supramaximal verification phase and CS was measured as the average speed of the last 30 s of the 3MT. A statistically significant and positive correlation was observed between relative VO2max and CS values (r = 0.819, p < 0.001). Based on the significant correlation, a linear regression analysis was completed, including sex, in order to develop a VO2max prediction equation (VO2max (mL/kg/min) = 8.449(CS) + 4.387(F = 0, M = 1) + 14.683; standard error of the estimate = 3.34 mL/kg/min). Observed (47.71 ± 6.54 mL/kg/min) and predicted (47.71 ± 5.7 mL/kg/min) VO2max values were compared using a dependent t-test and no significant difference was displayed between the observed and predicted values (p = 1.000). The typical error, coefficient of variation, and intraclass correlation coefficient were 2.26 mL/kg/min, 4.90%, and 0.864, respectively. The positive and significant relationship between VO2max and CS suggests that the 3MT may be a practical alternative to predicting maximal oxygen uptake when time and access to a metabolic analyzer is limited.

Critical speed and finite distance capacity: norms for athletic and non-athletic groups

PURPOSE

Two parameters in particular span both health and performance; critical speed (CS) and finite distance capacity (D'). The purpose of the present study was to: (1) classify performance norms, (2) distinguish athletic from non-athletic individuals using the 3-min all-out test (3MT) for running, and (3) introduce a deterministic model highlighting the relationship between variables of the 3MT.

METHODS

Athletic (n = 43) and non-athletic (n = 25) individuals participated in the study. All participants completed a treadmill graded exercise test (GXT) with verification bout and a 3MT on an outdoor sprinting track.

RESULTS

Meaningful differences between non-athletic and athletic individuals (denoted by mean difference scores, p value and Cohen's d with 95% confidence intervals) were evident for CS (- 0.74 m s^-1, p < 0.001, d = - 1.41 [1.97, - 0.87]), exponential growth time constant ([Formula: see text]; 2.75 s, p < 0.001, d = - 1.29 [- 1.45, - 0.42]), time to maximal speed ([Formula: see text]; - 2.80 s, p < 0.001, d = - 0.98 [- 1.51, - 0.47]), maximal speed ([Formula: see text]; - 1.36 m s^-1, p < 0.001, d = - 1.56 [- 2.13, - 1.01]), gas exchange threshold (GET; - 5.62 ml kg^-1 min^-1, p < 0.001, d = - 0.97 [- 1.50, - 0.45]), distance covered in the first minute (1st min; - 81.69 m, p < 0.001, d = - 1.91 [- 2.52, - 1.33]), distance covered in the second minute (2nd min; - 52.02 m, p < 0.001, d = - 1.71 [- 2.30, - 1.15]) and maximal distance (- 153.78 m, p < 0.001, d = - 1.27 [- 1.82, - 0.74]). The correlation coefficient between key physiological and performance variables are shown in the form of a deterministic model created from the data derived from the 3MT.

CONCLUSIONS

Coaches and clinicians may benefit from the use of normative data to potentially identify exceptional or irregular occurrences in 3MT performances.

Bi-exponential modeling derives novel parameters for the critical speed concept

All-out exercise testing (AOT) has emerged as a method for quantifying critical speed (CS) and the curvature constant (D'). The AOT method was recently validated for shuttle running yet how that method compares with linear running is unknown. In the present study, we utilized a novel bi-exponential model that derives CS and D' with additional new parameters from the AOT method. Fourteen male athletes (age = 21.6 ± 2.2 years; height = 177 ± 70 cm; weight = 83.0 ± 11.8 kg) completed a graded exercise test (GXT) to derive maximum oxygen uptake ( V ˙ O 2 max ) and the average speed between gas exchange threshold and V ˙ O 2 max (sΔ50%), a linear AOT, and two shuttle AOTs. Measurement agreement was determined using intraclass correlation coefficient (ICC α ), typical error (TE), and coefficient of variation (CV). The y-asymptote ( S 0 ) of the speed-time curve (3.52 ± 0.66 m·sec-1 ) did not differ from sΔ50% (3.49 ± 0.41 m·sec-1 ) or CS (3.77 ± 0.56 m·sec-1 ) (P = 0.34). Strong agreement was observed for estimates of CS (ICC α  = 0.92, TE = 0.18 m·sec-1 , and CV = 5.7%) and D' (ICC α  = 0.94, TE = 16.0 m, CV = 7.6%) with significant (P < 0.01) correlations observed between V ˙ O 2 max and CS and between S 0 and V ˙ O 2 max (r values of 0.74 and 0.84, respectively). The time constant of the decay in speed ( τ d ) and the amplitude between maximal speed and S 0 ( A d ) emerged as unique metrics. The A d and τ d metrics may glean new insights for prescribing and interpreting high-intensity exercise using the AOT method.

Energetics of male field-sport athletes during the 3-min all-out test for linear and shuttle-based running

PURPOSE

All-out, non-steady state running makes for difficult comparisons regarding linear and shuttle running; yet such differences remain an important distinction for field-based sports. The purpose of the study was to determine whether an energetic approach could be used to differentiate all-out linear from shuttle running.

METHODS

Fifteen male field-sport athletes volunteered for the study (means ± SD): age, 21.53 ± 2.23 years; height, 1.78 ± 0.68 m; weight, 83.85 ± 11.73 kg. Athletes completed a graded exercise test, a 3-min linear all-out test and two all-out shuttle tests of varied distances (25 m and 50 m shuttles).

RESULTS

Significant differences between the all-out tests were found for critical speed (CS) [F(8.97), p < 0.001), D' (finite capacity for running speeds exceeding critical speed) [F(7.83), p = 0.001], total distance covered [F(85.31), p < 0.001], peak energetic cost ([Formula: see text]) [F(45.60), p < 0.001], peak metabolic power ([Formula: see text]) [F(23.36), p < 0.001], average [Formula: see text] [F(548.74), p < 0.001], maximal speed [F(22.87), p < 0.001] and fatigue index [F(3.93), p = 0.027]. Non-significant differences were evident for average [Formula: see text] [F(2.47), p = 0.097], total [Formula: see text] [F(0.86), p = 0.416] and total [Formula: see text] [F(2.11), p = 0.134].

CONCLUSIONS

The energetic approach provides insights into performance characteristics that differentiate linear from shuttle running, yet surprising similarities between tests were evident. Key parameters from all-out linear and shuttle running appear to be partly interchangeable between tests, indicating that the final choice between linear and shuttle testing should be based on the requirements of the sport.