Skip to main content
Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Relationship between anaerobic capacity estimated using a single effort and 30-s tethered running outcomes

  • Alessandro Moura Zagatto ,

    Affiliations São Paulo State University (Unesp), School of Sciences, Laboratory of Physiology and Sports Performance (LAFIDE), Bauru-SP, Brazil, Post-Graduate Program in Movement Sciences, São Paulo State University (Unesp), Institute of Biosciences, Rio Claro–SP, Brazil

  • Willian Eiji Miyagi,

    Affiliations São Paulo State University (Unesp), School of Sciences, Laboratory of Physiology and Sports Performance (LAFIDE), Bauru-SP, Brazil, Post-Graduate Program in Movement Sciences, São Paulo State University (Unesp), Institute of Biosciences, Rio Claro–SP, Brazil

  • Filipe Antônio de Barros Sousa,

    Affiliation Campinas State University (UNICAMP), School of Applied Sciences, Limeira-SP, Brazil

  • Claudio Alexandre Gobatto

    Affiliation Campinas State University (UNICAMP), School of Applied Sciences, Limeira-SP, Brazil


The purpose of the current study was to investigate the relationship between alternative anaerobic capacity method (MAODALT) and a 30-s all-out tethered running test. Fourteen male recreational endurance runners underwent a graded exercise test, a supramaximal exhaustive effort and a 30-s all-out test on different days, interspaced by 48h. After verification of data normality (Shapiro-Wilk test), the Pearson’s correlation test was used to verify the association between the anaerobic estimates from the MAODALT and the 30-s all-out tethered running outputs. Absolute MAODALT was correlated with mean power (r = 0.58; P = 0.03), total work (r = 0.57; P = 0.03), and mean force (r = 0.79; P = 0.001). In addition, energy from the glycolytic pathway (E[La-]) was correlated with mean power (r = 0.58; P = 0.03). Significant correlations were also found at each 5s interval between absolute MAODALT and force values (r between 0.75 and 0.84), and between force values and E[La-] (r between 0.73 to 0.80). In conclusion, the associations between absolute MAODALT and the mechanical outputs from the 30-s all-out tethered running test evidenced the importance of the anaerobic capacity for maintaining force during the course of time in short efforts.


Maximal accumulated oxygen deficit (MAOD) has been widely used as an anaerobic capacity estimative [14], i.e., the amount of energy that can be resynthesized by the phosphagen and glycolysis metabolism pathways. Anaerobic capacity has been well related to several exercise modes with a high-intensity and relatively short duration [5].

Some studies have described the effective use of the blood lactate response (i.e., post-exercise minus resting values) to estimate the oxygen equivalent corresponding to the glycolytic metabolic pathway [68] and the fast phase of excessive post-exercise oxygen consumption (EPOCFAST) to estimate the equivalent of oxygen corresponding to the phosphagen metabolic pathway [7,8]. In this way, some authors have reported that the sum of both equivalents of oxygen from the phosphagen and glycolytic metabolic pathways allow assessment of the anaerobic capacity in a single supramaximal exhaustive effort, denominated by authors of the alternative MAOD method (MAODALT) [914]. Recently Zagatto et al. [13] reported the validity, reliability and reproducibility of the MAODALT for estimating the anaerobic capacity in treadmill running, evidencing that exercise intensity at 115% of maximal oxygen uptake (iVO2max) is the greatest intensity for MAODALT determination. In addition, this same group of authors recently reported that MAODALT assessed in treadmill running can be considered a sensitive enough procedure to distinguish the anaerobic capacity in individuals with different training levels (untrained, moderately active, recreational endurance runners and elite rugby sevens players) [15]

This method has a better practical application than the conventional MAOD method, which is basically assessed through oxygen uptake (VO2), measured in several submaximal and supramaximal trials [2], precluding its wide use in the training routine. In addition to assessment of anaerobic capacity, another advantage of the MAODALT is the possibility of estimating the maximal energy contributions from the glycolytic and phosphagen metabolism pathways [9], a distinction that is unable to be performed using conventional MAOD.

Despite MAODALT being easy to estimate regarding time required, it is a recent method that requires further investigation, principally comparing it with other scientifically accepted procedures, such as the 30-s Wingate anaerobic test [16].

The 30-s Wingate Anaerobic test is a widely used test to measure the anaerobic metabolism; it has been recognized that the peak power and mean power outputs measured during a 30-s Wingate Anaerobic test must represent the breakdown of phosphocreatine and muscle glycogen depletion, respectively [17,18]. In this way, the 30-s Wingate Anaerobic test has also been used to validate other anaerobic tests [5,9]. Recently, Bertuzzi et al. [9] described, in nine physical education students, significant correlations between MAODALT measured in cycling with peak power (r = 0.78) and mean power (r = 0.79) from a 30-s Wingate Anaerobic test. Furthermore, the authors reported that the glycolytic metabolism pathway was correlated with mean power (r = 0.71) and the phosphagen metabolism pathway with peak power (r = 0.72) from the 30-s Wingate Anaerobic test [9]. Despite the relevant findings, the use of a 30-s Wingate Anaerobic test, such as reported by Bertuzzi et al. [9], is restricted to cycle ergometer and cannot be transferred to running, which is the most common locomotion mode performed by humans in sport, in addition to which, the cited study had a low sample size consisting of physical education students.

Recent studies evidenced higher correlations between sprint running performance and peak and mean power measured in running efforts, rather than on a cycle ergometer [1,16].

The running anaerobic sprint test was considered as an adaptation of the 30-s Wingate Anaerobic test for running [16,19] considering Newton's second law (force = mass x acceleration), but the use of body mass to calculate the force (i.e., force = body mass x distance/ time2) in horizontal running is the main limitation to assessing running power using this procedure. Therefore, the application of an all-out tethered run measuring the horizontal force may be more appropriate [1,2023], and it can be used to investigate the association of MAODALT and a 30-s maximal effort such as performed by Bertuzzi et al. [9] in cycling.

Thus, the purpose of the current study was to investigate the relationship between MAODALT and parameters measured in a 30-s all-out tethered running test. Based on recent findings of Bertuzzi et al. [9] and studies that verified significant correlations between MAODALT and the 30-s Wingate Anaerobic test, we hypothesized that MAODALT would be significantly correlated with the 30-s all-out tethered running test outputs, chiefly regarding mean values.

In addition, such as previously investigations have reported that the MAODALT is similar to conventional MAOD [13,14], the current study advances in literature [10,1214,24] using only the MAODALT method and assuming it as an valid method to estimate the anaerobic capacity [9,13,14,25].

Materials and methods


The sample size was based on a sample calculation taking into consideration a significant correlation between MAODALT and power output from the Wingate test of 0.79 [9] and a test power of 95%, resulting in a minimum sample size of eleven participants (software G*Power 3.0.10, Franz Faul, Germany).

Fourteen male recreational endurance runners were recruited for this study (mean±SD, age 29±4 years; height 177.0±6.1 cm; body mass 74.3±8.0 kg; body fat 16.2±3.8% and VO2max 55.3±4.5 mL/kg/min). These subjects performed at least three running training sessions per week (weekly training volume ~40 km, at least three times per week), but were not professional athletes. The 10-km running times of the participants were between 40 and 60 min, which is a pace between 10 and 15 km/h. All subjects were familiarized with the experimental procedures and equipment and were instructed to eat the same individual light meal at least 2 hours before the tests, to maintain hydration habits, and to avoid additional sessions of hard physical activity and alcohol or caffeine ingestion during the experimental period.

Inclusion and exclusion criteria

Participants were included in the study if they met the following inclusion criteria; a weekly training routine of at least 3 times per week, maximal oxygen uptake (VO2max) higher than 50 mL/kg/min and intensity at VO2max (iVO2max) of at least 15 km/h, measured in a graded exercise test. Athletes who presented any kind of tendon, joint or skeletal muscle lesion were excluded from the sample, as were participants who took any dietary supplements during the 3 months prior to the start of the study.

The subject recruitment was performed via a direct approach to the coach of the recreational runner groups, who selected the runners according to the inclusion criteria required for the study. Subsequently, the runners were invited to participate in the study according to their personal and physical training availability.

The subjects were informed about the possible risks and benefits of the study prior to signing an informed consent, and all procedures were conducted respecting the declaration of Helsinki. The experimental procedures used in both studies, as well as the informed consent, were approved by the Research Ethics Committee of the University (Protocol number 645.784/2014).

Experimental procedures

All exercise sessions were applied over two weeks, with the subjects performing four visits to the laboratory separated by a recovery interval of at least 48 hours. On the first visit the body composition was assessed by means of a whole-body dual-energy X-ray absorptiometry scan (Hologic QDR, Discovery, Bedford, USA) and each participant performed a familiarization session on the non-motorized treadmill. On the second visit a graded exercise test (GXT) was applied, and on the third and fourth visits a supramaximal exhaustive effort at 115% of the intensity associated with maximal oxygen uptake or a 30-s all-out tethered running test (30-s ATR) was performed in random order.

The GXT and supramaximal exhaustive effort test were performed on a motorized treadmill (ATL, Inbramed, Inbrasport, Porto Alegre, RS, Brazil) with a fixed treadmill incline of 1% [26,27], while the 30-s ATR was performed on a non-motorized treadmill adapted from a motorized model (Inbramed, Inbrasport, Porto Alegre, RS, Brazil), as used and detailed in recent studies [21,28]. To eliminate any influence of circadian variation, each subject completed all trials at the same time period of day in controlled environmental conditions regarding temperature (22.9 ± 1.3°C) and relative humidity (43.8 ± 6.3%). In all efforts, participants were verbally encouraged to perform maximally and wore a chest harness with the rope attached to the ceiling to ensure maximal effort without fall risk (except the 30-s ATR) [13,15]. Prior to each exercise trial, the subjects responded to the profile of mood states scale to measure their motivation for the effort. If a state of fatigue, low vigor, or stress was detected, a new date for the test was scheduled.

Prior to each effort, a warm-up lasting 5-min at 8 km/h was performed with the test starting four minutes after the end of the warm-up. Only for the 30-s ATR, in the warm-up, two sprints were added lasting 3-4s performed in the 3rd and 4th minutes.

Physiological analysis.

Respiratory gas exchange and heart rate (HR) were collected breath-by-breath during all tests using a Cosmed Quark PFT gas analysis system (Quark PFT, Cosmed, Rome, Italy) coupled with a polar transmitter belt (T31, Polar Electro, Kempele, Finland). During the supramaximal effort, the VO2 was measured over the 10 minutes of rest before the warm-up (i.e., sitting in a chair), during the efforts, and for seven minutes after the end of the exercise, to assess the fast component of excess post-exercise oxygen consumption (EPOCFAST). Before each test, the gas analyzer was calibrated using an ambient air sample and a high-precision gas mixture (3.98% CO2 and 16.02% O2; White Martins®, Osasco, Brazil), whereas the spirometer was calibrated using a 3-liter syringe (Hans Rudolf, Kansas City, Missouri, USA), in accordance with the manufacturer’s instructions. After the removal of outliers to exclude discrepant breaths, breath-by-breath VO2 data were smoothed using a 5-second moving average and interpolated to give 1-second values (OriginPro 8.0; Origin Lab Corporation, Microcal, MA, USA) to enhance the underlying VO2 response characteristics [29].

To measure the blood lactate concentration ([La-]), blood samples were drawn from the earlobe (25 μL) after 10 minutes of rest and 3, 5 and 7 minutes after the end of exercise in the supramaximal test and the 30-s ATR, while in the GXT the blood samples were drawn only after the effort. Blood samples were stored at -20°C in tubes containing 50 micro-liters of sodium fluoride (1%) and later analyzed using an electrochemical lactate analyzer (Yellow Springs Instruments model 2300, Ohio, USA) to determine the [La-] (measurement error of ±2%).

Graded Exercise Test (GXT) to assess VO2max and iVO2max.

The GXT began at 8 km/h with stage increments of 1.5 km/h every 2 minutes until exhaustion, given voluntarily by the participant or by their inability to perform the effort at the pre-determined speed [10,13]. The GXT was based on the guidelines of Howley et al.[30] for VO2max and designed to last 8–12 minutes. The Borg scale (6–20) [31] was used to assess the rate of perceived exertion (RPE) at the end of each stage of the GXT. VO2 was measured during the entire test and the highest VO2 average (i.e., VO2 average over the final 30s of each stage) was assumed as VO2max, considering the verification of a plateau in VO2 (variation in VO2<2.1 mL·kg-1·min-1 between the final and penultimate stage of exercise). Secondary criteria were: 1) maximal HR (HRmax) ≥ 90% of predicted HRmax [32]; 2) respiratory exchange ratio (RER) ≥ 1.10 and 3) peak lactate ≥ 8.0 mmol·L-1. The minimal exercise intensity at which the subject reached VO2max was considered as iVO2max [33]. If the final stage had not been completed, the iVO2max was determined using the method proposed by Kuipers et al. [34] [iVO2max = running speed of the final complete stage + (velocity increment after each stage × time sustained during the incomplete stage / total time of stage)].

30-s All-out Tethered Running Test (30-s ATR).

The 30-s ATR was performed on a non-motorized treadmill (Inbramed, Inbrasport, Porto Alegre, RS, Brazil) and consisted of running in an all-out maximal effort for 30-s [23], with velocity and horizontal force measured by a high frequency (1000 Hz) signal acquisition system [21,28,35].

The signal acquisition system consisted of a strain gage (CSA/ZL-100, MK Control, Sao Paulo, Brazil), a portable amplifier (MKTC5-10, MK Control, Sao Paulo, Brazil) and a data acquisition module (NI USB-6009, National Instruments, Austin, USA). The strain gage was connected to the runner’s waist by an inextensible thread (2-m) and a nylon belt. This way, data of force was measured by the strain gages, while velocity was calculated as the first derivative of displacement, which was measured by a pulse sensor placed in the treadmill. Force and displacement signals were captured using specific software (LabView2012—National Instruments, Signal Express—Austin, Texas, EUA) and then transferred and analyzed using MatLab (MatLab®, MathWorkstm, USA) (Fig 1). The force and velocity data were synchronized each 1-ms for assessment of running power (i.e., multiplication of force and velocity during the effort). Next, 5-s averages were performed for determination of peak power (highest 5-s value), mean power (average of all 5-s values) and power decrement [36]. The peak power and mean power were presented in absolute and relative to body mass values. Likewise, the peak force, mean force, mean velocity and distance covered were also determined considering 5-s averages. Lastly, total work and the time to attain the maximal velocity were also assessed [28]. The power measurement in sprinting on a non-motorized treadmill measured by force transducers and goniometers has presented high test-retest reliability (r = 0.94; ICC = 0.90) [22]

Fig 1. Schematic model for the 30-s all-out tethered running test on a non-motorized treadmill.

Supramaximal exhaustive effort and assessment of MAODALT.

The supramaximal exhaustive effort consisted of a maximal effort at 115% of iVO2max [13]. The time to exhaustion was recorded. Energetic contributions from the phosphagen metabolic pathway (EPCr) and glycolytic metabolic pathway (E[La-]) were estimated during the test and the MAODALT was assumed as the sum of both oxygen equivalents [3,7,8,10,11,14]. Zagatto et al. [13] reported high test and retest reliability for MAODALT determined at 115% of iVO2max during treadmill running (ICC = 0.87).

The E[La-] amount of energy was estimated by subtracting resting blood lactate from post-exercise blood lactate concentration (Δ[La-]), considering a value of 1 mmol.L-1 to be equivalent to 3 mL O2/kg body mass.[7,8] The EPCr contribution was considered to be the EPOCFAST [6,7,13,37], which was estimated by multiplying the amplitude and the time constant of the fast component of a bi-exponential model (Eq 1) using OriginPro 8.0 software (OriginLab Corporation, Microcal, Massachusetts, USA) (Eq 2) [13,25,37,38]. Equation (1) where VO2(t) is the oxygen uptake at time t, VO2baseline is the oxygen uptake at baseline, A is the amplitude, δ is the time delay and τ is the time constant. The numbers 1 and 2 after A represent the fast and slow components, respectively, and the EPOCFAST was calculated by the product of A1 and τ1.

Statistical analysis.

The data are presented as mean ± standard deviation (SD) and confidence interval of 95% (CI95%). Data normality was initially verified using the Shapiro-Wilk test allowing the use of parametric statistical analysis. The Pearson’s correlation test was used to verify the association between the MAODALT value and the 30-s ATR outputs. The coefficient of correlation was classified as very weak to negligible (0 to 0.2), weak (0.2 to 0.4), moderate (0.4 to 0.7), strong (0.7 to 0.9), and very strong (0.9 to 1.0).[39] In all cases, a significance level of 5% was assumed. All statistical analysis was performed using the Statistical Package for Social Sciences (SPSS Inc. Released 2009. PASW Statistics for Windows, Version 18.0. Chicago, USA)


In the GXT, all subjects attained the criteria for assessment of VO2max, with [La-] peak values of 11.4 ± 2.1 mmol/L (CI95% = 10.1 − 12.6 mmol/L), heart rate of 188.7 ± 5.4 bpm (CI95% = 185.6 − 191.8 bpm) and respiratory exchange ratio of 1.16 ± 0.06 (CI95% = 1.13 − 1.19). Therefore, the VO2max was 55.3 ± 4.5 mL/kg/min (CI95% = 52.6 −57.9 mL/kg/min) and the iVO2max was 16.4 ± 0.9 km/h (CI95% = 16.0 − 17.1 km/h).

The mechanical variables measured during the 30-s ATR are shown in Table 1, whereas Fig 2 shows the behavior of force (2A), velocity (2B), power (2C) and distance covered (2D) measured over time (i.e., values measured as 5-s averages).

Fig 2.

Values of force (A), velocity (B), power (C) and distance covered (D) during the 30-s all-out tethered running test averaged each 5-s of effort. The circles are the mean values and the dark gray area corresponds to the upper and lower standard deviations.

Table 1. Values of power, force, velocity power decrement, total distance covered, total work and time to attain the maximal velocity measured in the 30-s ATR.

Results in Mean ± SD and CI95%.

The exercise intensity in the supramaximal exhaustive test of 115% of iVO2max corresponded to 19.1 ± 1.1 km/h (CI95% = 18.4 − 19.7 km/h) and the time to exhaustion was 109.5 ± 29.8 s (CI95% = 92.3 − 126.7 s). The peak [La-] was 11.6±2.0 mmol/L (CI95% = 10.5 − 12.8 mmol/L), with Δ[La-] corresponding to 10.2±1.9 mmol/L (CI95% = 9.2 − 11.4 mmol/L), whereas the A1 and τ1 from the EPOCFAST were 21.3±2.4 mL/kg/min (CI95% = 20.0 − 22.7 mL/kg/min) and 1.00±0.13 min (CI95% = 0.92 − 1.08 min), respectively. Concerning the oxygen equivalents estimated from the glycolytic and phosphagen metabolic pathways during this test, the E[La-] corresponded to 2.29 ± 0.52 L (CI95% = 2.00 − 2.59 L) (30.8±5.7 mL/kg; CI95% = 27.5 − 34.1 mL/kg), whereas the EPCr was 1.58 ± 0.26 L (CI95% = 1.43 − 1.73 L) (21.2±2.5 mL/kg; CI95% = 19.8 − 22.7 mL/kg). Therefore, the absolute MAODALT corresponded to 3.87 ± 0.71 L (CI95% = 3.46 − 4.28 L) and MAODALT relative to body mass was 52.0 ± 6.8 mL/kg (CI95% = 48.0 − 55.9 mL/kg) (S1 Dataset).

Table 2 shows the coefficient of correlations between the 30-s ATR outputs and MAODALT. Absolute MAODALT was statistically moderately correlated with mean power (r = 0.58, CI95% = 0.08 − 0.85; P = 0.03) and total work (r = 0.57, CI95% = 0.06 − 0.85; P = 0.03), and strongly correlated with mean force (r = 0.79, CI95% = 0.45 − 0.93; P = 0.001), however no significant correlation for MAODALT was found when presented relative to body mass. In addition, the E[La-] was moderately correlated with mean power (r = 0.58, CI95% = 0.07 − 0.85; P = 0.03), but a weak and non-significant correlation was found between EPCr and peak power (r = 0.33, CI95% = -0.59 − 0.47; P = 0.25) and other outcomes.

Table 2. Coefficient of Correlation between the 30-s ATR outputs and MAODALT. Values in r (CI95%).

In addition, for the correlations between peak and mean outputs from the 30s- ATR, the MAODALT was also strongly correlated with force values at 5–10 s until 25–30 s (Fig 3) and moderately correlated with the power and velocity values at 15–20 s (Fig 4 and Fig 5, respectively), but not with distances covered (Fig 6). Force values at 5–10 s until 25–30 s were also strongly correlated with E[La-] (r = 0.53 to 0.63; p < 0.01) and EPCr (r = 0.60 to 0.74; P ≤ 0.025), while the power values at 5–10 s until 20–25 s were also moderately correlated with E[La-] (r = 0.54 to 0.62; P ≤ 0.049). However, there was no significant correlation between anaerobic energy estimation and values of velocity or distance covered.

Fig 3. Linear regression and coefficient of correlation between force measured each 5-s during the 30-s ATR with MAODALT.

Fig 4. Linear regression and coefficient of correlation between velocity measured each 5-s during the 30-s ATR with MAODALT.

Fig 5. Linear regression and coefficient of correlation between power measured each 5-s during the 30-s ATR with MAODALT.

Fig 6. Linear regression and coefficient of correlation between distances covered measured each 5-s during the 30-s ATR with MAODALT.


The main findings of this study were the MAODALT correlations with mean power, mean force and total work, and, principally, the correlations of MAODALT, EPCr and E[La-] with force values from the 5–10 s to 25-30s periods in the 30-s ATR and E[La-] with power values, confirming our initial hypothesis.

The conventional MAOD has been significantly correlated with 30-s Wingate test outputs [5]. However, the conventional MAOD is unable to distinguish both the glycolytic and phosphagen metabolic pathways in the same test, besides which the conventional MAOD requires a huge amount of time to assess the anaerobic capacity in a robust procedure without overestimating the energy demand during the supramaximal effort [9,40].

More recently Bertuzzi et al.[9] also described associations between MAODALT and 30-s Wingate test outputs. However, since these authors used the MAODALT method, they also reported significant correlations of the phosphagen and glycolytic metabolism pathways with peak power and mean power, respectively, for the first time. In our findings the EPCr was weak and non-significantly correlated with peak power (r = 0.33, CI95% = -0.59 − 0.47; P = 0.25). As the 30-s ATR was performed on a non-motorized treadmill and beginning with the treadmill belt stopped, the improvement and attainment of peak value for the force was faster than the response of velocity and power, therefore delaying the peak power value to near 10 seconds (see Fig 2A, 2B and 2C), instead the peak value occurred in the first seconds of exercise such as observed during the Wingate test. Mangine et al. [23] reported similar findings, with the peak velocity being attained at 7.22±3.77 s during a 30-s tethered running test. Considering that the phosphagen metabolism is predominantly activated during the first seconds of effort, the EPCr was mainly correlated with force values (force values at 5–10 s until 25–30 s; r = 0.60 to 0.74; P ≤ 0.025) and weakly correlated with power values, which were more correlated with E[La-]. The delayed response of power during the 30-s ATR is the main factor to explain the difference between the findings of our study and those of Bertuzzi et al. [14] concerning the association between EPCr and peak power during a 30-s all-out effort.

The current study is the first to investigate the associations between MAODALT and a 30-s all-out test in running. In addition, the assessment of power using a high frequency signal acquisition system to measure the horizontal force and velocity improves the quality of the mechanical work measurements during this test, which is a novelty of this study.

All studies that have compared anaerobic parameters with a 30-s Wingate test have used the mean power, peak power, fatigue index and total work as the main outputs [5,9]. The data from the present study reported correlations of MAODALT with mean power, mean force and total work, which are parameters that can be considered as the overall anaerobic metabolism [5,41]. All-out tethered running is considered a good test to assess the specific sprint-running anaerobic power [42], but the lack of significant correlations between MAODALT and peak power values can be explained also due to power not indicating capacity and consequently the peak power from the 30-s Wingate test (similar to the 30-s ATR) is not a good predictor of anaerobic capacity, as also reported by Minahan et al. [43]. Minahan et al. [43] demonstrated that there is no significant relationship between peak power from the 30-s Wingate anaerobic test and the conventional MAOD in cycling, similar to the findings of the present study (r = 0.38 for MAODALT in L and 0.13 for MAODALT relative to body mass; Table 2).

In a similar study, Andrade et al. [19] also reinforced these findings, reporting that power outputs from a running-based anaerobic sprint test (i.e., adaptation of the 30-s Wingate anaerobic test for running) are not correlated with conventional MAOD. On the other hand, the duration of the all-out test results in a high influence of anaerobic capacity on the total (work) and mean (force and power) mechanical parameters, as suggested by the significant correlations presented here.

A novelty of the current investigation is the strong and significant correlations of MAODALT, E[La-] and EPCr with force values in the course of time (Fig 3), and the correlation of E[La-] with power values from the 5–10 s to 20–25 s periods during the 30-s ATR. These correlations describe the importance of anaerobic capacity estimated through MAODALT and of the E[La-] and EPCr to produce high force over time during the test. Subjects with higher anaerobic capacity produce higher force values during almost the entire test, and the glycolytic metabolism has a moderate influence on power values. In addition, during a tethered running effort the force generation seems be higher than during a free-running effort such as a running-based anaerobic sprint test, explaining the significant correlation found in the current study in comparison to the study of Andrade et al. [19].

Moreover, several studies have reported that horizontal force during sprinting is the strongest predictor of acceleration [44] and short distance performance (i.e., 100-m) [45], highlighting the relationship between MAODALT and horizontal force outcomes found in the current study.

Limitations of study

A limitation of the MAODALT method which should be considered is the fact that the E[La-] could be underestimated as the lactate production is dependent on active body mass during effort and also a portion of the lactate produced by muscles can be oxidized during exercise. In addition, the EPOCFAST can also be affected by some factors such as caffeine, which can hasten the oxidative metabolism and decrease the time constant [46]. Moreover, a limitation of the present study is the fact that MAODALT was not compared with the conventional MAOD method; however, this was based on the findings of Bertuzzi et al. [14], Zagatto et al. [13] and Miyagi et al. [25], who reported the similarity between anaerobic estimated using the MAODALT and MAOD. In addition, in the current study we used a sample size of 14 runners, which is considered a satisfactory sample size based on a statistical power of 95%, however, this must also be considered as a limitation. Finally, further investigation of MAODALT using sprinters is recommended.


In conclusion, the absolute MAODALT was moderately associated with mean power and total work, and it was strongly associated with mean force from a 30-s all-out tethered running test, and, principally, with force behavior over time during the test, evidencing the importance of anaerobic capacity to maintain force over the course of time in short efforts.

Author Contributions

  1. Conceptualization: AMZ WEM.
  2. Data curation: AMZ WEM FS.
  3. Formal analysis: AMZ WEM FS CAG.
  4. Funding acquisition: AMZ CAG.
  5. Investigation: AMZ WEM FS CAG.
  6. Methodology: AMZ WEM FS CAG.
  7. Project administration: AMZ WEM.
  8. Resources: AMZ WEM FS CAG.
  9. Supervision: AMZ.
  10. Validation: AMZ WEM FS CAG.
  11. Visualization: AMZ WEM FS CAG.
  12. Writing – original draft: AMZ WEM FS CAG.
  13. Writing – review & editing: AMZ WEM FS CAG.


  1. 1. Lima MC, Ribeiro LF, Papoti M, Santiago PR, Cunha SA, Martins LE, et al. (2011) A semi-tethered test for power assessment in running. International Journal of Sports Medicine 32: 529–534. pmid:21563027
  2. 2. Noordhof DA, de Koning JJ, Foster C (2010) The maximal accumulated oxygen deficit method: a valid and reliable measure of anaerobic capacity? Sports Medicine 40: 285–302. pmid:20364874
  3. 3. Zagatto A, Redkva P, Loures J, Kalva Filho C, Franco V, Kaminagakura E, et al. (2011) Anaerobic contribution during maximal anaerobic running test: correlation with maximal accumulated oxygen deficit. Scandinavian Journal of Medicine & Science in Sports 21: e222–230.
  4. 4. Medbo JI, Mohn AC, Tabata I, Bahr R, Vaage O, Sejersted OM (1988) Anaerobic capacity determined by maximal accumulated O2 deficit. Journal of Applied Physiology 64: 50–60. pmid:3356666
  5. 5. Scott CB, Roby FB, Lohman TG, Bunt JC (1991) The maximally accumulated oxygen deficit as an indicator of anaerobic capacity. Medicine and Science in Sports and Exercise 23: 618–624. pmid:2072841
  6. 6. Margaria R, Edwards HT, Dill DB (1933) The possible mechanisms of contracting and paying the oxygen debt and the role of lactic acid in muscular contraction. The American Journal of Physiology 106: 689–715.
  7. 7. di Prampero PE, Ferretti G (1999) The energetics of anaerobic muscle metabolism: a reappraisal of older and recent concepts. Respiration Physiology 118: 103–115. pmid:10647856
  8. 8. di Prampero PE (1981) Energetics of muscular exercise. Reviews of Physiology, Biochemistry and Pharmacology 89: 143–222. pmid:7015457
  9. 9. Bertuzzi R, Kiss MA, Damasceno M, Oliveira RS, Lima-Silva AE (2015) Association between anaerobic components of the maximal accumulated oxygen deficit and 30-second Wingate test. Brazilian Journal of Medical and Biological Research 48: 261–266. pmid:25627804
  10. 10. Brisola GP, Miyagi WE, da Silva H, Zagatto AM (2015) Sodium bicarbonate supplementation improved MAOD but is not correlated with 200 and 400m running performances: a double blind, crossover and placebo controlled study. Applied Physiology, Nutrition and Metabolism 40: 931–937.
  11. 11. Zagatto AM, Gobatto CA (2012) Relationship between anaerobic parameters provided from MAOD and critical power model in specific table tennis test. International Journal of Sports Medicine 33: 613–620. pmid:22562729
  12. 12. Milioni F, Malta ES, Rocha LGSA, Mesquita CAA, Freitas EC, Zagatto AM (2016) Acute administration of high doses of taurine does not substantially improve high-intensity running performance and the effect on maximal accumulated oxygen deficit is unclear. Applied Physiology, Nutrition and Metabolism 41: 498–503.
  13. 13. Zagatto AM, Bertuzzi R, Miyagi WE, Padulo J, Papoti M (2016) MAOD determined in a single supramaximal test: a study on the reliability and effects of supramaximal intensities. International Journal of Sports Medicine 37: 700–707. pmid:27176893
  14. 14. Bertuzzi RCM, Franchini E, Ugrinowitsch C, Kokubun E, Lima-Silva AE, Pires FO, et al. (2010) Predicting MAOD using only a supramaximal exhaustive test. International Journal of Sports Medicine 31: 477–481. pmid:20432195
  15. 15. Zagatto AM, Nakamura FY, Milioni F, Miyagi WE, Padulo J, Bragazzi NL, et al. (2017) The sensitivity of the alternative maximal accumulated oxygen deficit method to discriminate training status. Journal of Sports Sciences in press.
  16. 16. Zagatto AM, Beck WR, Gobatto CA (2009) Validity of the Running Anaerobic Sprint Test for Assessing Anaerobic Power and Predicting Short-Distance Performances. Journal of Strength and Conditioning Research 23: 1820–1827. pmid:19675478
  17. 17. Bar-Or O (1987) The Wingate anaerobic test. An update on methodology, reliability and validity. Sports Medicine 4: 381–394. pmid:3324256
  18. 18. Bogdanis GC, Nevill ME, Boobis LH, Lakomy HK (1996) Contribution of phosphocreatine and aerobic metabolism to energy supply during repeated sprint exercise. Journal of Applied Physiology 80: 876–884. pmid:8964751
  19. 19. Andrade VL, Zagatto AM, Kalva CA, Mendes OC, Gobatto CA, Campos EZ, et al. (2015) Running-based Anaerobic Sprint Test as a Procedure to Evaluate Anaerobic Power. International Journal of Sports Medicine 36: 1156–1162. pmid:26422055
  20. 20. Cheetham ME, Williams C, Lakomy HK (1985) A laboratory running test: metabolic responses of sprint and endurance trained athletes. British Journal of Sports Medicine 19: 81–84. pmid:4027498
  21. 21. Pereira VH, Gama MCT, Sousa FAB, Lewis TG, Gobatto CA, Manchado—Gobatto FB (2015) Complex network models reveal correlations among network metrics, exercise intensity and role of body changes in the fatigue process. Scientific Reports 5: 10489. pmid:25994386
  22. 22. Morin JB, Samozino P, Bonnefoy R, Edouard P, Belli A (2010) Direct measurement of power during one single sprint on treadmill. Journal of Biomechanics 43: 1970–1975. pmid:20541762
  23. 23. Mangine GT, Hoffman JR, Gonzalez AM, Wells AJ, Townsend JR, Jajtner AR, et al. (2014) Speed, force, and power values produced from nonmotorized treadmill test are related to sprinting performance. Journal of Strength and Conditioning Research 28: 1812–1819. pmid:24950225
  24. 24. de Poli R, Miyagi WE, Nakamura FY, Zagatto AM (2016) Caffeine improved time to exhaustion, but did not change alternative maximal accumulated oxygen deficit estimated during a single supramaximal running bout. International Journal of Sport Nutrition and Exercise Metabolism 26: 549–557. pmid:27096623
  25. 25. Miyagi WE, de Poli RAB, Papoti M, Bertuzzi R, Zagatto AM (2017) Anaerobic capacity estimated in a single supramaximal test in cycling: validity and reliability analysis. Scientific Reports.
  26. 26. Padulo J, Chamari K, Ardigò LP (2014) Walking and running on treadmill: the standard criteria for kinematics studies. Muscles, Ligaments and Tendons Journal 4: 159–162. pmid:25332929
  27. 27. Jones AM, Doust JH (1996) A 1% treadmill grade most accurately reflects the energetic cost of outdoor running. Journal of Sports Sciences 14: 321–327. pmid:8887211
  28. 28. Gama MCT, Sousa FAB, Reis IGM, Gobatto CA (2016) Reliability of the all-out three minutes test for non-motorized treadmill tethered running. International Journal of Sports Medicine In Press.
  29. 29. Ozyener F, Rossiter HB, Ward SA, Whipp BJ (2001) Influence of exercise intensity on the on- and off-transient kinetics of pulmonary oxygen uptake in humans. The Journal of Physiology 533: 891–902. pmid:11410644
  30. 30. Howley ET, Bassett DR Jr., Welch HG (1995) Criteria for maximal oxygen uptake: review and commentary. Medicine and Science in Sports and Exercise 27: 1292–1301. pmid:8531628
  31. 31. Borg GA (1982) Psychophysical bases of perceived exertion. Medicine and Science in Sports and Exercise 14: 377–381. pmid:7154893
  32. 32. Tanaka H, Monahan KD, Seals DR (2001) Age-predicted maximal heart rate revisited. J Am Coll Cardiol 37: 153–156. pmid:11153730
  33. 33. Billat VL, Blondel N, Berthoin S (1999) Determination of the velocity associated with the longest time to exhaustion at maximal oxygen uptake. European Journal of Applied Physiology 80: 159–161.
  34. 34. Kuipers H, Verstappen FT, Keizer HA, Geurten P, van KG (1985) Variability of aerobic performance in the laboratory and its physiologic correlates. International Journal of Sports Medicine 6: 197–201. pmid:4044103
  35. 35. Sousa FAB, dos Reis IGM, Ribeiro LFP, Martins LEB, Gobatto CA (2015) All-Out Loaded Running: Field Measurements of Kinetic, Kinematic and Metabolic Variables During Whole 30 Seconds. 62th ACSM Annual Meeting. San Diego: Medicine and Science in Sports and Exercise. pp. 12–13.
  36. 36. Fitzsimons M, Dawson B, Ward D, Wilkinson A (1993) Cycling and running tests of repeated sprint ability. Australian Journal of Science and Medicine in Sport 25: 82–87.
  37. 37. Zagatto A, Papoti M, Leite JVM, Beneke R (2016) Energetics of table tennis and table tennis specific exercise testing. International Journal of Sports Physiology and Performance 11: 1012–1017. pmid:26869146
  38. 38. Milioni F, Zagatto AM, Barbieri RA, de Andrade VL, sos-Santos JW, Gobatto CA, et al. (2017) Energy systems contribution in the running-based anaerobic sprint test. International Journal of Sports Medicine In press.
  39. 39. Rowntree D (2000) Statistics without tears. An introduction for non-mathematicians. London: Penguin. 208 p.
  40. 40. Bangsbo J (1996) Oxygen deficit: a measure of the anaerobic energy production during intense exercise? Canadian Journal of Applied Physiology 21: 350–363; discussion 364–359. pmid:8905187
  41. 41. Vandewalle H, Peres G, Heller J, Monod H (1985) All out anaerobic capacity tests on cycle ergometers. A comparative study on men and women. European Journal of Applied Physiology and Occupational Physiology 54: 222–229. pmid:4043052
  42. 42. Zemková E, Hamar D (2004) "All-Out" tethered running as an alternative to wingate anaerobic test. Kinesiology 36: 165–172.
  43. 43. Minahan C, Chia M, Inbar O (2007) Does power indicate capacity? 30-s Wingate anaerobic test vs. maximal accumulated O2 deficit. International Journal of Sports Medicine 28: 836–843. pmid:17497577
  44. 44. Morin JB, Gimenez P, Edouard P, Arnal P, Jimenez-Reyes P, Samozino P, et al. (2015) Sprint Acceleration Mechanics: The Major Role of Hamstrings in Horizontal Force Production. Frontiers in Physiology 6: 404. pmid:26733889
  45. 45. Morin JB, Bourdin M, Edouard P, Peyrot N, Samozino P, Lacour JR (2012) Mechanical determinants of 100-m sprint running performance. Eur J Appl Physiol 112: 3921–3930. pmid:22422028
  46. 46. Astorino TA, Martin BJ, Wong K, Schachtsiek L (2011) Effect of acute caffeine ingestion on EPOC after intense resistance training. The Journal of Sports Medicine and Physical Fitness 51: 11–17. pmid:21297558