Overestimation of maximal aerobic speed by the Université de Montréal track test and a 1500-m-time trial in soccer

Introduction: Maximal aerobic speed (MAS), usually measured by cardiopulmonary exercise testing (CPET) on a treadmill, is gaining popularity in soccer to determine aerobic performance. Several field tests are used to estimate MAS, although, gold standard methods are still not clarified. Therefore, this work aims 1) to compare two different CPET based methods to assess MAS and 2) to investigate the convergent validity of two common field tests to estimate MAS in soccer.

Methods: Thirteen trained male soccer players completed an CPET on a treadmill to determine two VO₂-kinetic based definitions of MAS (MAS_Plateau = speed at onset of VO₂-plateau = gold standard; MAS_30s = first speed of 30-s-interval of VO₂max), the Université de Montreal Track Test (UMTT; V_UMTT = speed of the last stage), and a 1500-m-time trial (1500-m-TT; V_1500m = average speed). MAS_Plateau, MAS_30s, V_UMTT, and V_1500m were compared using ANOVA. Additionally, limits of agreement analysis (LoA), Pearson’s r, and ICC were calculated between tests.

Results: MAS_30s, V_UMTT, and V_1500m significantly overestimated MAS_Plateau by 0.99 km/h (ES = 1.61; p < 0.01), 1.61 km/h (ES = 2.03; p < 0.01) and 1.68 km/h (ES = 1.77; p < 0.01), respectively, with large LoA (-0.21 ≤ LoA≤3.55), however with large-to-very large correlations (0.65 ≤ r ≤ 0.87; p ≤ 0.02; 0.51 ≤ ICC≤ 0.85; p ≤ 0.03).

Discussion: The overestimation and large LoA of MAS_Plateau by all estimates indicate that 1) a uniform definition of MAS is needed and 2) the UMTT and a 1500-m-TT seem questionable for estimating MAS for trained soccer players on an individual basis, while regression equations might be suitable on a team level. The results of the present work contribute to the clarification of acquisition of MAS in soccer.

Introduction

Given the high cardiorespiratory demands during a soccer match, in which professional players cover a distance up to 13 km, assessment of endurance performance with subsequent individual training prescription seems indispensable (Tanner and Gore, 2012; Altmann et al., 2020). Aerobic performance is often assessed by measuring the maximum oxygen uptake (VO₂max). In soccer, VO₂max is significantly related to the distance covered during a match and reflects aerobic capacity (Bangsbo et al., 1991; Aquino et al., 2020). The VO₂max is commonly assessed by cardiopulmonary exercise testing (CPET) on a treadmill with incremental protocols (Kuipers et al., 2003; Riboli et al., 2021). A criterion for obtaining the true VO₂max in such tests is the occurrence of a VO₂-plateau which is defined by a lower increase in VO₂ than 150 ml/min in at least the last minute of an incremental exercise (Meyer and Kindermann, 1999). Then, VO₂max is defined as the maximal 30-s-interval of VO₂ during an incremental CPET usually occurring at the termination of the test due to exhaustion. However, while being mainly an aerobic marker, VO₂max is reached with efforts above the onset of the plateau associated with a higher input of anaerobic resources (Billat and Koralsztein, 1996). Therefore, the way VO₂max is commonly measured, it incorporates not only aerobic but to some extent also anaerobic resources. Importantly, the anaerobic contribution can largely differ between athletes. This leads to different lengths of the VO₂-plateau until exhaustion is reached, thereby distinguishing between athletes depending on their utilization of anaerobic resources. More specifically, athletes mainly relying on aerobic resources show a short VO₂-plateau, whereby athletes using a greater amount of anaerobic resources display a longer plateau (Petot et al., 2012). As the velocity associated with the 30-s-interval of VO₂max is commonly used for prescribing training intensities, it might trigger the aerobic and anaerobic energy pathways to different extents depending on the physiological profile of the respective athlete possibly leading to a non-optimal training adaptation. A parameter that addresses the mentioned shortcomings of VO₂max is the maximal aerobic speed (MAS) which has recently gained popularity in scientific literature and practice. The MAS was firstly described by Di Prampero et al. (1986) as the minimum speed at which VO₂-consumption stops increasing despite a further increase in load, i.e., the onset of the VO₂-plateau, in the current study referred to as MAS_Plateau. Based on MAS_Plateau, training intensities aiming to address mainly aerobic resources to the same extent for different athletes can be set. CPET on a treadmill is used as a gold standard method to assess MAS. Nevertheless, different treadmill protocols and definitions of MAS exist, which also provide different results (Berthoin et al., 1996; Billat et al., 1996; Riboli et al., 2021). Besides MAS_Plateau, the velocity of the 30-s-interval of VO₂max (MAS_30s) is often applied as an alternative method to assess MAS (Buchheit, 2008; Sandford et al., 2019). However, to date, no studies compared the currently most common definitions based on examination of VO₂-kinetics, i.e., first velocity at onset of VO₂-plateau (MAS_Plateau) and the first velocity of 30-s-interval of VO₂max (MAS_30s).

Despite ambiguities in the gold standard method, simplified methods in the field are used to estimate MAS, such as incremental continuous field tests like Université de Montréal Track Test (UMTT) or different set time and distance trials (TT) (Léger and Boucher, 1980; Léger et al., 1988; Bangsbo et al., 2008; Clarke et al., 2016; Sandford et al., 2019). In terms of the validity of the UMTT, Berthoin et al. (1996) and Souza et al. (2014) could not find any significant differences between MAS and V_UMTT, whereas Lacour et al. (1991) revealed an overestimation of MAS by V_UMTT. Regarding set distance time trials to assess MAS, the current literature also reveals conflicting results. Set distance TT yielded similar results (Souza et al., 2014; Bellenger et al., 2015; Lundquist et al., 2021) or overestimated MAS and V_UMTT (Sandford et al., 2019; Darendeli et al., 2021). Due to contrary results in the current literature on field tests to estimate MAS, Buchheit (2010) proposed to distinguish the results obtained from CPET, from those obtained from field tests by designating the values obtained from CPET as MAS and the estimates from a field test as V_Test. This reinforces the importance of reporting exact definitions and methods. Furthermore, most of the above-mentioned studies were conducted with runners and sports students, which does not allow for a clear conclusion about soccer.

To address these shortcomings, the aims of this study were 1) to compare two different VO2-kinetic based methods, i.e., first velocity at onset of VO₂-plateau (MAS_Plateau) and first velocity of 30-s-interval of VO₂max (MAS_30s), using CPET on a treadmill, and 2) to investigate convergent validity of both the UMTT and a 1500-m-TT in relation to a VO₂-kinetic based MAS, i.e. MAS_Plateau, in soccer. Thus, this work contributes to clarify the implementation of the gold standard method for assessing MAS in soccer and whether the assessment can be simplified by the UMTT or a 1500-m-TT.

Materials and methods

Study design

Thirteen trained male soccer players performed three tests at three different occasions, with a minimum of seven and a maximum of 21 days between the tests and a training rest of at least 24 h before each test. Tests were conducted in the same order for all participants: 1) UMTT on a 400-m-running track, 2) CPET on a treadmill, and 3) a 1500-m-TT on a 400-m-running track. During the incremental treadmill test, MAS_Plateau [km/h] and MAS_30s [km/h] were determined by examining the VO₂-kinetics. Moreover, the main parameters measured during field testing were: V_UMTT [km/h], V_1500m [km/h], and V_calc [km/h]. MAS_30s, V_UMTT, V_1500m, and V_calc were compared to MAS_Plateau which is considered as the gold standard method in the current study.

Sample

The sample consisted of n = 13 trained male soccer players classified as tier two athletes (Mckay et al., 2022) (mean ± SD: age: 25.38 ± 2.75 years; height: 178.51 ± 7.82 cm; weight: 78.60 ± 8.85 kg; fat mass proportion: 16.86 ± 4.78%; VO₂max: 49.92 ± 3.15 ml/kg/min; exercise frequency: 4.50 ± 0.50 times/week; soccer experience: 21.67 ± 3.40 years). Players’ health was checked and confirmed by the Physical Activity Readiness-Questionnaire (Tremblay et al., 2012). Each subject was informed about the study procedure and possible risks and agreed to participate by signing a consent form. As per the local legislation, this study was exempt from full ethics review by the institutional review board, due to this being an anonymous study containing anonymous data. To avoid bias, goal keepers were excluded from this study (Altmann et al., 2020).

Variables and procedures

Université de Montréal track test

The UMTT was conducted on a 400-m-tartan track. Large cones were placed at 50-m-intervals, small cones after the first 33.33 m and at 100-m-intervals. The speed was controlled by an acoustic signal at which the cones had to be reached. The initial speed was set at 10 km/h and every 2 min the speed was increased by 1 km/h (Berthoin et al., 1996; Billat and Koralsztein, 1996; Bellenger et al., 2015; Darendeli et al., 2021). Each subject was equipped with a previously validated chest strap (H7 or H10, Polar Electro, Kempele, Finland) for monitoring HR (Speer et al., 2020; Hernández-Vicente et al., 2021). The test was completed as soon as the subject was no longer able to reach the specified cone at the acoustic signal. V_UMTT was determined as the speed of the last stage. If the last stage had not been finished, V_UMTT was calculated using the following formula: V_UMTT = speed of the last completed stage [km/h]+time in last stage [s]/120 s (Berthoin et al., 1996). In addition, the HRmax_UMTT and RPE_UMTT were recorded after the end of the test to assess physical exhaustion.

Cardiopulmonary exercise testing

To assess MAS_Plateau and MAS_30s, CPET on a treadmill with ±0.1 km/h speed accuracy was performed (Woodway PPSmed 55 and PPSmed L70; WOODWAY GmbH; Weil am Rhein; Germany). The test protocol started at 6 km/h and increased every 3 min by 2 km/h with a treadmill incline of 1% to reflect the energy expenditure of outdoor running (Jones and Doust, 1996). Between each stage, the subject rested for 0.5 min and the test got terminated by the subject due to voluntary exhaustion (Dickhuth and Badtke, 2007). Breath-by-breath ventilatory data were obtained using the Metalyzer 3B spirometer and the appropriate MetaSoft three software (Cortex Biophysik GmbH; Leipzig; Germany) with which the data was prepared as 15-s moving average values for further analysis. This technology enables accurate and precise determination of the individual VO₂-kinetics (Vogler et al., 2010). Gas sensors were calibrated using gases of known concentrations (15% O₂, 5% CO₂), and the turbine volume transducer was calibrated using a 3-l syringe (Cortex Biophysik GmbH; Leipzig; Germany).

The VO₂-data were first examined for a plateau which is defined as a lower increase in VO₂ than 150 ml/min in at least the last minute of exercise (Meyer and Kindermann, 1999). The MAS_Plateau represents the first velocity when reaching this plateau (Billat and Koralsztein, 1996). Additionally, the velocity at the onset of the 30-s-interval of VO₂max (MAS_30s) was determined, as this is another common definition for the determination of MAS (Buchheit, 2008; Sandford et al., 2019). The VO₂max was defined as the highest 30-s-interval of VO₂. The RER_end represented the highest value of the quotient VCO₂/VO₂ during the end of exercise. The HRmax was assessed using a chest strap (H7 or H10; Polar Electro; Kempele; Finland). In addition, RPE was queried after test termination. Immediately after the test, 20 μl of capillary blood was collected from the right earlobe and analyzed by the BIOSEN C-Line lactate analyzer (EKF Diagnostic; Barleben; Germany) to assess the maximal lactate value reached during the treadmill test (La_end). In order to achieve physical exhaustion and thus VO₂max, the collected data were analyzed for the following exercise criteria, of which at least two had to be fulfilled (Neumann, 2013): RER_end ≥ 1.0 (Dickhuth and Kindermann, 2002); RPE ≥17 (Sangan et al., 2021); HRmax ≥210-age, La_end ≥ 8 mmol/L, and reaching a VO₂-plateau (Marées and Heck, 2003).

1500-m-time trial

To ensure reliability of the 1500-m-TT, subjects performed a habituation session 1 week in advance (Clarke et al., 2016). For HR measurement, each subject received a chest strap (H7 or H10; Polar Electro; Kempele; Finland). The subjects ran on a 400-m tartan track and performed a warm-up (at least 400 m jogging; 100 m easy acceleration runs; 3 min stretching) right before the start of the TT. During the TT, subjects were instructed to keep their speed as even as possible. The time to complete the 1,500 m was measured with a stopwatch, from which the average speed in km/h (V_1500m) was determined (Darendeli et al., 2021). In addition, the regression equation of Bellenger et al. (2015) was used to calculate an approximation to the true MAS (V_calc = V_1500m*(0.766 + 0.117*1.5 km)). HRmax_1500m and RPE_1500m were recorded after test termination to ensure physical exhaustion.

Statistical analysis

Statistical analysis and creation of graphics were carried out with the statistical software IBM SPSS^© Statistics (version 27). To detect possible differences between the parameters MAS_Plateau/V_UMTT/V_1500m/V_calc, HRmax/HRmax_UMTT/HRmax_1500m, and RPE/RPE_UMTT/RPE_1500m, ANOVA with repeated measures and Bonferroni post-hoc tests were calculated. In addition, t-tests for dependent samples were used for the comparison of MAS_Plateau vs. MAS_30s, and MAS_Plateau vs. V_calc. The effect sizes of the ANOVA results were estimated by partial eta²: 0.01≤η_p²<0.06 is considered a small, 0.06≤η_p²<0.14 as a medium, and 0.14≥η_p² as a large effect (Cohen, 1988). The effect sizes (ES) of the t-tests and post-hoc tests were calculated using Cohen’s d: 0.2 ≤ ES < 0.5 represent small, 0.5 ≤ ES < 0.8 medium, and ES ≥ 0.8 represent large effects (Cohen, 1988). Absolute agreement between MAS_Plateau, V_UMTT, and V_1500m and between MAS_Plateau and MAS_30s, and MAS_Plateau and V_calc was determined with the limits-of-agreement analysis (LoA analysis) and Bland-Altman plots (Altman and Bland, 1983). In addition, Pearson’s correlation coefficient r and the intraclass correlation coefficient (ICC 3.1) were calculated. According to Hopkins (2004), the magnitude of the correlation was considered to be small (0.1 ≤ r/ICC<0.3), medium (0.3 ≤ r/ICC<0.5), large (0.5 ≤ r/ICC<0.7), very large (0.7 ≤ r/ICC<0.9), and almost perfect (r/ICC≥0.9) classifications. The significance level for all calculations was set at p < 0.05.

Results

Each subject met three or more of the specified criteria, so that physical exhaustion was ensured. The mean values and standard deviations of the recorded parameters for the incremental treadmill test, UMTT and the 1500-m-TT are shown in Table 1. Moreover, individual progressions of MAS_Plateau/MAS_30s, MAS_Plateau/V_UMTT/V_1500m, and MAS_Plateau/V_calc are visualized as spaghetti plots in Figure 1. These descriptive results already indicate an overestimation of MAS_Plateau by the estimations, i.e., MAS_30s, V_UMTT, V_1500m, and V_calc.

TABLE 1

TABLE 1. Descriptive results for the CPET on the treadmill, UMTT, and 1500-m-TT. Results are presented as mean values ±SD.

FIGURE 1

FIGURE 1. Spaghetti plots for intra- and interindividual comparison of (A) MAS_Plateau and MAS_30s; (B) MAS_Plateau, V_UMTT, and V_1500m; and (C) MAS_Plateau and V_calc.

The comparison of both VO₂-kinetic based methods to assess MAS resulting in the parameters MAS_Plateau and MAS_30s (see Table 2) shows a significant increase by 0.99 km/h (p < 0.01) with a large effect (ES = 1.61) and Limits of Agreement (LoA) ranging from -0.21–2.20 km/h (see Figure 2). Though, results of correlation analysis show very large correlations between MAS_Plateau and MAS_30s (r = 0.87; ICC = 0.85; see Table 2).

TABLE 2

TABLE 2. Results of ANOVA, Bonferroni post-hoc tests, t-tests, and correlation analysis.

FIGURE 2

FIGURE 2. Bland-Altman plots for limits-of-agreement analysis (LoA analysis) between (A) MAS_Plateau and MAS_30s; (B) MAS_Plateau and V_UMTT; (C) MAS_Plateau andV_1500m; (D) V_UMTT and V_1500m; and (E) MAS_Plateau and V_calc. The solid lines represent the mean difference, the dashed lines represent the limits of agreement (±1.96 SD).

Moreover, V_UMTT and V_1500m overestimate MAS_Plateau by 1.61 km/h (p < 0.01; ES = 2.03) and 1.68 km/h (p < 0.01; ES = 1.77), respectively. Between V_UMTT and V_1500m, no significant difference (p = 0.99; ES = 0.14) was found. The LoA between V_UMTT and V_1500m range from -0.8–1.01 km/h, between MAS_Plateau and V_UMTT from 0.05 to 3.17 km/h, and between MAS_Plateau and V_1500m from -0.18–3.55 km/h. The correlations between the three velocities are large to very large (0.65 ≤ r ≤ 0.79; p ≤ 0.02; 0.51 ≤ ICC≤0.72; p ≤ 0.03). The comparison of MAS_Plateau and V_calc shows a significant difference (MD = 0.67 km/h; p = 0.03; ES = 0.70). In addition, the LoA between MAS_Plateau and V_calc range from -1.21–2.55 km/h. There is a medium to large correlation between MAS_Plateau and V_calc (r = 0.65; p = 0.02; ICC = 0.40; p = 0.04).

Discussion

Main findings

The first aim of this study was to compare two different VO₂-kinetic based methods to determine MAS in soccer players, i.e., MAS_Plateau and MAS_30s, using CPET on a treadmill. MAS_Plateau was consistently overestimated by MAS_30s, nevertheless, MAS_Plateau and MAS_30s were highly correlated.

The second aim was to investigate the convergent validity of the UMTT and a 1500-m-TT to estimate MAS_Plateau. MAS_Plateau was overestimated by both V_UMTT and V_1500m, nonetheless, large to very large correlations with MAS_Plateau were found. Further, the calculated speed from the 1500-m-TT according to Bellenger et al. (2015), V_calc, was significantly higher than MAS_Plateau.

Discussion of MAS assessment via CPET

The results of the CPET to determine MAS illustrate the difference between two of the common definitions of MAS. Since VO₂max in healthy subjects almost always occurs before the end of an physical exhaustion exercise and a VO₂-plateau by definition lasts at least 1 minute (Meyer and Kindermann, 1999), a significant difference between MAS_Plateau and MAS_30s was expected. The mean difference of 0.99 km/h indicates that after reaching MAS_Plateau, subjects maintained their performance for an average of almost 1.5 min with a higher proportion of anaerobic resources until MAS_30s was reached (Buchheit, 2010). Because MAS_Plateau represents the first velocity when reaching a VO₂-plateau (Di Prampero et al., 1986) and therefore reflects the maximal speed with mainly aerobic resources, efforts above the onset of the plateau are associated with a higher input of anaerobic resources. Hence, velocities above the onset of a VO₂-plateau should not be attributed as a MAS. The very large effect size illustrates the practical relevance of this difference and the very large correlation between the two velocities supports the consistent overestimation of MAS_Plateau. Therefore, MAS should be determined individually based on VO₂-kinetics by investigating the plateau. In addition, these results suggest that studies that used V_max (Berthoin et al., 1996) or MAS_30s (Sandford et al., 2019) to validate field testing procedures, probably did not use the “true” MAS determined by CPET with examining the onset of the VO₂-plateau as a gold standard, which may have biased the results.

Discussion of UMTT and 1500-m-TT

The LoA between MAS_Plateau and V_UMTT indicate a wide dispersion of individual differences. Moreover, the significant overestimation found in this study is similar to the results of Lacour et al. (1991) who also reported a higher V_UMTT than MAS (+0.25 ± 0.07 km/h, p = 0.03) and a nearly perfect correlation (r = 0.92; p < 0.01) in a group of runners despite using a different protocol and a different definition for MAS. In contrast, Berthoin et al. (1996) and Souza et al. (2014) did not find differences between MAS and V_UMTT, but also used different protocols and definitions of MAS. Berthoin et al. (1996) determined the velocity of the last stage for both MAS (assessed by CPET on a treadmill) and V_UMTT, which means that they did not distinguish between MAS and V_max. On the contrary, in the present study, V_UMTT was compared to MAS_Plateau, which represents the first velocity of the VO₂-plateau. The UMTT represents an incremental test similar to CPET on a treadmill and because the final speed achieved during the UMTT is used as V_UMTT the significant difference to MAS_Plateau assessed as the onset of a VO₂-plateau can be explained.

Additionally, V_1500m shows a systematic overestimation of MAS_Plateau. Nevertheless, both the relatively large LoA and the large 95% CI of the mean difference indicate interindividual discrepancies in the differences between MAS_Plateau and V_1500m. Sandford et al. (2019) also detected an overestimation of MAS by V_1500m. The overestimation could be explained by the assumption that the distance for the total sample may have been too short to include only aerobic resources, but additionally anaerobic resources to run the 1,500 m in the best possible time. The fact that for some players the V_1500m was considerably closer to the MAS_Plateau than for others could indicate a heterogeneous character of the endurance performance of the sample. This may be due to the non-professional level of the sample on the one hand and on the other hand to position-specific differences. Different endurance profiles related to the player position could already be demonstrated in part (Altmann et al., 2020). Therefore, different distances should be used when implementing TT to estimate MAS_Plateau depending on the endurance performance level.

To address this issue, Bellenger et al. (2015) propose a regression equation (V_calc) to estimate MAS by set distance TT with distances between 1,600 m and 2,200 m. The comparison of MAS_Plateau and V_calc shows similar results as the comparison of MAS_Plateau and V_1500m. In this sense, V_calc also overestimates MAS_Plateau. If individual variations are considered, it is plausible that, as with V_1500m, the dispersion around the mean difference is very large. This was to be expected, since V_calc is calculated from V_1500m. The individual differences were merely shifted downward, so that they scatter both to the positive and to the negative. However, it should be noted that the regression equation used to calculate V_calc was set up by Bellenger et al. (2015) using V_UMTT as reference. This could additionally explain the overestimation of the MAS_Plateau in this study.

Moreover, the comparison of the two velocities V_1500m and V_UMTT achieved during the field test have the lowest mean difference and narrowest range of variation, as well as a very large correlation. Both Bellenger et al. (2015) and Lundquist et al. (2021) found high to very high levels of agreement between V_1400m–V_2000m and V_UMTT in male and female Australian Rules Football players. This also indicates a similar intensity of the two test procedures for team sports athletes.

Delimitations and limitations

The gold standard method to assess MAS has not yet been clarified, in particular it is unclear which treadmill protocol leads to the “true” MAS, especially in soccer. A major delimitation of our study is that we used a protocol with a 0.5 min break between the stages, which commonly serves to measure lactate via capillary blood between the stages of an incremental treadmill test. When analysing the individual VO₂-kinetics, we determined that the break between the stages is a major limitation. This pause probably allowed a short recovery, so that VO₂ progression delayed, especially at higher speeds at the beginning of a stage. This influences individual determination of MAS based on the VO₂-kinetics and possibly postpones physical exhaustion and thus reaching VO₂max (Metaxas et al., 2005). As a further delimitation, different environmental conditions may have influenced performance during the different test procedures. For example, some players completed the incremental treadmill test in the morning or at noon, with the UMTT and 1500-m-TT occurring in the evening for all subjects. Changes in performance at different times of the day have already been confirmed (Chtourou and Souissi, 2012). A limitation of our study is that the field tests were performed in different groups while the treadmill test was performed individually. This might have induced different levels of motivation in the subjects at the test time points. A last point to consider is the relatively heterogeneous aerobic endurance performance of the subjects. The MAS_Plateau of the sample shows a range of 13.23–17.18 km/h. Due to heterogeneous performance, the use of a TT with the same distance for all subjects is questionable. However, a habituation session was performed for improvement of independent speed control during the 1500-m-TT.

Future research

In order to interpret and compare different study results, it is important to use a consistent gold standard method for the assessment of MAS. Since different definitions are used to determine MAS, future research is necessary to clearly delineate MAS_Plateau, MAS_30s and V_max. Because previous studies on the validity of field test procedures have not been conducted with a uniform gold standard method and because MAS determination via an incremental treadmill test claims many resources, further investigation of the validity of existing field test procedures or the development of new test procedures is essential. Especially in team sports and its divergent endurance performance levels, there is a great potential for research in this regard. Regarding a TT, e.g., a classification of players into different endurance profiles based on norm values of MAS or by different expressions of anaerobic speed reserve (Sandford et al., 2021) and the assignment of these levels to appropriate distances to estimate MAS should be investigated in the future. Thus, a more accurate estimate of MAS using a TT would be possible. Though, the sample consisted of trained soccer players, the results can not directly be transferred to professional soccer. Therefore, more research regarding the assessment of MAS is required with professional soccer players.

In addition, technological evolutions may simplify MAS estimation in the future. On the one hand, global positioning systems could make it easier and presumably more accurate to record velocities in field tests, and on the other hand, algorithms could be developed and validated that estimate the current MAS based on certain physiological parameters - at best during training - and indicate any acute adjustments (Leser et al., 2011). Given the tight schedules of soccer players and coaches, integrating physiological diagnostics into the usual training could lead to a more efficient time schedules of players and coaches.

Practical applications

The UMTT and 1500-m-TT do not appear to be valid and thus less appropriate methods for estimating MAS for male soccer players. The LoA for both, UMTT and 1500-m-TT, indicate the deviations from MAS are higher than typical improvements of MAS achieved through specific training programs (Denadai et al., 2006; González-Mohíno et al., 2016). Therefore, training based on MAS estimations via UMTT or a TT might lead to much higher intensities than expected when using the true MAS, probably resulting in less improvements in performance, overload, or even a higher risk of injuries. For this purpose, it is recommended to either set up regression equations using a consistent gold standard method for estimating MAS using the V_UMTT or V_1500m or to choose individual distances for TT adjusted to the endurance performance level. Moreover, adapted training programs are possible, when the individual intensity of V_UMTT or V_1500m in deviation to MAS is known.

Conclusion

To conclude, our results indicate that different definitions of MAS lead to different results and that estimates by field tests are non-appropriate methods to determine MAS in trained soccer players. Conversely, using such methods may result in researchers and practitioners using too high intensities. This indicates the necessity of MAS-assessment by investigating VO₂-kinetics and examining the onset of the VO₂-plateau or the use of adjusted or new field tests to estimate MAS. This work provides the first evidence on the validity of MAS estimation of different field tests in soccer players. To improve MAS estimation in field tests, further valid and time saving methods as well as practical instructions for coaches should be developed in soccer in the future.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

All authors contributed to the conception of the study. MT and CK assessed the data. MT performed the statistical analysis and wrote the first draft of the manuscript. SH, SA, LR, CK, LK, and AW revised the original manuscript. All authors read and approved the final manuscript.

Acknowledgments

We acknowledge support by the KIT-Publication Fund of the Karlsruhe Institute of Technology.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Altman D. G., Bland J. M. (1983). Measurement in medicine: The analysis of method comparison studies. Statistician 32, 307–317. doi:10.2307/2987937

CrossRef Full Text | Google Scholar

Altmann S., Neumann R., Woll A., Härtel S. (2020). Endurance capacities in professional soccer players: Are performance profiles position specific? Front. Sports Act. Living 2, 549897. doi:10.3389/fspor.2020.549897

CrossRef Full Text | Google Scholar

Aquino R., Carling C., Maia J., Vieira L. H. P., Wilson R. S., Smith N., et al. (2020). Relationships between running demands in soccer match-play, anthropometric, and physical fitness characteristics: A systematic review. Int. J. Of Perform. Analysis Sport 20, 534–555. doi:10.1080/24748668.2020.1746555

CrossRef Full Text | Google Scholar

Bangsbo J., Iaia F. M., Krustrup P. (2008). The yo-yo intermittent recovery test : A useful tool for evaluation of physical performance in intermittent sports. Sports Med. 38, 37–51. doi:10.2165/00007256-200838010-00004

PubMed Abstract | CrossRef Full Text | Google Scholar

Bangsbo J., Nørregaard L., Thorsoe F. (1991). Activity profile of competition soccer. Can. J. Of Sport Sci. 16, 110–116.

PubMed Abstract | Google Scholar

Bellenger C. R., Fuller J. T., Nelson M. J., Hartland M., Buckley J. D., Debenedictis T. A. (2015). Predicting maximal aerobic speed through set distance time-trials. Eur. J. Appl. Physiol. 115, 2593–2598. doi:10.1007/s00421-015-3233-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Berthoin S., Pelayo P., Lensel-Corbei G., Robin H., Gerbeaux M. (1996). Comparison of maximal aerobic speed as assessed with laboratory and field measurements in moderately trained subjects. Int. J. Sports Med. 17, 525–529. doi:10.1055/s-2007-972889

PubMed Abstract | CrossRef Full Text | Google Scholar

Billat L. V., Hill D. W., Pinoteau J., Petit B., Koralsztein J. P. (1996). Effect of protocol on determination of velocity at Vo2 max and on its time to exhaustion. Arch. Physiol. Biochem. 104, 313–321. doi:10.1076/apab.104.3.313.12908

PubMed Abstract | CrossRef Full Text | Google Scholar

Billat L. V., Koralsztein J. P. (1996). Significance of the velocity at vo 2max and time to exhaustion at this velocity. Sports Med. 22, 90–108. doi:10.2165/00007256-199622020-00004

PubMed Abstract | CrossRef Full Text | Google Scholar

Buchheit M. (2008). The 30-15 intermittent fitness test: Accuracy for individualizing interval training of young intermittent sport players. J. Strength Cond. Res. 22, 365–374. doi:10.1519/JSC.0b013e3181635b2e

PubMed Abstract | CrossRef Full Text | Google Scholar

Buchheit M. (2010). The 30–15 intermittent fitness test: 10 Year review. Myorobie J. 1, 278.

Google Scholar

Chtourou H., Souissi N. (2012). The effect of training at A specific time of day: A review. J. Strength Cond. Res. 26, 1984–2005. doi:10.1519/JSC.0b013e31825770a7

PubMed Abstract | CrossRef Full Text | Google Scholar

Clarke R., Dobson A., Hughes J. (2016). Metabolic conditioning: Field tests to determine A training velocity. Strength & Cond. J. 38, 38–47. doi:10.1519/ssc.0000000000000188

CrossRef Full Text | Google Scholar

Cohen J. (1988). Statistical power analysis for the behavioral sciences. Ny: Academic.

Google Scholar

Darendeli A., Vitiello D., Billat V., Diker G., Cuğ M. (2021). Comparison of different exercise testing modalities to determine maximal aerobic speed in amateur soccer players. Sci. Sports 36, 105–111. doi:10.1016/j.scispo.2020.09.006

CrossRef Full Text | Google Scholar

Denadai B. S., Ortiz M. J., Greco C. C., De Mello M. T. (2006). Interval training at 95% and 100% of the velocity at V O2 max: Effects on aerobic physiological indexes and running performance. Appl. Physiology, Nutr. And Metabolism 31, 737–743. doi:10.1139/h06-080

PubMed Abstract | CrossRef Full Text | Google Scholar

Di Prampero P., Atchou G., Brückner J.-C., Moia C. (1986). The energetics of endurance running. Eur. J. Appl. Physiol. Occup. Physiol. 55, 259–266. doi:10.1007/BF02343797

PubMed Abstract | CrossRef Full Text | Google Scholar

Dickhuth H.-H., Kindermann W. (2002). Einführung in die sport-und leistungsmedizin. Sportwiss. 32, 110–112. doi:10.1007/bf03176718

CrossRef Full Text | Google Scholar

Dickhuth H., Badtke G. (2007). Sportmedizin für ärzte: Lehrbuch auf der grundlage des weiterbildungssystems der deutschen gesellschaft für sportmedizin und prävention (dgsp). Deutscher Ärzteverlag: Mit 109 Tabellen.

Google Scholar

González-Mohíno F., González-Ravé J. M., Juárez D., Fernández F. A., Castellanos R. B., Newton R. U. (2016). Effects of continuous and interval training on running economy, maximal aerobic speed and gait kinematics in recreational runners. J. Strength Cond. Res. 30, 1059–1066. doi:10.1519/JSC.0000000000001174

PubMed Abstract | CrossRef Full Text | Google Scholar

Hernández-Vicente A., Hernando D., Marín-Puyalto J., Vicente-Rodríguez G., Garatachea N., Pueyo E., et al. (2021). Validity of the polar H7 heart rate sensor for heart rate variability analysis during exercise in different age, body composition and fitness level groups. Sensors 21, 902. doi:10.3390/s21030902

PubMed Abstract | CrossRef Full Text | Google Scholar

Hopkins W. G. (2004). How to interpret changes in an athletic performance test. Sportscience 8, 1–7.

PubMed Abstract | Google Scholar

Jones A. M., Doust J. H. (1996). A 1% treadmill grade most accurately reflects the energetic cost of outdoor running. J. Sports Sci. 14, 321–327. doi:10.1080/02640419608727717

PubMed Abstract | CrossRef Full Text | Google Scholar

Kuipers H., Rietjens G., Verstappen F., Schoenmakers H., Hofman G. (2003). Effects of stage duration in incremental running tests on physiological variables. Int. J. Sports Med. 24, 486–491. doi:10.1055/s-2003-42020

PubMed Abstract | CrossRef Full Text | Google Scholar

Lacour J., Padilla-Magunacelaya S., Chatard J., Arsac L., Barthelemy J. (1991). Assessment of running velocity at maximal oxygen uptake. Eur. J. Appl. Physiol. Occup. Physiol. 62, 77–82. doi:10.1007/BF00626760

PubMed Abstract | CrossRef Full Text | Google Scholar

Léger L., Boucher R. (1980). An indirect continuous running multistage field test: The Université de montréal track test. Can. J. Appl. Sport Sci. 5, 77–84.

PubMed Abstract | Google Scholar

Léger L., Mercier D., Gadoury C., Lambert J. (1988). The multistage 20 metre shuttle run test for aerobic fitness. J. Sports Sci. 6, 93–101. doi:10.1080/02640418808729800

PubMed Abstract | CrossRef Full Text | Google Scholar

Leser R., Baca A., Ogris G. (2011). Local positioning systems in (game) sports. Sensors 11, 9778–9797. doi:10.3390/s111009778

PubMed Abstract | CrossRef Full Text | Google Scholar

Lundquist M., Nelson M. J., Debenedictis T., Gollan S., Fuller J. T., Larwood T., et al. (2021). Set distance time trials for predicting maximal aerobic speed in female Australian Rules footballers. J. Sci. Med. Sport 24, 391–396. doi:10.1016/j.jsams.2020.10.002

PubMed Abstract | CrossRef Full Text | Google Scholar

Marées H. D., Heck H. (2003). Sportphysiologie. Köln: Sportverlag strauß.

Google Scholar

Mckay A. K., Stellingwerff T., Smith E. S., Martin D. T., Mujika I., Goosey-Tolfrey V. L., et al. (2022). Defining training and performance caliber: A participant classification framework. Int. J. Sports Physiol. Perform. 17, 317–331. doi:10.1123/ijspp.2021-0451

CrossRef Full Text | Google Scholar

Metaxas T. I., Koutlianos N. A., Kouidi E. J., Deligiannis A. P. (2005). Comparative study of field and laboratory tests for the evaluation of aerobic capacity in soccer players. J. Strength Cond. Res. 19, 79–84. doi:10.1519/14713.1

PubMed Abstract | CrossRef Full Text | Google Scholar

Meyer T., Kindermann W. (1999). Die maximale sauerstoffaufnahme (Vo2max). Dtsch. Z. Für Sportmed. 50, 285–286.

Google Scholar

Neumann R. (2013). Analyse physiologischer Gesetzmäßigkeiten zu den Themenbereichen “Ausbelastungskriterien” und “Nachbelastungsverhalten” anhand der Ergebnisse ausdauerleistungsdiagnostischer Untersuchungen am Institut für Sport und Sportwissenschaft des Karlsruher Instituts für Technologie (KIT) im Zeitraum 2007–2010 Doctoral dissertation. Karlsruhe: Karlsruher Institut für Technologie (KIT), Diss.

Google Scholar

Petot H., Meilland R., Le Moyec L., Mille-Hamard L., Billat V. L. (2012). A new incremental test for VO₂max accurate measurement by increasing VO₂max plateau duration, allowing the investigation of its limiting factors. Eur. J. Appl. Physiol. 112, 2267–2276. doi:10.1007/s00421-011-2196-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Riboli A., Coratella G., Rampichini S., Limonta E., Esposito F. (2021). Testing protocol affects the velocity at Vo2max in semi-professional soccer players. Res. Sports Med. 30, 182–192. doi:10.1080/15438627.2021.1878460

CrossRef Full Text | Google Scholar

Sandford G. N., Laursen P. B., Buchheit M. (2021). Anaerobic speed/power reserve and sport performance: Scientific basis, current applications and future directions. Sports Med. 51, 2017–2028. doi:10.1007/s40279-021-01523-9

CrossRef Full Text | Google Scholar

Sandford G., Rogers S., Sharma A., Kilding A., Ross A., Laursen P. (2019). Implementing anaerobic speed reserve testing in the field: Validation of Vvo2max prediction from 1500-M race performance in elite middle-distance runners. Int. J. Sports Physiol. Perform. 14, 1147–1150. doi:10.1123/ijspp.2018-0553

PubMed Abstract | CrossRef Full Text | Google Scholar

Sangan H. F., Hopker J. G., Davison G., Mclaren S. J. (2021). The self-paced submaximal run test: Associations with the graded exercise test and reliability. Int. J. Sports Physiol. Perform. 1, 1865–1873. doi:10.1123/ijspp.2020-0904

PubMed Abstract | CrossRef Full Text | Google Scholar

Souza K. M. D., Lucas R. D. D., Grossl T., Costa V. P., Guglielmo L. G. A., Denadai B. S. (2014). Performance prediction of endurance runners through laboratory and track tests. Revista Brasileira De Cineantropometria Desempenho Humano 16, 466–474. doi:10.5007/1980-0037.2014v16n4p465

CrossRef Full Text | Google Scholar

Speer K. E., Semple S., Naumovski N., Mckune A. J. (2020). Measuring heart rate variability using commercially available devices in healthy children: A validity and reliability study. Eur. J. Investig. Health Psychol. Educ. 10, 390–404. doi:10.3390/ejihpe10010029

CrossRef Full Text | Google Scholar

Tanner R., Gore C. (2012). Physiological tests for elite athletes. Champaign: Human Kinetics.

Google Scholar

Tremblay M. S., Leblanc A. G., Carson V., Choquette L., Connor Gorber S., Dillman C., et al. (2012). Canadian sedentary behaviour guidelines for the early years (aged 0–4 Years). Appl. Physiology, Nutr. And Metabolism 37, 370–391. doi:10.1139/h2012-019

CrossRef Full Text | Google Scholar

Vogler A. J., Rice A. J., Gore C. J. (2010). Validity and reliability of the cortex Metamax3b portable metabolic system. J. Sports Sci. 28, 733–742. doi:10.1080/02640410903582776

PubMed Abstract | CrossRef Full Text | Google Scholar