Effect of free versus constant pace on performance and oxygen kinetics in running : Medicine & Science in Sports & Exercise

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APPLIED SCIENCES: Physical Fitness and Performance

Effect of free versus constant pace on performance and oxygen kinetics in running


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Medicine & Science in Sports & Exercise 33(12):p 2082-2088, December 2001.
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On a track where the goal is to run a given distance as quickly as possible, athletes spontaneously choose to modulate their pace during the race to avoid becoming overfatigued before reaching the finishing line (1). Sports records are performed with free and not constant paces even during long-distance running, and an athlete in any event lasting more than 2 min has the opportunity to use energy available from the cleavage of phosphagen and from glycolysis in a flexible manner (15). If one considers the last three world records for middle- and long-distance running (1500 m, 3000 m, 5000 m, and 10,000 m), it can be observed that the range of the coefficient of variation of velocity is 1 to 5% (unpublished data computed from the International Amateur Athletic Federation books). However, in a review on pacing strategy and athletic performance, Foster et al. (14) recall that since the initial study of Robinson et al. (25) during a 1200-m run, there have been few systematic studies to determine how various pacing strategies might influence the outcome of competitive performance. The studies were true pacing studies (1,2,14,20) or controlled stochastic investigations (23,24).

It has been demonstrated that under competitive conditions the physiological responses of athletes might be significantly greater than suggested by the conventional incremental test (9,12). Moreover, in a run at 90% of the velocity associated with V̇O2max in an incremental test (vV̇O2max), oxygen consumption continues to increase with time by means of a V̇O2 slow component (i.e., the second amplitude of the oxygen biexponential kinetics model) (6,16,26). Foster et al. (14) suggested that athletes learn how to sense low values of muscle pH and adjust their pace accordingly so that they ideally reach critically low values of pH near the end of a race. During an all-out event of 3–15 min, the increase of type II fiber recruitment, which is correlated with the lactate accumulation, could increase V̇O2 toward V̇O2max. Therefore, a spontaneous decrease in the velocity around the third minute could prevent the development of the V̇O2 slow component (26). Indeed, above the critical power, V̇O2 rises inexorably until fatigue ensues, at V̇O2max(5). Therefore, the purpose of this study was to examine whether a free versus a constant pace produces different performance results and, if so, whether this related to the slow V̇O2 response.



Eleven male long-distance runners (age, 41 ± 10 yr; height, 175 ± 5 cm; weight, 71 ± 5 kg) participated in this study. They trained five times per week (70 ± 20 km·wk−1). These subjects were long-distance runners training for the half-marathon. They were chosen to avoid a strategy (long-term planned) and to get a stochastic pace (i.e., a variation of pace involving probability arising from chance). Before participation in this study, all subjects provided voluntary written informed consent in accordance with the guidelines of the University of Lille.

Experimental Design

Subjects performed nine tests performed until exhaustion. Only one test was carried out on a given day. All tests were performed on a synthetic 400-m track at the same time of day in a climate of 19° to 22°C without wind according to the immobility of the flags surrounding the track. On the day separating the two tests, subjects were asked either to rest or to do light training (i.e., 30 min at 60% of vV̇O2max). They were also asked to refrain from food or beverages containing caffeine before testing. Runners followed a pacing cyclist traveling at the required velocity. The cyclist received audio cues via a Walkman; the cue rhythm determined the speed needed to cover 20 m. Visual marks were set at 20-m intervals along the track (inside the first lane).

The first test was needed to determine V̇O2max, the velocity associated with V̇O2max (vV̇O2max), and the running velocity at the lactate threshold (vLT) (3,9). After this preliminary incremental test, runners performed, in a random order, four constant pace runs at 90, 95, 100, and 105% of vV̇O2max with time (tlim) and distance limits (dlim) being determined at each velocity (Table 1). Then, they performed, also in a random order, a free paced run on each four distance limits (dlim) set by the time limit (tlim) at 90, 95, 100, and 105% of vV̇O2max. For instance, if they ran 300 s at 100% of vV̇O2max equal to 5 m·s−1, they performed a distance limit equal to 1500 m. Therefore, they performed their variable pace run on the same distance limit (i.e., 1500 m) to compare the average velocity with the constant pace trial. Hence, the runners performed free paced runs at the same four distance limits: dlim90, dlim95, dlim100, and dlim105.

Table 1:
Experimental design of the nine tests performed until exhaustion and each separated by 1 day.

Data Collection Procedures

Protocol of V̇O2max and vV̇O2max determination.

The initial speed was set at 10 km·h−1 and was increased by 1 km·h−1 every 2 min. Each stage was separated by a 30-s rest during which a capillary blood sample was obtained from the fingertip and analyzed for lactate concentration (YSI 27 analyzer, Yellow Spring Instruments, Yellow Spring, OH). Measurement of V̇O2 was carried out throughout each test using a telemetric system (K4 b2, COSMED, Rome, Italy) (17,21). Expired gases were measured breath by breath and were averaged every 5 s. Before each test, the O2 analysis system was calibrated using ambient air, whose partial O2 composition was assumed to be 20.9% and a gas of known CO2 concentration (5%) (K4 b2 instruction manual). The calibration of the turbine flow- meter of the K4 b2 was performed with a 3-L syringe (Quinton Instruments, Seattle, WA). In the incremental tests, the maximal oxygen consumption (V̇O2max) was defined as the highest V̇O2 obtained in two successive 15-s intervals. In this incremental protocol, vV̇O2max was defined as the lowest running speed maintained for more than 1 min that elicited V̇O2max(8). If, during the last stage, an athlete achieved V̇O2max that was not sustained for at least 1 min, the speed during the previous stage was recorded as his vV̇O2max. If this velocity that resulted in fatigue was only sustained for ≥ 1 min and < 2 min, then vV̇O2max was considered to be equal to the velocity during the previous stage plus the half velocity increase between the last two stages (i.e., 1 km·h−1/2 = 0.5 km·h−1) (19). The lactate threshold (LT) was defined as the V̇O2 value that corresponded to the starting point of an accelerated lactate accumulation between 3.5 and 5 mmol·L−1(3).

Constant and free paces on distances limit at 90, 95, 100, and 105% vV̇O2max.

The constant and free pace runs on dlim90, dlim95, dlim100, and dlim105 were preceded by 15 min of warming-up at 50% vV̇O2max and 5 min of rest to obtain basal oxygen consumption and blood lactate concentration. For the constant velocity runs, the subjects followed a pacing cyclist traveling at the required velocity. The cyclist received audio cues via a Walkman; the cue rhythm determined the speed needed to cover 20 m. Visual marks were set at 20-m intervals along the track (crossing perpendicular to the first lane). The runners were asked to maintain the tempo as long as possible. This allowed the time and distance limit at 90, 95, 100, and 105% vV̇O2max to be determined. For the free pace runs, the runners were asked to run as fast as possible the same distance they had previously covered at 90, 95, 100, and 105% of vV̇O2max (dlim90, dlim95, dlim100, and dlim105). Subjects had no way of knowing their velocities. Every 20 m, the time was registered by two cyclists with a chronometer (Digisports Instruments, Seyssins, France) set exactly on the runner’s side avoiding the parallax error when crossing the visual track marks. Thereafter, these data were downloaded into a microcomputer. Since it was operated manually, the registration of the two operators was checked for similarity (it was the case). In all the distance limit runs, six successive 5-s intervals runs (for a period of 30 s as in the incremental tests) were recorded as the maximal V̇O2 obtained during the dlim run.

Blood lactate samples were collected after the warm-up and at 1, 3, and 5 min after the exercise. The highest of these values was taken as the maximal blood lactate value for each test. The rating of perceived exertion (RPE) was based on the Borg scale from 6 to 20 (10). The runners were asked to give their RPE at each lap with hand signals. Another cyclist had the scale board on his back and asked the runners for their RPE at every lap and at the end of the all-out run. The runner answered with a hand signal because of the K4 b2 mask on his face. Subjects had been previously familiarized with the use of the Borg scale during the incremental test.

Data Analyses

Oxygen uptake kinetics.

The V̇O2 kinetics were fit by a monoexponential function (5) for the short exercise bouts on dlim100 and dlim105 according to the following equation:

where V̇O2 (t) is the oxygen uptake at time (t); the V̇O2baseline is the oxygen uptake at the end of the warm-up; A is the amplitude of oxygen uptake (V̇O2max − V̇O2baseline), which subjects reached at the end of the dlim100 and dlim105 all-out runs; and τ is the time constant (5).

For runs long (90% of vV̇O2max), it was checked that all the subjects developed a V̇O2 slow component. Hence, the kinetics of V̇O2 were fit by a triple exponential function (4,5) of the form:

where V̇O2 (t) is the oxygen uptake at time (t), V̇O2baseline is the oxygen uptake at the end of the warm-up, A is the amplitude of oxygen uptake for each component during the test (I, II, and slow), δ is the time delay before the onset of each exponential component (I, II, and slow), and τ is the time constant of each component (5). Initial estimates of the parameter values were made by inspection of the experimental V̇O2max time points. Sigma Plot (SPSS, Inc., Chicago, IL) was used to determine the best-fit estimates for each parameter.

Calculation of the time limit at VO2max in all-out runs at 90, 95, 100, and 105% vV̇O2max.

The time to reach 95% of V̇O2max in the incremental test (TA95% V̇O2max) was calculated according to the following equations used for the mono (equation 1) or triple exponential (equation 2).

1. For the mono exponential starting from equation 1, solving for time t:MATH

Specifically, when V̇O2 (t) has reached 95% V̇O2max,MATH

2. For the triple exponential, a similar approach is used:

Where δ2 is given in equation 2 as the time delay of the third exponential of the V̇O2 kinetics and

Where A1′ = A1 + A0 * (1 − e-(δ1/τ0))

Combining equations 5 and 6 yields


Time limit at V̇O2max (tlim @ V̇O2max) can be computed according to equation 8:

where TA95% V̇O2max is derived from the mono or triple exponential models as described above (equations 1 or 2), and tlim is the total time to exhaustion (time limit) of the all-out runs performed at constant or variable paces.

Oxygen consumed.

The aerobic component of the total energy requirement for the all-out tests was computed by integrating the area under the curve V̇O2 time until exhaustion. The volume of oxygen consumed is the definite integral of equations 1 and 2 performed with Mathcad 8 software (MathSoft, Cambridge, MA) (7).

Statistical Analysis

The results are presented as mean ± standard deviation (SD). A two-way analysis of variance (constant vs free pace) for four levels (four speeds: 90, 95, 100, and 105% vV̇O2max) was used to compare the average velocities between the constant versus variable paces in dlim90, dlim95, dlim100, and dlim105. Significant differences were identified by Scheffépost hoc tests. Oxygen kinetics parameters (time delay, time constant, amplitude, and V̇O2baseline) in constant versus variable paces were compared using the Student’s t-test. The results are presented as mean ± SD. Statistical significance has been set at P < 0.05.


The individual characteristics of the subjects obtained during the incremental test are presented in Table 2. In all free pace runs (dlim90, dlim95, dlim100, and dlim105), the runners accelerated in the second part of the run, especially during the last lap (Fig. 1). In all the free pace runs, the variation of velocity were very small and not significantly different between the four dlim. Indeed, the coefficient of variation (in percentage of the average velocity) was less than 5% dlim (4.2 ± 1.3%, 4.8 ± 2.4%, 3.6 ± 1.1%, and 4.6 ± 1.9% for dlim90, dlim95, dlim100, and dlim105, respectively;P = 0.40). Figure 2 shows a typical subject. Moreover, the coefficient of variation of the speed was much lower during all the race but the last lap (3.8 ± 1.6%, 2.3 ± 1.7%, 2.5 ± 0.8%, and 3.2 ± 2.9% for dlim90, dlim95, dlim100, and dlim105, respectively;P = 0.32).

Table 2:
Individual incremental test data.
Velocity (expressed as a percent of the average velocity on dlim90, dlim95, dlim100, and dlim105) in the first and second half of the time limit tests and in the last lap of the runs at free pace.
Time course of oxygen consumption in the free (black squares) and constant pace (open squares) all-out runs on dlim90, dlim95, dlim100, and dlim105 (from top to bottom). Velocity is indicated as a narrow line (constant velocity) and squares (free velocity). This is an example in a typical subject for each distance limit: dlim90, dlim95, dlim100, and dlim105.

These velocity variations were ineffective in improving performance (i.e., to decrease the time for running the distance limits) (Table 3). Indeed, there was no significant difference in time to exhaustion between free and constant pace on the same dlim. Hence, performances (i.e., average velocity on dlim) were not improved by variable pace excepted in dlim at 105% vV̇O2max (4.96 ± 0.6 m·s−1 vs 4.86 ± 0.5 m·s−1, P = 0.04).

Table 3:
Individual performance (time limit), time spent at V̇O2max, and maximal blood lactate in the dlim90, dlim95, dlim100, and dlim105 run at constant and spontaneous paces.

All the subjects developed a slow phase of oxygen kinetics in dlim90, long enough to observe it. The oxygen kinetics and the volume of oxygen consumed during dlim were not modified in the free pace runs except for the time delay in the onset of the slow phase of oxygen kinetics, which appears earlier in the dlim90 variable velocity run (134 ± 64 s vs 180 ± 94 s, P = 0.05) (Table 4). Indeed, at 90% of vV̇O2max, the time delay for the oxygen slow phase (δ2) was significantly shorter in the free than in the constant pace (134 ± 64 s vs 180 ± 94 s, P = 0.05), but in this case, subjects had run this 130 s faster than in the constant velocity dlim90 (92% vs 90% of vV̇O2max). The time spent at V̇O2max in each of the dlim run at constant versus free pace was not significantly different (Table 4).

Table 4:
Influence of free pace versus constant pace on oxygen kinetics parameters.

Maximal blood lactate did not differ significantly between free and constant paces (P = 0.86) (Table 3). The RPE was not influenced either by spontaneous velocity (P = 0.53) or by the interaction between intensity (90, 95, 100, and 105% vV̇O2max) and (small) variation of pace in free pace runs (P = 0.32). RPE response at 25, 50, 75, and 100% of time to exhaustion, independent of the distance limit, was not influenced by constant or variable velocity (P = 0.90). In both cases, RPE was close to its maximum at the end of the exercise whatever the intensity and was not significantly different according to the type of pace (constant or variable) (19.9 ± 0.4 vs 19.5 ± 0.8 for constant and variable velocity, respectively;P = 0.34).


This study showed that in free pace runs performed by long-distance runners unfamiliar with these middle distances (1000–3000 m), pace variations were small, especially if we only consider all of the distance that is run except the last lap. Consequently, the oxygen kinetics and blood lactate were not affected by the free pace versus constant runs except for the time delay for the oxygen slow component, which was shorter because the first part of the distance run was faster than in the constant pace run (92% vs 90% of vV̇O2max).

This study clearly shows that a variable versus a constant pacing in all-out runs on dlim90, dlim95, dlim100, or dlim105 produces similar performances in these subjects who are not middle-distance runners. Moreover, the oxygen kinetics and the slow V̇O2 response were not affected by the variable versus constant pace. Indeed, this study showed that the oxygen kinetics was not modified by the small variation in velocity except at 90% of vV̇O2max, where there was a shorter time delay for the V̇O2 slow component because of the first 3 min run at 92% versus 90% of vV̇O2max. This is in accordance with Hughson et al. (18), who recently reported that there was an inverse relationship between the time delay to reach V̇O2max, the V̇O2 slow component, and the intensity of exercise.

Pace and performance in variable velocity studies.

The literature has generally focused on performance and physiological responses in a one-time trial (1,2,12) or in subsequent all-out exercise (23,24). Using a self-pace approach as in our study, Foster et al. (13) examined the pace in a 5-km simulated competition where no pacing constraint was applied in order to examine the physiological responses of the cyclists. Each subject was instructed to complete the 5 km as rapidly as possible, as in a competition. Throughout the first half of the 5-km time trial (of the same duration as our dlim90 and dlim95), cycling velocity increased progressively to remain relatively constant throughout the last 2 km. In our study carried out on running performance, where the energy cost is nonaerodynamic (11), all of the runners accelerated during the second part of the distance limit and in particular during the last lap. This may be because they were on a track and the finishing line stimulates subjects more than tests made in the laboratory. In addition, the subjects were long-distance runners who were used to accelerating at the end of the 10-km race. In running competitions, acceleration during the last stages of more prolonged events (as 10 km) is common (14).

This present investigation was “self-paced,” with athletes not receiving instruction regarding running speed (and therefore not having consistency between efforts). We found that the variation of pace was very small; consequently, this study cannot be point by point compared with true pacing studies (12) or controlled stochastic investigations (23,24). However, even if the experimental design was different, the effect of variation of velocity on physiological response and performance have been examined, since the best performances are generally performed with pace variations. Larger variations of pace could have been observed if we had chosen middle-distance runners, who would have used their racing strategy to get the best time on free pace runs.

Foster et al. (12) reported that in an all-out 2-km time trial (on a bicycle attached to a wind load simulator), the relationship between the starting pace and the final time relationship could be described by a U-shaped second-order polynomial curve with the nadir for final time at a starting pace of 51% of the best total time. Two recent studies also performed on cyclists but in a longer trial (2 h) used stochastic exercise (23,24). In the first study (23), the authors compared the effects on performance (20-km time trial) of 150 min of steady-state exercise (at 58% of the peak power output reached in an incremental test (PPO) (22)) versus stochastic exercise (58 ± 12.2% PPO) by 150-min paced rides. The power outputs during the stochastic ride ranged from 35.8 to 82.3% of PPO to mimic the efforts of cyclists during a previously investigated 105-km mass start cycle race. The authors found that all the cyclists decreased their performances (the time trial increased by 6%) in the subsequent 20-km time performed after the stochastic pace. The authors speculated that a repeated work-rate increase in the stochastic ride might have been associated with an increased use of muscle glycogen. As a consequence, they then compared the metabolic responses to constant load versus variable intensity exercise (24) and found that type II muscle fibers were more depleted after variable than after constant load exercise, and that the inverse was true for type I fibers. In this new study (24), however, subsequent time trial performance was similar after both variable or constant intensity load (70% of V̇O2max). These results demonstrate that the whole body metabolic and cardiovascular responses (V̇O2, energy expenditure, heart rate) to 140 min of either constant load or variable intensity exercise (cycling) at the same average intensity are similar, despite differences in skeletal muscle carbohydrate metabolism and recruitment. Variable intensities of exercise could produce a reduction in the utilization of total muscle glycogen.

Free versus constant pace effect on oxygen kinetics and physiological responses.

The second purpose of this study was to examine the influence of free pace on oxygen kinetics during all-out runs on dlim90, dlim95, dlim100, and dlim105. The results we have obtained confirm those of Gaesser and Poole (16) that during prolonged exercise at intensities above the critical velocity, the V̇O2 continues to increase until V̇O2max is reached. In the present study, V̇O2max was attained by all but one subject (one of the two best trained) for the dlim90 performed at a constant pace. This subject attained V̇O2max during the dlim90 free pace run because of an increase in the velocity at the beginning of the second lap (the runner reaching 105% of vV̇O2max in the last lap). We hypothesize that small variations in velocity, spontaneously chosen by the runners, could decrease the V̇O2 slow component in these two supracritical velocity runs during the dlim90 and dlim95 tests. The V̇O2 slow component was as large during the free pace as during the constant pace runs (414 ± 241 mL·min−1 vs 417 ± 151 mL·min−1, respectively). This confirms that in running events, nonelite runners have a slow component, which is in contrast to high level runners (9). The δ2 decreased during free pace running compared with constant pace running at dlim90 (134 ± 64 s vs 180 ± 94 s, respectively;P < 0.05).

RPE and blood lactate were not significantly different in free versus constant pace runs according to Liedl et al. (20). In both cases, RPE was close to its maximum at the end of the distance limit (dlim90, dlim95, dlim100, and dlim105). Recently, Liedl et al. (20) reported no differences in mean V̇O2, blood lactate concentration, and mean rate of perceived exhaustion between the constant versus variable power (± 5%) during endurance cycling (1 h at 78% of V̇O2max).


This study, performed on the track, is the first to examine the influence of variable pace versus constant pace on performance associated with the oxygen kinetics. With the exception of the final 400 m, these runners had little pace variation (< 5% on all dlim). This was possibly because they are not middle-distance runners and are more accustomed to the constant load pacing of long-distance running. Consequently, the physiological responses and, in particular, the oxygen kinetics and time spent at V̇O2max were not significantly different in free versus constant pace in all-out runs over a distance limit previously determined in constant pace runs at 90, 95, 100, and 105% vV̇O2max. Since the best performances and, in particular, world records are usually broken with variations in speed, it is important that applied physiologists examine the adaptation of the physiological responses on the input, which is variable by nature. The question is to know whether an athlete changes his or her velocity to maintain a physiological steady state for as long as possible or if this change in velocity is tactical or both. Therefore, further work on middle-distance runners is needed in order to determine whether free pace with spontaneous pace variation will improve performance and if it is related to oxygen kinetics acceleration.

This study was supported by grants from the Caisse Centrale des Activités Sociales d’Electricité et Gaz de France.

Address for correspondence: Véronique L. Billat, PhD, Centre de Médecine du Sport C.C.A.S., 2 Avenue Richerand, F-75010 Paris, France; E-mail: [email protected]


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