We investigated the relationship of the time-dependent behaviour of muscle oxygen saturation SmO 2 (t), phosphagen energy supply W PCr (t) and blood lactate accumulation ΔBLC(t) during a 60-s all-out cycling sprint and tested SmO 2 (t) for correlations with the end of the fatigue-free state t Ff...

Background: Maximal force-velocity (F/v) profiles for track cyclists are commonly derived from ergometer sprints using an isovelocity or isoinertial approach. Previously, an attempt was made to derive maximal F/v profiles from a single maximal 65-m sprint on the cycling track. Hypothesising that this approach may not accurately reflect the fatigue-free F/v profile, we propose an alternative procedure and compare it to the previous method. Moreover, we test for the impact of gear ratio on diagnostic results. Methods: Twelve elite track cyclists completed a high-cadence low-resistance pedalling test on a freestanding roller (motoric test) and two series of three maximal 65-m sprints on a cycling track with different gear ratios. F/v profiles were calculated based on the measured crank force and cadence either during the first 6–7 revolutions (≤6 s) on the track (model I) or were derived from the first 3–4 revolutions (≤3 s) on the track combined with 1 or 2 fatigue-free cycles at cadences above 160 rpm from the motoric test (model II). Results: Although both models exhibit high-to-excellent linearity between force and velocity, the extrapolated isometric force was higher (1507.51 ± 257.60 N and 1384.35 ± 276.84 N; p < 0.002; d = 2.555) and the slope steeper (−6.78 ± 1.17 and −5.24 ± 1.11; p < 0.003, d = −2.401) with model I. An ICC of 1.00 indicates excellent model consistency when comparing the F/v profiles (model II) derived from the different geared sprints. Conclusions: Assuring fatigue-free measurements and including high-cadence data points in the calculations provide valid maximal F/v and P/v profiles from a single acceleration-sprint independent of gear ratio.

Purpose: Following short-term all-out exercise, the maximal rate of glycolysis is frequently assessed on the basis of the maximal rate of lactate accumulation in the blood. Since the end of the interval without significant accumulation (t_alac) is 1 of 2 denominators in the calculation employed, accurate determination of this parameter is crucial. Although the very existence and definition of t_alac, as well as the validity of its determination as time-to-peak power (t_Ppeak), remain controversial, this parameter plays a key role in anaerobic diagnostics. Here, we describe a novel approach to determination of t_alac and compare it to the current standard. Methods: Twelve elite track cyclists performed 3 maximal sprints (3, 8, and 12 s) and a high-rate, low-resistance pedaling test on an ergometer with monitoring of crank force and pedaling rate. Before and after each sprint, capillary blood samples were taken for determination of lactate accumulation. Fatigue-free force–velocity and power–velocity profiles were generated. t_alac was determined as t_Ppeak and as the time span up to the first systematic deviation from the force–velocity profile (t_Ff). Results: Accumulation of lactate after the 3-second sprint was significant (0.58 [0.19] mmol L⁻¹; P < .001, d = 1.982). t_Ff was <3 seconds and t_Ppeak was ≥3 seconds during all sprints (P < .001, d = − 2.111). Peak power output was lower than maximal power output (P < .001, d = −0.937). Blood lactate accumulation increased linearly with increasing duration of exercise (R² ≥ .99) and intercepted the x-axis at ∼t_Ff. Conclusion: Definition of t_alac as t_Ppeak can lead to incorrect conclusions. We propose determination of t_alac based on t_Ff, the end of the fatigue-free state that may reflect the beginning of blood lactate accumulation.

In cycling, performance models are used to investigate factors that determine performance and to optimise competition results. We present an innovative and easily applicable mathematical model describing time-resolved approaches for both the physical aspects of tractional resistance and the physiological side of propelling force generated by muscular activity and test its validity to reproduce and forecast time trials in track cycling. Six elite track cyclists completed a special preparation and two sprint time trials in an official velodrome under continuous measurement of crank force and cadence. Fatigue-free force-velocity profiles were calculated, and their fatigue-induced changes were determined by non-linear regression analysis using a monoexponential equation at a constant slope. Model parameters were calibrated based on pre-exercise performance testing and the first of the two time-trials and then used to predict the performance of the second sprint. Measured values for power output and cycling velocity were compared to the modelled data. The modelled results were highly correlated to the measured values ($R^2>0.99$) without any difference between runs ($p>0.05$; $d<0.1$). Our mathematical model can accurately describe sprint track cycling time trial performance. It is simple enough to be used in practice yet sufficiently accurate to predict highly dynamic maximal sprint performances. It can be employed for the evaluation of completed runs, to forecast expected results with different setups, and to study various contributing factors and quantify their effect on sprint cycling performance.

In track cycling sprint events, optimal cadence PR_opt is a dynamic aspect of fatigue. It is currently unclear what cadence is optimal for an athlete’s performance in sprint races and how it can be calculated. We examined fatigue-induced changes in optimal cadence during a maximal sprint using a mathematical approach. Nine elite track cyclists completed a 6-s high-frequency pedaling test and a 60-s isokinetic all-out sprint on a bicycle ergometer with continuous monitoring of crank force and cadence. Fatigue-free force-velocity (F/v) and power-velocity (P/v) profiles were derived from both tests. The development of fatigue during the 60-s sprint was assessed by fixing the slope of the fatigue-free F/v profile. Fatigue-induced alterations in PR_opt were determined by non-linear regression analysis using a mono-exponential equation at constant slope. The study revealed that PR_opt at any instant during a 60-s maximal sprint can be estimated accurately using a mono-exponential equation. In an isokinetic mode, a mean PR_opt can be identified that enables the athlete to generate the highest mean power output over the course of the effort. Adding the time domain to the fatigue-free F/v and P/v profiles allows time-dependent cycling power to be modelled independent of cadence.

Sprint races in track cycling are characterised by maximal power requirements and high-power output over 15 to 75 s. As competition rules limit the athlete to a single gear, the choice of gear ratio has considerable impact on performance. Traditionally, a gear favouring short start times and rapid acceleration, i.e., lower transmission ratios, was chosen. In recent years, track cyclists tended to choose higher gear ratios instead. Based on a review of the relevant literature, we aimed to provide an explanation for that increase in the gear ratio chosen and apply this to a 1000 m time trial. Race data with continuous measurements of crank force and velocity of an elite track cyclist were analysed retrospectively regarding the influence of the selected gear on power, cadence and resulting speed. For this purpose, time-dependent maximal force-velocity (F/v) profiles were used to describe changes in performance with increasing fatigue. By applying these profiles to a physical model of track cycling, theoretical power output, cadence and resulting speed were calculated for different scenarios. Based on previous research results, we assume a systematic and predictable decline in optimal cadence with increasing fatigue. The choice of higher gear ratios seems to be explained physiologically by the successive reduction in optimal cadence as fatigue sets in. Our approach indicates that average power output can be significantly increased by selecting a gear ratio that minimises the difference between the realised cadence and the time-dependent dynamic optimum. In view of the additional effects of the gear selection on acceleration and speed, gear selection should optimally meet the various requirements of the respective sprint event.