## 7 Discussion  
The findings presented in the current study confirmed that the decrease in optimal cadence due to fatigue during a 60-s maximal sprint by elite track cyclists can be described quite accurately by a mono-exponential equation. By combining the fatigue-induced changes of the fatigue-free F/v profile with the time course of fatigue at maximal intensity, this approach allowed, for the first time, power  
Figure 4: **(a)** Time-dependent maximal power output (Pmax(t)) at dynamic optimal cadence (PRopt(t)) and power output (P(t)) during a 60-s all-out sprint at a cadence of 120 rpm (PR) on a cycle ergometer. **(b)** Comparison of the time-dependent power output (P(t)) at a pedaling rate of 120 rpm and the corresponding work performed (W(t)) to optimized power output (Popt(t)) at a mean optimal pedaling rate of 102 rpm and the corresponding work performed (Wopt(t)) during a 60-s all-out sprint on a cycle ergometer. In fact, free optimization of the mean power output by altering the cadence during the isokinetic test resulted in a calculated mean optimal pedaling rate of 102 rpm. Changing the cadence to 102 rpm would result in a 7% higher mean power output of the athlete in the isokinetic test mode. output to be described in a cadence-independent, normalized form as a three-dimensional model. The relationship between F/v and P/v at maximal effort as a function of time is exemplified in Figure 5.  
Assessment of fatigue or calculation of the decrement in fatigue in a normalized fashion is necessary for modelling the decay in performance during sprints. This model allowed both the evaluation of the different components of physiological performance and the simulation of scenarios to optimize competition performance, taking into account the physical characteristics of cycling. Using Equation (5) to examine the effects of fatigue on the optimal cadence can help to optimize individual cadences and gear ratios. [PERSON] and co-workers [5] suggested that, during competition, when the difference between an athlete's optimal (fatigue-free) cadence and the mean cadence is small, mean power output is maximal. In this context, our present findings indicate that the difference between the mean cadence and mean optimal dynamic cadence should be minimized in order to maximize mean power output. In fact, altering the cadence in the isokinetic test to the calculated mean optimal cadence would have resulted in a 4-12% higher mean power output. In track cycling sprint races with fixed gear ratios, where cadence also changes due to resistance and fatigue, there appears to be even greater potential for enhancing performance by reducing the discrepancy between cadence and individual dynamic optimal cadence [7]. Furthermore, this model allowed the exploration of the relationship between biomechanical and physiological performance. The systematic reduction in optimal cadence might correspond to the mechanical and metabolic properties of the various fiber types, with respect to specific characteristics of force development and contraction velocity, as well as of resistance to fatigue [4; 21]. While force production by contractile units containing different types of fibers is similar, the maximal velocity of contraction by type IIx is approximately four-fold faster than that of type I muscle fibers [22; 23; 24]. IIx fibers derive their energy mainly from phosphates and glycolysis and are assumed to be completely fatigued after about 60 s of maximal power output [25]. The duration of maximal force production by predominantly glycolytic to predominantly oxidative IIa muscle fibers usually ranges from 3-6 min [26; 27], whereas  
Figure 5: A set of curves illustrating the time-course of the relationship between the force-velocity and power-velocity curves during a 60-s all-out sprint on a cycle ergometer. The profiles were derived from the data at every fifth second of the sprint test shown in Figure 2.  
type I muscle fibers can work for as long as several hours without significant loss of power [28].