The work of this thesis relies on modeling fatigue in endurance sport as a smooth, athlete-normalized dynamical state that links external workload and internal responses to performance. Fatigue is treated as the progressive loss of capacity to sustain pace or power, emerging from cardiovascular, metabolic, neuromuscular, and perceptual factors. Because no single laboratory metric or rating captures this heterogeneity, we seek a representation that is data efficient, comparable across athletes, and predictive. We adopt an interpretable bounded formulation in which a differentiable state in [0,1] accumulates when intensity exceeds an athlete's specific critical threshold and dissipates during recovery, with a smooth transition between the two regimes.