Endurance cycling events are often won or lost in a maximal finishing sprint. Supply and demand modeling may provide useful insight regarding optimal sprinting strategies. However, modeling energy supply during such a sprint is complicated by the initial conditions for that sprint, including fatigue and pedaling rate, and by the progression of fatigue during the sprint itself. Energy demand is highly dependent on aerodynamic drag which, in turn, depends on velocity and proximity to other riders. In this presentation, validation of a recently-developed model for supply power during maximal cycling will be presented. An established demand model will be modified to include recently published data on rider-rider aerodynamic interactions. These supply and demand models will be coupled to predict performance using forward integration and to explore a variety of sprint finish strategies including starting point, gear selection, following distance, and lateral clearance during passing.