Performance in downhill road cycling is understudied. Tools that can be used to assess the cyclists` cornering strategies ecologically and objectively are missing. A new methodology based on motion capture and mathematical modelling is presented here. A drone was used to capture the trajectory of the centre of mass of a cyclist, who was asked to complete 10 times a ~220-m-long downhill course. The motion capture and `optimal` trajectories were compared in terms of displacement, speed, and heading. In each trial, the apex, the turn-in and the braking points were detected. Whilst the `optimal` trajectory suggested an `early` apex strategy was best, the cyclist in this study completed the corners with a `late` apex strategy. This study presents a methodology that can be used to objectively assess cornering strategies in road cycling. Discrepancies between actual and `optimal` trajectories are also discussed. This study brings to light concepts such as: `early` or `late` apex, braking and turning points, which are discussed within the context of road cycling downhill performance.
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