UCI Sports Nutrition Project: Nutrition in Road Cycling

Why It Matters

Accurate, individualized nutrition directly influences performance, recovery and weight management in elite cycling, making it a competitive differentiator for WorldTour teams.

Key Takeaways

• Early race intensity rises, prompting earlier glycogen depletion
• Cyclists burn 5,000‑7,000 kcal per day in races
• Target carbohydrate intake: 90 g/h, up to 120 g/h
• Protein mainly post‑exercise; intra‑ride protein may slow carbs
• Teams deploy AI software for individualized energy and carb forecasts

Pulse Analysis

Modern road cycling has shifted from a conservative start‑to‑finish model to aggressive early pacing, forcing riders to tap glycogen stores sooner than ever. This metabolic shift elevates the importance of carbohydrate availability, as athletes now need to replace fuel continuously throughout the race. The UCI paper quantifies this demand, showing that professional cyclists can expend 5,000‑7,000 kcal daily, especially on mountain stages, making precise energy budgeting essential for maintaining power‑to‑mass ratios and avoiding performance‑degrading fatigue.

The nutrition community has responded by revising carbohydrate guidelines from the historic 30 g/h to a more evidence‑based 90 g/h, with some elite riders experimenting up to 120 g/h. While higher intakes boost exogenous oxidation, the marginal performance gains plateau and gastrointestinal distress rises, underscoring the need for gut‑training and tailored drink formulations. Protein remains a cornerstone for post‑ride recovery, stimulating muscle protein synthesis, yet intra‑ride protein can impede carbohydrate absorption, so most teams prioritize carbs during effort and protein afterward. Hydration strategies now factor in variable sweat rates and logistical constraints, ensuring fluid intake aligns with real‑time race conditions.

Beyond the physiology, teams are leveraging sophisticated software platforms and AI engines to predict daily energy and carbohydrate needs based on power‑meter data, historical workloads, and individual metabolic profiles. This data‑driven approach enables dynamic nutrient periodization—keeping protein steady, adjusting carbs to workload, and flexibly managing fat—while also guiding body‑mass targets to optimize climbing performance without triggering low‑energy availability. As practice outpaces published research, the next frontier lies in bridging laboratory findings with these real‑world algorithms, ensuring that nutrition recommendations translate into measurable performance gains on the road.