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HOW DO I MODEL FATIGUE CARRY-OVER FROM SPRING CLASSICS INTO GRAND TOURS?
Racing the Spring Classics takes a massive toll on a rider's physiology—and smart modeling is essential for carrying form into the Grand Tours without blowing up. In this guide, we’ll explore how coaches and performance analysts use training data, fatigue metrics, and recovery models to predict how Spring efforts influence later stage races. Whether you're managing a pro cyclist or building your own season strategy, understanding fatigue carry-over is key to sustainable peak performance.
Understand training load and fatigue metrics
To model fatigue effectively, you need to quantify it. The most common tools for this are Training Stress Score (TSS), Chronic Training Load (CTL), Acute Training Load (ATL), and Training Stress Balance (TSB). These metrics are derived from power data and heart rate variability, offering a numerical way to assess how much strain a rider is under after a heavy race block like the Spring Classics.
Key metrics that matter most
TSS estimates the overall training impact of a session based on intensity and duration. CTL reflects long-term fitness (rolling average of TSS), while ATL measures short-term fatigue. TSB is simply CTL minus ATL, representing freshness. A deeply negative TSB after the Spring Classics suggests the rider needs structured recovery before any Grand Tour prep continues.
CTL (42-day rolling): Measures fitness trend post-classics.
ATL (7-day rolling): Highlights acute fatigue accumulation.
TSB: Use this to schedule deload or reloading weeks.
HRV (Heart Rate Variability): Useful for daily readiness snapshots.
RPE (Rate of Perceived Exertion): Still valuable for qualitative insights.
These models help coaches simulate how riders may respond to various tapering, load, or recovery strategies as the Grand Tours approach.
Apply performance modeling tools
After establishing a baseline with TSS-based metrics, you can use modeling software like TrainingPeaks, WKO5, Golden Cheetah, or Best Bike Split to simulate training and fatigue timelines. These platforms allow coaches to test “what if” scenarios—like inserting a recovery camp post-Classics or adjusting race intensity during tune-up events.
Simulate Grand Tour readiness
Let’s say a rider ends the Spring Classics with a CTL of 120 and ATL of 145. Their TSB is -25, indicating heavy fatigue. Instead of ramping up training again, a taper or recovery block may be used to reduce ATL, allowing freshness (TSB) to rise. With these tools, you can plan for an optimal CTL plateau (~100–110) leading into a Grand Tour with a TSB of +10 to +15.
Use WKO5’s Performance Manager Chart to view CTL/ATL/TSB trends.
Simulate different recovery taper lengths—7, 10, or 14 days.
Apply normalized power outputs to better predict stage-specific readiness.
Layer historical response data to improve model accuracy year over year.
Integrate subjective data (sleep, soreness, motivation) for holistic modeling.
Modeling isn't guesswork—it's iterative testing and adjustment. Elite teams review these metrics daily, especially after high-stress periods like Flanders or Roubaix.
Balance freshness, form, and race exposure
The biggest challenge in modeling fatigue carry-over is balancing freshness with ongoing race sharpness. Pulling a rider out of racing too early may recover their body but dull their edge. Conversely, stacking more race days risks overtraining. Smart modeling accounts for both physiological metrics and the rider’s psychological need to stay race-ready.
Recovery ≠ inactivity
Post-Classics recovery doesn’t mean total rest. Low-intensity rides, altitude camps, or even controlled time trial efforts can help maintain readiness. The key is to monitor for signs of non-functional overreaching—poor sleep, mood dips, and performance stagnation—and adjust the load accordingly. Riders with naturally high CTL ceilings may need less taper than others.
Use HRV trends and mood logs to detect early burnout.
Prescribe “priming” sessions (short high-intensity efforts) every 5–7 days.
Plan altitude blocks with reduced training stress but high adaptation potential.
Include 1–2 short tune-up races if rider motivation drops.
Re-test FTP and VO2 max pre-Grand Tour to confirm restored peak form.
The art of fatigue modeling is finding the sweet spot between sharp and shattered. When done right, it lets riders carry the grit of the Classics into the Grand Tours—and still have legs by Stage 21.
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