Progressive Overload and Ramp Rate in Endurance Training

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For much of the last 30 years, the late Dr Jim Stray-Gundersen and I have been studying how we quantify training load. In the mid-90s, we met Dr. Erik Bannister at the American College of Sports Medicine (ACSM) Conference in Orlando, Florida. Dr Bannister developed the Training Impulse (TRIMP) system, which is still used today as part of many online training platforms. While the system is not perfect, it provides a better measure of training load than hours, mileage, or pace/power. In all my coaching work, I use TRIMPs as the primary metric to quantify the training loads and plan for progression of training.

Progressive overload appears to be a common theme in endurance training. But what is progressive overload? Despite many thousands of papers and articles related to progressive overload in endurance training on academic and coaching websites, I have found little to no research that specifically addresses the role of progressive overload—or ramp rate—in a structured, evidence-based way for endurance athletes. A general Google search reveals a multitude of articles explaining the theory of progressive overload, but few, if any, studies that scientifically validate its practical application in endurance sport.

Let me be clear: I do not question the need to increase training loads over years of athletic development. The evidence supports that long-term progressive training is necessary. What I do question is how we approach load distribution across a training year. Over my 50+ years of involvement in high-level training, the principle of overload has always been present. But we need to ask ourselves:

• What exactly is “overload?”
• How is it measured?
• And if we can define and measure it, is it truly effective?

This discussion also overlaps with the Supercompensation Theory, another widely accepted concept that, like progressive overload, lacks robust research. In my experience, progressive overload often leads to overtraining rather than performance gains. Rather than thinking about the theory of progressive overload or Supercompensation we ought to think of training as a compounding effect on fitness. In other words the consistency of well executed training sessions is most important.

What Load Are We Increasing?

The first question is: What type of load are we trying to progress?

• Is it speed, pace, or power (external load)?
• Is it internal physiological strain (e.g., O2 utilization, energy metabolism, heart rate, perceived exertion)?
• Is it time or distance spent training?

The second question: Is increasing the load actually necessary to stimulate adaptation, or can consistent training yield gains through chronic exposure to stimulus? And third: If progressive overload is valid, how do we determine when and how to increase load—through volume, intensity, frequency, or something else?

Most coaches base progression on hours trained or distance covered. But those alone fail to define true training loads because they omit intensity, pace, or power—an essential component. The question I pose is: If training is working as planned, the speed/pace or power we can maintain at a given intensity should consistently improve. Is that not the ideal way to increase the load and fitness?

TRIMP and Load Monitoring

For the purpose of this discussion, I will use TRIMP (Training Impulse) as a reference. While TRIMP has a known bias toward duration over intensity, it still offers a consistent comparative metric. However, even TRIMP doesn’t fully capture external load (e.g., power output).

Take this example: if I ride my bike for two hours a day, 5–6 days a week, over three months, will my fitness plateau? Experience says no. In fact, I’ve observed that optimal acute training loads should hover around 1.2 times an athlete’s current chronic load, with weekly ranges from 0.9 to 1.2. Loads exceeding this often hinder adaptation. A recent paper by Sandbakken from Norway suggests a very similar loading pattern. Of course, there will be races and peak sessions that occasionally fall outside this range, but most training should stay within it.

Dispelling the Myth of “Replicating the Event”

Some believe that to prepare for long endurances event, we must replicate its demands in training. But as Inigo San Millán has stated, training just above baseline lactate levels saturates the mitochondria and stimulates adaptation effectively. This means we are stressing that energy system maximally improvements can occur without massive load increases, what I call the compounding effect of training.

Sustainable Progression Over Aggressive Ramping

This is not to minimize volume; we know it must increase over years to maximize potential. However, the rate of increase must be sustainable. Traditional models often ramp from, say, 50–60 hours/month in May to 100–120 hours/month in November—expecting a magical performance gain in racing season. This assumes each month provides sufficient adaptation to support the next. My experience says otherwise. The performance gains were often unsustainable and unpredictable.

Let’s consider a typical monthly ramp of 50 hours:

• Week 1: 11.25 hours
• Week 2: 13.25 hours
• Week 3: 15.25 hours
• Week 4 (recovery): 10.25 hours

This assumes athletes can adapt weekly to rising loads—something I strongly question. While the body adapts quickly to an appropriate load, that doesn’t mean it can adapt to increased loads every seven days.

Real-World Data: A More Effective Model

I’ve observed many athletes, especially skiers, push ramp rates aggressively—often at camps. They train 30–40% more load than usual. But based on HRV data, by the time they recover from these camps, much of the benefit is lost. This will be especially problematic for junior skiers who have not yet had the years of aerobic training and the ability to adapt to these big loads is a serious challenge.

In contrast, consider the case of a successful master’s cross-country skier:

• Training load increased from 500 to 600 TRIMP/week over a full year (~20% increase).
• That equates to ~10 TRIMP per week, or just 8 minutes of easy training or 2 minutes of high-intensity work—virtually nothing.
• Yet their performance and testing data steadily improved throughout the season.

In the following year, this athlete started at 600 TRIMP/week and progressed to 700–750 TRIMP/week, building on last year’s base. Because recovery was well managed, no long offseason break was needed. HRV data (RMSSD) stayed in a tight normal range throughout the season, except for two brief illness-related dips—indicating effective recovery and adaptation.

I’ve observed this same pattern in cross-country skiers, national champion mountain bikers, and high-level triathletes.

Elite-Level Patterns

This trend is supported by data from elite Scandinavian cross-country skiers. These athletes train 80–100 hours per month with very small month-to-month variation. The goal for most skiers is to have 100-120 high intensity sessions per year. So, the high-intensity sessions are a consistent part of the plan, with total training load increases coming primarily from slight upticks in intensity—not volume.

Conclusion

Based on what I’ve experienced and observed, I question the necessity of aggressive ramp rates, especially in terms of volume and distance. With effective training, performance improves in pace, speed, or power at a gradual rate. That itself represents a form of ramping—but one that’s based on output, not input, and one that’s sustainable.