Training Adaptations in Cycling Gross Efficiency (GE): A Study on the Impact of Pedaling Technique on Energy Expenditure

Two riders with identical VO2max can perform vastly differently—the key lies in “exercise economy”—how much oxygen is consumed to produce the same power output. Gross Efficiency (GE) quantifies the conversion ratio between mechanical work and metabolic energy.

This article, grounded in research from leading international academic journals, systematically unpacks the scientific underpinnings of cycling gross efficiency and exercise economy. We will start from the methods and findings of key papers, delve into the underlying physiological mechanisms, quantify the relationship between training dose and effect, compare differences across populations, and ultimately translate these academic findings into actionable training recommendations that Taiwanese endurance athletes can implement immediately. This is not merely a compilation of knowledge; it is a practical map leading from the laboratory to the training ground. In an era where it is difficult to distinguish truth from falsehood, returning to rigorous scientific evidence is the most worthwhile investment for any athlete who takes their training seriously.

Review of Academic Research

The most effective way to understand this topic is to directly examine representative studies from leading international journals. Below, we have compiled several papers that are either landmark contributions or methodologically rigorous, each building our current scientific understanding from different angles.

1. Coyle et al. (1992, MSSE)

This study employed elite rider efficiency research. More efficient riders maintained the same power output at a lower VO2. The value of this study lies in its systematic approach to testing hypotheses, providing a quantifiable basis for subsequent training prescriptions, and allowing us to move beyond the ambiguity of rule-of-thumb practices.

2. Lucia et al. (2002, MSSE)

This study employed GE analysis of professional cyclists. Top-tier cyclists can achieve a GE of 23–24%. The value of this study lies in its systematic approach to testing hypotheses, providing a quantifiable basis for subsequent training prescriptions, and allowing us to move beyond the ambiguity of rule-of-thumb practices.

3. Hopker et al. (2010, MSSE)

This study examined the effect of training on GE. One season of training significantly improved GE. The value of this study lies in its systematic approach to testing hypotheses, providing a quantifiable basis for subsequent training prescriptions, and allowing us to move beyond the ambiguity of rule-of-thumb practices.

4. Moseley and Jeukendrup (2001, JSS)

This study examined the reliability of GE measurement. It established standards for steady-state testing. The value of this study lies in its systematic approach to testing hypotheses, providing a quantifiable basis for subsequent training prescriptions, and allowing us to move beyond the ambiguity of rule-of-thumb practices.

Looking across the aforementioned literature, a common trend emerges: contemporary sports science increasingly emphasizes replacing intuition with objective data and rigorous experimental design. These studies echo and reinforce one another, collectively pointing to consistent core conclusions, giving us greater confidence when formulating training strategies. The next section will delve into the physiological mechanisms behind these phenomena.

Synthesis of Core Findings

Human cycling gross efficiency is approximately 18–24%, with elite cyclists at the higher end. GE can improve progressively with years of training, partly due to improvements in muscle fiber oxidative characteristics and pedaling coordination. For every 1 percentage point improvement in efficiency, the metabolic cost at the same power output decreases noticeably, which has a profound impact on long-distance performance.

It is worth emphasizing that these findings are not isolated laboratory numbers, but robust conclusions repeatedly validated across different populations and research designs. Precisely because of this, they can serve as the scientific cornerstone of training prescriptions. However, between “research findings” and “training application,” there lies a layer of mechanistic understanding—only by figuring out the “why” can we make correct adjustments when faced with individual differences and on-the-ground variables, rather than rigidly applying numbers. This is also the critical dividing line that separates “executors who follow a plan mechanically” from “athletes who truly understand training”—the former merely replicates workout schedules, while the latter can flexibly adjust every training decision based on their own condition, environmental changes, and race demands, maximizing the benefit of limited time and energy.

Core Physiological Mechanisms

Behind any training adaptation, a cascade of physiological changes operates across molecular, cellular, and organ-system levels. Understanding these mechanisms helps us determine which training methods truly address the limiting factors of performance and which merely add fatigue with limited benefit. The table below summarizes the key physiological mechanisms closely related to this topic and their effects:

Mechanism/Adaptation	Physiological Change	Effect on Performance
Muscle fiber oxidation↑	Type I proportion and enzymes	More economical energy conversion
Pedaling coordination	Neuromuscular efficiency	Reduced wasted work
Mitochondrial efficiency	ATP production rate	Lower VO2 cost

These mechanisms do not operate independently but are interwoven into a holistic network that influences one another. For example, without a simultaneous improvement in peripheral muscle metabolic capacity, the increased oxygen delivery from central cardiovascular adaptations cannot be effectively utilized; and vice versa. This “barrel effect” reminds us that comprehensive and balanced training stimuli often yield more lasting progress than extreme focus on a single point.

More importantly, the “timing” of these adaptations varies. Some changes (such as plasma volume expansion, neural coordination) can manifest within days to weeks, while others (such as cardiac structural remodeling, skeletal adaptations) require months or even years of accumulation. Understanding this temporal dimension helps us maintain reasonable expectations for training outcomes, avoiding the mistake of declaring a method ineffective before giving it sufficient time—a key reason why many people give up halfway.

Training Dose-Response Relationship

“How much should I train?” is the question every athlete cares about most. Sports science answers this using the concept of “dose-response”—there is a quantifiable relationship between training variables (intensity, frequency, duration, total volume) and the magnitude of adaptation, but this relationship is almost never simply linear. Understanding the shape of the dose-response curve helps us find the “sweet spot” with the highest return on investment, avoiding undertraining or overtraining.

The table below summarizes dose recommendations and expected effects under different scenarios as a reference for practical planning:

Population/Scenario	Recommended Dose	Expected Effect
Multi-year training	Progressive GE improvement	Long-term adaptation
High-cadence training	Improved coordination	Technical efficiency
Strength supplementation	Pedaling stiffness	Power transfer

Several general principles can be drawn from the table. First, diminishing marginal returns: as fitness levels rise, the training stimulus required to achieve the same magnitude of improvement grows larger, which is why elite athletes’ progress is often measured in “fractions of a percent.” Second, ceiling effect: beyond a certain threshold, additional training volume not only yields sharply diminishing returns but may even backfire due to fatigue accumulation. Third, individual thresholds: the minimum effective dose required to trigger adaptation differs for each person, which explains why the same training plan produces vastly different results across individuals.

Therefore, the smartest training strategy is not blindly pursuing “more,” but rather pursuing “just right”—providing sufficient stimulus to trigger adaptation, paired with adequate recovery to allow the adaptation to actually occur. Periodization is designed precisely to achieve this goal: through planned fluctuations in load, it avoids linear fatigue accumulation and allows the body to peak at critical moments.

Differences Across Populations

Research on gross efficiency and exercise economy in cycling repeatedly surfaces a theme that cannot be ignored: individual and population differences. Applying the same conclusions indiscriminately to everyone is one of the most common errors in training prescription. Below, we analyze these differences across several key dimensions.

Beginners vs. Advanced Athletes: Because beginners are still far from their physiological ceiling, almost any regular stimulus produces a significant response—the so-called “beginner’s bonus.” Advanced athletes, by contrast, have limited adaptive capacity and require more precise, higher-intensity, or more varied stimuli to keep improving. This means the optimal training strategies for the two groups are fundamentally different. Advanced athletes especially need to prioritize training “quality” and “specificity” rather than simply stacking “volume.”

Male vs. Female: In absolute values (such as absolute VO2max, muscle mass, and hemoglobin concentration), men generally exceed women, largely due to differences in body size, hormones, and body composition. However, in “relative training responses” (percentage-based improvements), the differences between sexes are often insignificant—women benefit just as fully from various types of training. Notably, the menstrual cycle, hormonal fluctuations, and energy availability (RED-S risk) in female athletes need special consideration in training planning.

Age Differences: With advancing age, maximal heart rate, muscle mass, recovery speed, and the hormonal environment all change. Yet a large body of research confirms that even middle-aged and older populations retain the capacity to adapt to training—it may just be slower and require more recovery. In other words, the idea that “training is useless when you’re older” is a complete myth. Older adults, in fact, need regular training even more to combat sarcopenia, bone loss, and declining cardiorespiratory function.

Genetic Factors: Don’t forget the “responder–non-responder” phenomenon. Large family studies indicate that a considerable proportion of training response can be explained by genetics. This means that, given the same training plan, some people improve dramatically while others progress slowly—often not due to a lack of effort, but to inherent differences in response potential. Recognizing this helps athletes view their own and others’ progress with a healthier mindset and become more willing to experiment with different training modes to find the stimulus that suits them.

Practical Training Applications

The value of theory lies in guiding practice. Translating research findings on gross efficiency and exercise economy into daily executable training requires grasping three core principles: “specificity,” “progression,” and “monitorability.”

The Specificity Principle: Training must target the energy systems and physiological adaptations required by the goal. If the goal is long-distance endurance, substantial aerobic base training is needed; if the goal is to break through VO2max limits, high-intensity interval stimuli are required. The most common problem with aimless training is falling into the “moderate-intensity black hole”—every session is somewhat breathless but not hard enough, failing to accumulate an effective aerobic base while also missing the key high-intensity stimulus, ultimately leading to stagnation.

The Progression Principle: The body adapts only when faced with loads slightly above current capacity, but load increases must be gradual. A practical guideline is to keep weekly training volume increases within roughly 10%, and schedule a deload week every 3–4 weeks to allow accumulated fatigue to dissipate and adaptations to consolidate. Rushing progress is the number one cause of injury and overtraining in amateur athletes.

The Monitorability Principle: Replacing subjective feelings with objective data is the core of modern training. We recommend establishing the following monitoring habits:

• Morning resting heart rate and heart rate variability (HRV): These reflect recovery status and autonomic nervous system balance. An abnormally elevated resting heart rate or a sudden drop in HRV is a warning sign of fatigue.
• Power or pace: Tracking output at the same intensity under standardized conditions is the most objective way to assess fitness progression.
• Subjective fatigue and sleep quality: Simple daily self-ratings capture overall status beyond the numbers.
• Periodic testing: Every 6–12 weeks, perform a standardized test (such as threshold power or a time trial) to objectively evaluate training effectiveness and adjust accordingly.

Integrating these principles, a mature training plan should be “built on a large volume of low-intensity work to establish a base, driven upward by a small amount of high-intensity work, consolidated by adequate recovery, and navigated by objective data.” Rather than blindly chasing mileage numbers every day, it is better to execute 1–2 high-quality sessions per week with discipline and truly relax the rest of the time—this is the essence of quality over quantity.

Local Applications in Taiwan

Taiwanese cyclists often neglect efficiency training and over-chase power numbers. Incorporating single-leg pedaling drills, fixed cadence rhythms, and core strength can improve performance without increasing VO2max. Long climbs are an excellent setting for testing efficiency.

Taiwan’s unique geography and climate mean that conclusions from international research must be localized before application. The hot, humid summers, mountainous terrain, and dense, diverse racing culture are both challenges and advantages. Knowing how to leverage high-altitude resources such as Hehuan Mountain and Wuling for altitude stimulus, how to manage heat adaptation and fluid/electrolyte replacement in humid heat, and how to adjust training priorities based on the characteristics of Taiwanese races (such as a high climbing proportion) allows Taiwanese endurance athletes to turn local conditions into a competitive edge. Remember, any data from laboratories in temperate countries must be interpreted and applied against Taiwan’s real training environment—this is the final mile for scientific training to take root locally.

Debunking Common Myths

There is often a considerable gap between scientific findings and popular beliefs. Many “common wisdoms” widely circulated in the cycling community do not hold up to empirical scrutiny. Below, we debunk the myths most relevant to this topic:

Myth 1: Efficiency cannot be trained.

In reality, years of training can significantly improve GE. Blindly believing such myths wastes training time and energy at best, and leads to fatigue, stagnation, or even injury at worst.

Myth 2: Higher cadence is always more economical.

In reality, the optimal cadence varies from person to person. Blindly believing such myths wastes training time and energy at best, and leads to fatigue, stagnation, or even injury at worst.

Myth 3: As long as the power is sufficient, that’s all that matters.

In reality, at the same power output, efficiency determines the metabolic burden. Blindly believing such myths wastes training time and energy at best, and leads to fatigue, stagnation, or even injury at worst.

The key to breaking myths lies in cultivating the habit of “demanding evidence.” Whenever you hear any training claim, ask yourself: “What research supports this? Which population does it apply to?” Only by grounding decisions in evidence can you avoid plausible-but-wrong traps in an age of information overload and make truly beneficial training decisions.

Conclusion: From Evidence to Action

Looking across the academic research on gross efficiency and exercise economy in cycling, several clear conclusions emerge. First, endurance performance is the result of multiple physiological systems working in concert—no single metric or training method holds a monopoly on the key to success. Second, the essence of training is “precise stress plus adequate recovery,” not merely the accumulation of effort. Third, individual differences are everywhere; the best training plan is always the one “tailored to yourself and continuously adjusted based on data.”

Looking ahead, sports science is rapidly moving toward “precision individualization.” Advances in genomics, metabolomics, and wearable devices will eventually allow us to predict an individual’s response potential before training even begins and to fine-tune every session in real time based on physiological data. For Taiwanese athletes and coaches, building a local physiological database and developing training models adapted to the local climate and race calendar are crucial steps toward closing the gap with the world’s best.

For every reader, the most important action item remains the same: First, understand your physiological baseline through objective testing; then design training based on scientific principles; pair it with disciplined recovery and continuous monitoring; and be patient with progress. There is no shortcut to building endurance, but there is a right direction. May this science-based analysis serve as a reliable guide on your training journey, accompanying you as you pursue your limits while also enjoying the purest joy of sport.

Related Reading

• Pedaling Efficiency: The Energy Ledger of Pedaling Mechanics and Muscle Contraction
• Quantifying Cycling Efficiency (GE/PE): How to Become a More Economical Rider
• Measuring and Improving Gross Efficiency: The Energy Conversion Rate of Pedaling Technique
• The Science of Cycling Efficiency: A Comprehensive Analysis of Pedaling Technique, Aerodynamics, and Equipment