Scientific Validity of Functional Threshold Power (FTP): A Correlation Study with MLSS

FTP (Functional Threshold Power) is the most widely used metric in cycling training, defined as the maximum average power sustainable for approximately one hour, commonly estimated via a 20-minute test multiplied by 0.95. However, the relationship between FTP and the laboratory gold standard MLSS warrants scrutiny regarding its validity.

This article systematically analyzes the scientific validity of FTP based on research from leading international academic journals. 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 for Taiwanese endurance athletes. This is not merely a compilation of knowledge, but a practical map leading from the laboratory to the training ground. In an era where distinguishing truth from falsehood is challenging, returning to rigorous scientific evidence is the most worthwhile investment for any athlete who takes training seriously.

Academic Research Review

The most effective way to understand this topic is to directly examine representative studies from leading international journals. Below, we have compiled several landmark or methodologically rigorous papers that collectively construct our current scientific understanding from different perspectives.

1. Allen and Coggan (Book/Concept)

This work introduced the FTP training concept, establishing FTP as the basis for training zones. The value of this work lies in its systematic approach to examining hypotheses, providing a quantifiable basis for subsequent training prescriptions, and moving us beyond the ambiguity of rule-of-thumb methods.

2. Borszcz et al. (2018, IJSPP)

This study compared FTP with MLSS. The 20-min × 0.95 estimate of FTP differed from MLSS. The value of this study lies in its systematic approach to testing hypotheses, providing a quantifiable basis for subsequent training prescriptions, and moving us beyond the ambiguity of rule-of-thumb methods.

3. Valenzuela et al. (2018, IJSPP)

This study examined the validity of FTP. FTP correlated with other thresholds but was not equivalent to them. The value of this study lies in its systematic approach to testing hypotheses, providing a quantifiable basis for subsequent training prescriptions, and moving us beyond the ambiguity of rule-of-thumb methods.

4. Morgan et al. (2019, JSS)

This study examined the reliability of FTP testing. FTP was reliable but influenced by the testing protocol. The value of this study lies in its systematic approach to testing hypotheses, providing a quantifiable basis for subsequent training prescriptions, and moving us beyond the ambiguity of rule-of-thumb methods.

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

Synthesis of Core Findings

FTP is highly correlated with MLSS and Critical Power, demonstrating acceptable validity as a practical training benchmark, but it is not precisely equivalent—the 20-min × 0.95 estimate can overestimate or underestimate true one-hour power for some riders. Its value lies in being field-based, low-cost, and repeatable, making it suitable for daily training zone prescription and progress tracking.

It is worth emphasizing that these findings are not isolated laboratory numbers but robust conclusions repeatedly validated across different populations and study designs. Precisely because of this, they can serve as the scientific cornerstone of training prescriptions. However, between “research findings” and “training application” lies a layer of mechanistic understanding—only by figuring out the “why” can we make correct adjustments when faced with individual differences and real-world variables, rather than rigidly applying numbers. This is also the critical divide separating “executors who follow a plan blindly” from “athletes who truly understand training”—the former merely replicate workouts, while the latter can flexibly modify 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 every training adaptation lies a cascade of physiological changes operating from the molecular and cellular levels up to the organ system level. Understanding these mechanisms helps us judge which training methods truly target 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	Impact on Performance
FTP ≈ sustainable power	Approximates MLSS/CP	Basis for training zones
20-min × 0.95	Field-based estimate	Subject to individual error
Anaerobic reserve differences	W’ influences estimate	Overestimation or underestimation

These mechanisms do not operate independently but are interwoven into a holistic network that influences each other. For example, without a simultaneous improvement in peripheral muscular metabolic capacity, 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) manifest within days to weeks, while others (such as cardiac structural remodeling, bone adaptations) require months or even years of accumulation. Understanding this temporal dimension helps us maintain reasonable expectations for training outcomes, avoiding the premature conclusion that a method is 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 most pressing question for every athlete. Sports science answers this using the concept of “dose-response”—a quantifiable relationship exists between training variables (intensity, frequency, duration, 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 organizes dose recommendations and expected effects for different scenarios as a reference for practical planning:

Population/Scenario	Recommended Dose	Expected Effect
FTP Test	20-min or ramp test	Feasible in the field
Training Zones	Based on %FTP	Basis for workout plans
Regular Retesting	Track progress	Adjust zones

Several general principles can be derived from the table. First, diminishing marginal returns: as fitness levels rise, the training stimulus required to achieve the same improvement becomes increasingly 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 benefits but may even be counterproductive due to fatigue accumulation. Third, individual thresholds: the minimum effective dose required to trigger adaptation varies from person to person, explaining why the same workout plan produces vastly different results in different individuals.

Therefore, the smartest training strategy is not blindly pursuing “more,” but 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, avoiding linear fatigue accumulation and allowing the body to peak at critical moments.

Differences Across Populations

A recurring and undeniable theme in research on the scientific validity of FTP is “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 from several key dimensions.

Beginners vs. Advanced Athletes: Beginners, being far from their physiological ceiling, respond significantly to almost any regular stimulus—the so-called “beginner’s bonus.” Highly trained athletes, however, have limited adaptive capacity and require more precise, higher-intensity, or more varied stimuli to continue progressing. This means the optimal training strategies for the two groups are fundamentally different; advanced athletes especially need to prioritize training “quality” and “specificity” over simply accumulating “quantity.”

Males vs. Females: In absolute values (such as absolute VO2max, muscle mass, hemoglobin concentration), males are generally higher than females, primarily due to differences in body size, hormones, and body composition. However, in “relative training responses” (percentage improvements), differences between sexes are often insignificant, and females benefit fully from various types of training. Notably, the menstrual cycle, hormonal fluctuations, and energy availability (RED-S risk) in females require special consideration in training planning.

Age Differences: With advancing age, maximal heart rate, muscle mass, recovery speed, and the hormonal environment all change. However, extensive research confirms that even in middle-aged and older populations, the capacity for training adaptation persists, though adaptation may be slower and require more adequate recovery. In other words, “it’s useless to train when you’re old” is a complete myth. Older individuals, in fact, need regular training even more to combat sarcopenia, bone loss, and cardiorespiratory decline.

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, meaning that faced with the same workout plan, some progress rapidly while others improve slowly—often not due to lack of effort but inherent differences in response potential. Recognizing this helps athletes maintain a healthier perspective on their own and others’ progress rates and encourages them to experiment with different training modes to find the stimulus that suits them.

Practical Training Application

The value of theory lies in guiding practice. Translating research findings on the scientific validity of FTP into daily executable training requires grasping three key principles: “Specificity,” “Progression,” and “Monitorability.”

Principle of Specificity: 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; to break through VO2max limits, targeted high-intensity interval stimuli are required. The most common problem with indiscriminate training is falling into the “moderate-intensity black hole”—each session is somewhat breathless but not hard enough, failing to effectively accumulate aerobic base while also not reaching the critical high-intensity stimulus, ultimately leading to stagnation.

Principle of Progression: The body only adapts when faced with loads slightly exceeding current capacity, but load increases must be gradual. A practical guideline is to keep “weekly training volume increases within approximately 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.

Principle of Monitorability: Replacing subjective feelings with objective data is the core of modern training. It is recommended to establish the following monitoring habits:

• Morning resting heart rate and heart rate variability (HRV): Reflect recovery status and autonomic nervous system balance; abnormally elevated resting heart rate or a sudden drop in HRV are warning signs of fatigue.
• Power or pace: Tracking output at a standardized intensity is the most objective way to assess fitness progress.
• Subjective fatigue and sleep quality: Simple daily self-assessments capture overall status beyond the numbers.
• Regular testing: Perform a standardized test (e.g., threshold power, time trial) every 6–12 weeks to objectively evaluate training effectiveness and adjust accordingly.

Integrating these principles, a mature training plan should be “building the base with high volume at low intensity, raising the ceiling with low volume at high intensity, consolidating adaptations with adequate recovery, and navigating direction with 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 Application in Taiwan

Almost every cyclist in Taiwan owns a power meter, and FTP is the core of smart trainer workouts. It is recommended to regularly (every 6–8 weeks) retest FTP and understand it as an “estimate” rather than absolute truth; those with high precision needs can further undergo MLSS or CP testing for calibration. High temperatures can lower test power, so testing should be done during cooler periods.

Taiwan’s unique geographical and climatic conditions necessitate local adaptation when applying conclusions from international research. The hot, humid summers, mountainous terrain, and dense, diverse racing culture are both challenges and advantages. By knowing how to utilize high-altitude resources like Hehuan Mountain and Wuling for altitude stimulus, how to implement heat acclimatization and proper hydration/electrolyte replacement in hot, humid environments, and how to adjust training focus based on the characteristics of Taiwanese races (such as a high proportion of climbing), Taiwanese endurance athletes can turn local conditions into a competitive advantage. Remember, any data from laboratories in temperate countries needs to 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 sense” notions widely circulated in the sports community do not withstand empirical scrutiny. Below, we debunk common myths related to this topic one by one:

Myth 1: FTP equals MLSS.

In reality, they are correlated but have systematic bias. Blindly believing such myths wastes training time and energy at best, and leads to fatigue, stagnation, or even injury at worst.

Myth 2: Higher FTP means better performance.

In reality, endurance and efficiency also need to be considered. Blindly believing such myths wastes training time and energy at best, and leads to fatigue, stagnation, or even injury at worst.

Myth 3: One FTP test is valid forever.

In reality, regular retesting is required for tracking. Blindly believing such myths wastes training time and energy at best, and leads to fatigue, stagnation, or even injury at worst.

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

Conclusion: From Evidence to Action

Reviewing the academic research on the scientific validity of FTP, we can draw several clear conclusions. First, endurance performance is the result of multiple physiological systems working in concert; no single metric or training method holds the exclusive key to success. Second, the essence of training is “precise stress plus adequate recovery,” not merely the accumulation of effort. Third, individual differences are omnipresent; the best training plan is always the one “tailored for yourself and continuously adjusted based on data.”

Looking ahead, sports science is rapidly advancing toward “precision individualization.” Advances in genomics, metabolomics, and wearable technology will eventually allow us to predict an individual’s response potential before training and fine-tune each 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 races are crucial steps toward closing the gap with the world’s elite.

Returning to each reader, the most important call to action remains unchanged: First, understand your physiological baseline through objective testing; then design your training based on scientific principles; pair it with disciplined recovery and continuous monitoring; and be patient with your progress. There are no shortcuts 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 in pursuing your limits while also enjoying the purest joy of sport.

Related Reading

• Comparison of Road Bike Power Testing Methods: Validity Study of FTP vs MAP vs 20-min Power
• The Physiological Mechanisms of Functional Threshold Power (FTP): A Detailed Analysis of the Lactate Balance Point
• 【Research Review】Correlation Analysis Between the 20-Minute Test Method for Functional Threshold Power (FTP) Detection and Aerobic Metabolic Threshold in Cycling: Biomechanical Quantification Experiment Report (No. 1106)
• 【Research Review】Correlation Analysis Between the 20-Minute Test Method for Functional Threshold Power (FTP) Detection and Aerobic Metabolic Threshold in Cycling: Biomechanical Quantification Experiment Report (No. 530)