Shownotes

Intensity as a percentage of Threshold

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• Using percentages of threshold is a widely recognised and effective method for prescribing workout intensities. Typically, this involves anchoring your training to a key performance metric like Functional Threshold Power (FTP) for cycling, pace thresholds for running, or threshold pace in swimming.

Cycling

• In cycling, FTP serves as the reference point. For example, with an FTP of 300 watts, 90% (270 watts) would be considered a "sweet spot" intensity. Similarly, 120% of FTP (360 watts) is a typical range for VO2max intervals.
• These percentages allow for scalable, relative training intensities suited to various performance levels. Importantly, FTP isn’t a single number but a range, making this approach flexible and adaptable across athletes.

Running

• In running, percentages of threshold are applied differently because intensity is based on pace rather than power. The narrower range of functional speeds compared to cycling makes adjustments more precise but still follows the same principle.
• A threshold-based system ensures workouts are tailored to an individual’s capacity, promoting consistency and relevance across different performance levels.

Swimming

• Swimming deviates from the percentage-based approach. Instead, training intensities are often prescribed as threshold pace plus or minus a specific time per 100 metres. This method is less about percentages and more about adding or subtracting seconds to create training zones. While effective, it’s less scalable and relative than the percentage-based systems used in cycling and running.

Benefits of the Threshold-Based Approach

• Performance Prediction - Anchoring training to the second threshold (commonly referred to as "threshold") provides a strong predictor of endurance performance for events from 5k runs to Ironman triathlons. While VO2max might be more relevant for short, high-intensity efforts like 1500-metre races or individual pursuits, threshold is better suited to endurance-focused athletes. For ultra-endurance events (e.g., over four hours), the first threshold (LT1) might be a better anchor, but threshold remains a practical middle ground for most.
• Scalability Across Athletes - By using percentages, training prescriptions are scalable and comparable across vastly different performance levels. For instance, a cyclist with an FTP of 175 watts doing intervals at 160 watts (91% FTP) is engaging in a similar effort, relative to their ability, as a cyclist with a 450-watt FTP doing intervals at 410 watts. This scalability is invaluable for coaches and self-coached athletes alike.
• Simplicity and Accessibility - The simplicity of this method has democratized knowledge within endurance sports, particularly in cycling and triathlon. Many athletes, even those who are self-coached, have a strong understanding of the physiological implications of different percentages of threshold. This widespread comprehension fosters a more informed community of athletes.
• Adaptability to Training Levels - For athletes far from their genetic or realistic potential, this approach works well due to its broad applicability. The closer an athlete gets to their limits, the more precise their training must be. However, the percentage-based method still provides effective results across a spectrum of abilities.

Disadvantages of this training approach

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• For elite athletes who are nearing their genetic potential, the precision of workouts prescribed as percentages of threshold (e.g., 90% or 80%) often lacks the granularity required to further enhance performance.
• These athletes need hyper-targeted approaches to find marginal gains, and the generalised nature of the classic model may fail to provide the precision needed for progress.
• At the other end of the spectrum, athletes with very low threshold powers or paces face a different challenge. The perceived differentiation between workouts at 90% and 80% of threshold may be as little as 10 watts.
• This tiny difference has virtually no physiological significance, rendering the classic model ineffective for creating meaningful workout distinctions. In these cases, individualisation is also necessary, but it leans towards simplification rather than greater precision.
• Physiological outliers, particularly those with unique muscle fibre compositions, also face challenges. For athletes with a strong glycolytic capacity or "fast-twitch" profiles, traditional percentages of threshold often lead to overtraining.
• The prescribed intensities may simply be too high, requiring a recalibration of thresholds to avoid excessive strain. For instance, a workout prescribed at 90% of threshold for an average endurance athlete might need to be set at 80% for a fast-twitch athlete to elicit the same physiological effect.
• Conversely, for slow-twitch-dominant athletes with minimal glycolytic capacity, the classic model also falls short, though the risks differ.
• Overtraining is less of a concern for these athletes, but the potential for ineffective training is just as significant. Without proper adjustments, their workouts may lack the intensity needed to stimulate improvement.
• Another disadvantage arises when athletes reach plateaus in their development. This often happens after years of consistent training or when time constraints limit their ability to add training volume.
• For time-crunched athletes, optimising the intensity of every session becomes critical. The classic model may not allow them to extract the maximum stimulus from their key workouts, which is essential for continued progress.

Who should not follow this methodology?

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•  Edge-case performers: Athletes who are either at very high or very low thresholds and performance levels.
• Edge-case physiological profiles: Those near the extremes of the fast-twitch to slow-twitch muscle fibre spectrum.
• Plateaued, time-limited athletes: Individuals who have hit a plateau in their development, despite doing most things right. They sleep well, eat properly, follow a well-structured training plan, and execute it effectively, but they lack additional time to invest in training to break through their stagnation.
• This approach helps avoid overtraining or undertraining, striking the right balance to maximise performance. The goal is to push hard but not so hard that it compromises your ability to replicate the effort a few days later—or even progress further. By maintaining this consistency, you create a sustainable cycle of effort and recovery that enhances long-term gains.
• This methodology reduces the need for frequent formal testing by leveraging training and racing data to guide decisions. It enables you to evaluate performance trends over months—sometimes a full year—of data, providing a more accurate and dynamic view of your optimal training zones.
• Formal testing remains valuable but becomes more supplementary. Instead of relying on a single test as the definitive metric, this approach incorporates tests as one element within a broader data-driven framework. This allows for more flexibility and continuity in planning, reducing the need to retest every 8 to 12 weeks.
• By shifting focus to the patterns within your training data, you gain a stronger foundation for planning, resulting in better overall outcomes without the constant need for testing recalibrations.

Establish a Performance profile

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• A performance profile provides a comprehensive picture of an athlete's capabilities over various durations and is derived from metrics like the power duration curve or speed duration curve.
• While a power duration curve maps the maximum power output across all durations—from a single second to several hours—the performance profile goes further. It focuses on specific durations, typically five minutes, thirty minutes, sixty minutes, and durations relevant to key races, analysing the top three to five mean maximal performances for each.
• The power duration curve shows the peak power outputs for different durations, forming a gradually declining curve. Short durations see steep declines, while longer durations taper off more gently.
• A similar concept applies to the speed duration curve in running or swimming. These curves offer valuable insights, but they represent only the single best output for each duration, potentially overlooking context and trends.
• Instead of focusing solely on the best output for a given duration, the performance profile evaluates the top three to five outputs to assess consistency and reliability.
• This helps identify whether the top result is a genuine reflection of ability or an outlier. For instance, if one exceptional performance significantly surpasses others, its validity should be questioned—context is critical.
• The five-minute mean maximal power (or speed) serves as a proxy for maximum aerobic power or speed, making it an essential benchmark for VO2 max-focused interval workouts.
• Meanwhile, 30- and 60-minute outputs correspond to upper and lower thresholds, respectively. These thresholds help define training intensities and offer a nuanced understanding of an athlete’s performance range.
• Performance data must always be contextualised. For example, a personal best achieved during a training camp in different conditions (e.g., outdoor climbs in Mallorca) might not reflect what is achievable in regular training environments.
• Similarly, outdated performances (e.g., nearly a year old) may not represent current fitness levels. By considering multiple data points, the profile can better reflect current capabilities and set realistic targets.
• Use five-minute outputs for VO2 max workouts, 30-minute outputs for upper threshold efforts, and 60-minute outputs for lower threshold efforts.
• Analyse race-specific durations to assess the feasibility of goals. For instance, if an athlete plans to maintain 250 watts during a 4.5-hour Ironman bike leg but their historical data shows a maximum of 200 watts for that duration, they might need to adjust their target or perform additional benchmark tests.
• The profile combines art and science, blending hard data with coaching experience to adjust and average results. This process creates a more realistic and actionable performance framework tailored to the individual.

Limitations of this approach

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• Firstly, your profile will only be reliable if you’ve performed near-maximal efforts across various durations. While these don’t need to be absolutely maximal, they must be hard enough to provide a meaningful dataset.
• The power or pace difference between near-maximal and maximal efforts is usually negligible, making near-maximal efforts suitable.
• Activities like racing over different distances—whether triathlons, running races, Zwift events, or other hard training sessions (around 9 out of 10 on the RPE scale)—can provide sufficient data.
• These races not only enhance your performance but also give a clearer understanding of your capabilities.
• Cycling data is typically more comprehensive because of the availability of mean max power values over a range of durations. However, running data tends to be limited. Runners often lack detailed speed-duration curves unless they’ve raced across multiple distances.
• In training, maximal running efforts might be restricted to short intervals or occasional 5k/10k races, leaving longer durations like one-hour efforts underrepresented.
• To address this, I recommend basing your running performance profile on paces for established distances such as 5k, 10k, half-marathon, or marathon.
• However, instead of racing all these distances, you can use two races of different lengths (e.g., a 5k and a 10k) and calculate estimated paces for other distances using the Riegel formula.
• This method involves plugging your race times into a tool or AI platform to compute your personalised Riegel exponent, which accounts for your individual fatigue rate between distances.
• The formula then estimates times for other distances like half-marathons and marathons.
• This approach is distinct from critical speed tests, which require all efforts to fall within the severe intensity domain (e.g., durations up to 20 minutes). The Riegel formula instead leverages empirical data and your own decay rate to provide a customised prediction.
• Unlike calculators based on standardised group averages, this method tailors paces to your unique physiology, yielding more accurate targets.
• Finally, while AI tools can simplify calculations, they cannot contextualise anomalies in your data—such as an outlier outdoor power result if most of your training is indoors.
• This highlights the importance of a coach or self-education to interpret data meaningfully, ensuring training targets align with your real-world capabilities and environment.

Structure training

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• When structuring your training, always treat initial plans and intensity targets as starting points. As you progress through the process, your workouts themselves provide valuable feedback to fine-tune future sessions.
• For example, if you repeatedly complete a VO2 max workout, such as five intervals of four minutes at 95% of your five-minute power, and find it easier the second time, it might indicate you should increase the target by 5–10 watts for the next session.
• At that stage, percentages become less relevant, and adjustments are made in absolute terms based on recent performance.
• Threshold or race-pace workouts, however, progress differently. Instead of increasing intensity, focus on extending the time spent on the target effort.
• Even with these guidelines, it’s essential to critically evaluate the effectiveness of your initial intensity settings. There’s no universally perfect formula, so staying engaged with your training process and correcting any missteps is crucial. This iterative approach ensures continual progress and alignment with your physiological needs.
• While some may argue that this feedback-based process could replace formal target-setting—such as repeating a standardised workout like 4x20 minutes and adjusting based on feel—there’s merit to both methods. For experienced athletes, it’s relatively easy to discern the threshold or sweet spot range.
• Yet, this approach might not yield the same benefits at the extremes of the intensity spectrum. For higher-intensity efforts, like VO2 max workouts, individual variability, particularly in glycolytic energy production, plays a significant role.
• Similarly, at lower intensities, like Ironman or marathon pace, durability becomes critical. Training too fast at these intensities can hinder total volume and duration accumulation, limiting effectiveness.
• If you’re plateauing, consider recalibrating your approach to intensity. For some, perceived effort at specific intensities may not align with physiological reality, and relying solely on feel might perpetuate stagnation.
• A structured, data-informed target-setting approach, balanced with feedback from your body, can help break through performance barriers.
• A final overarching principle is to work within a range of power or speed rather than fixating on a single number. For instance, aim for a 15-watt power range or a pace range of 10 seconds per kilometre.
• When I mention a specific power or pace, it’s always with the assumption that it represents the midpoint of such a range. This flexibility accounts for daily variations in performance, ensuring a more sustainable and effective training process.

Set intensity targets based on the performance profile

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• Threshold training is more nuanced and involves working within a range rather than aiming for a single value.
• In cycling, use your 30–60 minute mean maximum power (MMP) as the range. The 60-minute MMP is closer to sweet spot or MLSS (Maximal Lactate Steady State). The 30-minute MMP aligns with critical power.
• Athletes with a fast-twitch bias should train at the lower end of this range, while "diesel engine" athletes (endurance-focused) can target the higher end.
• For general fitness, start with longer intervals at the lower end of the range, progressing to shorter, higher-intensity intervals (linear periodisation).
• For race-specific preparation, reverse this (e.g., shorter, high-intensity intervals first, transitioning to longer, lower-intensity intervals).
• This approach aligns your training to your physiological needs and the demands of your event.
• For Faster Runners (Half Marathon <1:20), threshold pace is between your 10K and half-marathon paces.
• For Slower Runners (Half Marathon >2:00), threshold pace ranges from your 5K to 10K paces.
• For Mid-Level Runners, split the difference, anchoring efforts around race durations.
• Treat threshold as a flexible range rather than a fixed FTP or pace.
• Tailor workouts to your physiological profile, with shorter intervals at higher intensities and longer intervals at lower intensities.
• Use race duration rather than distance to define intensity, especially in running.
• Match your training intensity and progression to your goals, whether improving physiology or preparing for a specific event.

Applications for triathlon

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• In triathlon, achieving race pace goals, particularly for running and cycling, requires a well-thought-out strategy that factors in training, pacing, and data analysis.
• For well-trained athletes, a strong goal is to match your triathlon race pace to the pace you'd achieve in a running race over one distance longer.
• For Olympic Distance, aim to match your triathlon run pace to your half-marathon race pace.
• For 70.3 (Half Ironman), your triathlon run pace should approximate your pure marathon pace.
• For Ironman, Add roughly 20 seconds per kilometre (or 30 seconds per mile) to your 70.3 run pace.
• This goal is ambitious and serves as a stretch target for most athletes, particularly age-groupers. It’s vital to train to these targets but approach race day with a more conservative strategy.
• Start at a manageable pace, reassess how you feel mid-race, and pick up the pace if possible. Running too aggressively at the start often leads to suboptimal performance.
• If you’re consistently falling short of these targets, especially in shorter distances like 70.3, it’s a sign to reassess.
• Review your swim and bike efforts—were they too intense? Are you fuelling effectively during the race? Is your training sufficiently building your resilience for running off the bike?
• For most athletes, achieving these targets is realistic with proper pacing, nutrition, and durability focus.
• Cycling presents unique challenges because long-duration power data isn’t always readily available.
• Review two full years of power data to establish a reliable performance baseline. If your performance is stable, a single year may suffice.
• Use power data from durations 20-25% shorter than your target race duration to set realistic training targets.
• For a 5-hour Ironman bike leg, analyse your mean max power for 3 hours 45 minutes to 4 hours.
• For a 2-hour 30-minute 70.3 bike leg, examine power over 1 hour 52 minutes to 2 hours.
• By focusing on slightly shorter durations, you ensure your power targets are more manageable during training, which helps build confidence and capacity for race day.
• While this data informs your race strategy, your actual training sessions at these target powers are the most critical factor in determining race-day success. Completing Ironman-specific rides at race power in training is the best predictor of your capability on race day.
• These approaches are not one-size-fits-all. Tailor them to your context, coaching experience, and available data. Experimentation and refinement are often necessary to find what works best for you.

Swimming considerations

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• When it comes to swimming, the approach differs significantly compared to other endurance sports due to its highly technical nature.
• While there is some value in anchoring VO2 max intervals to a 400-metre or yard time trial and threshold intervals to a 1000-2000-metre or yard time trial, this methodology isn’t as critical in swimming as in other disciplines. These time trials can provide useful benchmarks, but they are not absolutely necessary.
• They come with a low physiological cost but may pose a higher psychological challenge depending on the individual.
• The primary reason for this difference lies in the technical complexity of swimming and the lack of immediate pacing feedback while in the water.
• Unlike cycling or running, where pace targets can be instrumental, in swimming, strict pace targets can sometimes be counterproductive. They may lead athletes to fight the water rather than focus on maintaining good technique and optimal effort.
• Having reference points—such as comparing your 50-metre intervals to a 400-metre time trial or a 300-metre threshold set to a 1500-metre time trial—is invaluable. These benchmarks help identify whether specific workouts were unusually fast or slow, providing insights into overall performance trends.
• However, rather than prescribing workouts strictly by pace, I generally recommend using RPE (Rate of Perceived Exertion) as the guiding input for swim training.
• During workouts, the pace remains an essential metric, but it serves more as an output for analysis rather than the primary focus during the session.
• Regularly checking your average interval pace provides real-time feedback, enabling you to observe how slight technical adjustments can result in faster swimming for the same effort level. This practice fosters greater engagement in the process and reinforces awareness of where you typically fall on the RPE scale.

Conclusions and Takeaways

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• This methodology isn’t designed to make you abandon one way of thinking for another but rather to offer a better starting point for setting target intensities.
• It can help you avoid wasted effort, particularly if your physiological or performance profile is far from the average. However, it’s crucial to avoid treating these guidelines as strict rules.
• Coaching involves a lot of nuance, and if you’re self-coached, you need to actively engage in tailoring this approach to suit your unique needs. Context is always paramount.
• Using percentages of your threshold to set intensity targets works well for most athletes. If this method is helping you progress, there’s no need to complicate things.
• However, if you’ve hit a plateau or face issues like overtraining, consider this alternative methodology. It’s especially useful for optimising and individualising your training.
• Optimising intensity requires using anchor points specific to each workout type. For example, prescribing VO2 max workouts based on a percentage of your threshold power isn’t ideal—it may work on average but lacks individual precision. Instead, use metrics like five-minute mean max power for VO2 max sessions.
• This ensures your intensity aligns more closely with your physiological capacities.
• Developing a critical performance profile involves focusing on power or speed outputs at key durations, and creating a personalised power-duration or speed-duration curve.
• For runners, using two races of varying distances (e.g., 5k and 10k) and applying the Riegel formula with an individualised exponent is an effective method. If you’re unsure how to apply this, tools like ChatGPT can simplify the process for you.
• Short-distance triathlons (sprint and Olympic), running races of various distances, and bike races (including virtual ones) can provide valuable data for refining your performance profile.
• These events can help you better understand and optimise your intensity targets. However, balance is key—don’t race excessively, but avoid racing too little. For age-group athletes, insufficient racing is often a more common issue than over-racing.

LINKS AND RESOURCES:

• Separating evidence from hype in endurance sports (Mikael interviewed on the Endurance Innovation podcast)
• Mallorca Training Camp 2025 
• Portugal Training Camp 2025