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In cycling, riders tend to love looking at, and comparing, data. We track heart rate and power habitually now, and use it to direct training, pace ourselves in events, and deem if we are getting fitter. But there are a host of metrics that tend to go unobserved, but in reality can play a huge role in giving far more depth and clarity to the overall picture. I\u2019ve been a coach for nearly the last decade, and these are some of the key metrics in TrainingPeaks that people need to be paying more attention towards.<\/p>\n\n\n
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\n(Image credit: Future)<\/span><\/figcaption><\/figure>\nPower Duration Curve <\/h2>\n For as long as I have been cycling, the most commonly referred to metric when it comes to cycling performance is \u2018FTP\u2019, or functional threshold power. It\u2019s long been used as a bragging right on the club ride, what your 20 minute power is, and the mean by which many riders have set their intervals and pacing strategies off. But it misses the vast majority of the bigger picture.<\/p>\n
Given that many riders test FTP with a 20 or 60 minute maximum test, in reality it only tells you your sustainable power for those durations. Critical Power (CP) is a more widely adopted concept for power testing, especially by professional teams. This is because CP is a mathematical model which uses two effort durations, often 3-5min and 10-15min, to create a power curve. But this tends to be most accurate from 3-45 minutes.<\/p>\n
The issue is that shorter duration efforts require different energy systems, and CP is more an aerobic modelling system. Glycolytic efforts (1-3min) and phosphocreatine efforts (maximum sprints) use different energy systems. However, both of those efforts are key performance indicators. If you\u2019re doing road races, criteriums, or short hill climbs, then FTP\/CP means very little for those efforts. Peak sprint power and maximal 1 minute attacking efforts though tend to correlate far better to performance in those scenarios. This is why monitoring not just one or two power metrics is key, but the whole spectrum of your power profile is key. Your FTP\/CP may not increase, but your sprint might go up 200 watts. That would still show a significant amount of progress and likely result in increased performance in bunch races.<\/p>\n\n\n
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\n(Image credit: TrainingPeaks)<\/span><\/figcaption><\/figure>\ndFRC\/W\u2019\/Anaerobic capacity <\/h2>\n Similar in some ways to the above point, dFRC (Dynamic Functional Reserve Capacity) in WKO5 and TrainingPeaks \u2013 sometimes referred to as the Anaerobic Capacity\/Battery, or colloquially, the number of matches you have to burn \u2013 or its equivalent, Work Prime (W\u2019) is another highly useful metric that often goes underutilised.<\/p>\n
While CP is your power curve, your anaerobic capacity is the amount of workload that you can do above your CP. For example, if you have a CP of 300w, and a \u2018battery\u2019 of 20000 joules, you can sustain 400w for 3 minutes and 20 seconds. This is because 100w is 100 joules\/second, so 20000j is depleted in 200 seconds, or 3min20.<\/p>\n
In addition to this, your \u2018battery\u2019 needs time to recharge, so riding at 200w for 200 seconds should recharge the W\u2019 fully.<\/p>\n
This principle is referred to as W\u2019Bal, and has been used by practitioners and coaches to model performance within events. It\u2019s not perfect, and there is interesting research ongoing at the moment into decay and replenishment rates in fatigued athletes as well as different level athletes, but it presents an interesting model to use.<\/p>\n
Let\u2019s say we have two riders, both with an FTP of 300w. Rider A has an anaerobic capacity of 20000 joules, whereas rider B\u2019s is 15000 joules. They both have a 10min hill climb to race and want to pace with appropriate power. Rider A can sustain 333w for 10min, rider B 325w. This is because rider A has a larger capacity above CP to dip into, so can produce more power.<\/p>\n
TrainingPeaks looks into dFRC through its Analyze 360 system and is shown as a percentage of the full amount, or measured in kilojoules (kJs). Being able to visualise this throughout a workout or event can also be very useful for determining the reasons why a race may have panned out the way it did or an effort was not able to be completed. If you can see that the battery was heavily depleted, you can look at how the ride or event evolved up to this point. Does the rider need to save more energy on flats and avoid needless efforts, or does it show that they need to work on a specific metric for more races like this? It helps give a broader and clearer picture when it comes to the full performance spectrum.<\/p>\n\n\n
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\n(Image credit: Getty Images)<\/span><\/figcaption><\/figure>\nSubjective measures <\/h2>\n We have data for heart rate, power, stress scores, sleep values, HRV and many more. But with all of these data metrics, we can tend to forget some of the most important measures; our own personal perceptions.<\/p>\n
Whereas those other data points are objective measures, metrics such as rate of perceived exertion, and feeling, are subjective measures measured by you. They are incredibly useful though, and provide further depth and insight into the objective metrics that we gather.<\/p>\n
For example, you might have a ride where HR is low and Power is high relative to normal. If you feel strong and the ride is easy, then perhaps you are in good form. If you feel lethargic though, it could be that you require some more rest.<\/p>\n
Likewise, if Hr is high and power low, but you feel strong and the session was easy, you are likely fresh and well rested. If you don\u2019t feel good, this could be an early sign of the onset of illness so you should rest and avoid efforts for the next couple of days.<\/p>\n
It\u2019s not just useful for coaches, but also for athletes to measure these subjective metrics and keep track of them in a training diary platform. TrainingPeaks has a feature called Training Insights which allows you to track these measures over time. This means you can then look back on this and see how the objective and subjective metrics track in relation to race performances or increases in fitness.<\/p>\n\n\n
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\nSee how the heart rate (red) in this graph climbs as the duration of the ride goes on, despite the power (pink) being the same in the two efforts. <\/span>(Image credit: Future)<\/span><\/figcaption><\/figure>\nEfficiency Factor<\/h2>\n Efficiency Factor – known as EF – is an often slept-on metric. It measures the amount of external workload you can produce for a given internal workload. In basic terms, how many watts you can produce per heartbeat.<\/p>\n
The reason this is important is that cycling is a predominantly aerobic sport, and a key indicator of how strong our aerobic performance is, is how much work we can produce to accelerate us forwards, for as little internal workload as possible.<\/p>\n
A common indicator of improved fitness is that for the same heart rate you go faster, because you are producing more power for the same effort level. This same principle is how we see increases in FTP or CP. But we can have improvements in EF at lower intensities without our higher level thresholds necessarily changing. You can use Workout Comparison in TrainingPeaks where you can set a time range and look at the tab for EF to see how this evolves over time along with plenty of other metrics.<\/p>\n
You might see that your power for 120-130 BPM increases as you do more endurance training. Depending on your specific event, this may matter more than seeing a higher peak capacity effort. Audax and Ultra events are built upon the ability to work at as high a power as possible within a lower heart rate range, otherwise the distance is just not achievable.<\/p>\n
It can also be useful though to gauge how external stressors impact internal load. Heat, altitude, stress, poor sleep, all tend to negatively impact EF. Heart rate increases relative to power and the EF number drops. But as you acclimatise to the likes of heat and altitude, or get better sleep, those EF numbers improve again. So they are also useful for stress monitoring outside of just training stresses.<\/p>\n
Resilience\/durability\/fatigue resistance <\/h2>\n This metric, which is now trackable in WKO5, is particularly important for those who do road races, gravel events, or any longer events with hard finishes. In recent years, this has become one of the key predictors in performance, with studies finding that five-minute power production after a high workload (often measured in kilojoules) was a key predictor of race results.<\/p>\n
What this term generally looks to define is the rate of decline of peak power output after workload. Sometimes this is measured as an absolute workload, such as a blanket 2500kj, and sometimes it is referred to by kj\/kg. A strong amateur rider might have less than a 5% reduction in peak 5min power output after 2000kj. Meanwhile, a WorldTour rider will likely have less than a 5% reduction after 3500+kj.<\/p>\n
In road races and gravel races, it\u2019s not a case of who has the best 5, 20, or any duration of power when fresh. What matters is how much of that peak capacity you can produce after hours of high workload and intensity. If a rider who produces 400w for 5min fresh drops 15% of that power, then they will be slower than a rider who can produce 370w for 5min fresh but only drops 5%, with weight and aerodynamics all being the same.<\/p>\n
This is important as even for events such as sportives and gran fondos, performance at the end matters greatly. The 2026 Marmotte, for example, finishes up Alpe d\u2019Huez, so you need a strong performance after fatigue to minimise your total time.<\/p>\n<\/div>\n