Wahoo has released new Fitness Metrics for cycling and running to provide a more complete picture of the impact of your training on the various dimensions of your fitness, your capacity to train, and your overall fitness when compared to simple FTP, other existing cycling metrics and tr
Leveraging our multidimensional analysis models, Four-Dimensional Power® (4DP®), Three-Dimensional Pace® (3DP®), and new algorithms developed by our sports and data science team, the Wahoo Cloud will analyze all cycling, activities uploaded to your paid Wahoo subscription account that contain power and cadence data, and all running activities.
This allows us to measure the impact of every ride that contains power and cadence data on the different components of your cycling fitness (endurance, max power, repeatability, etc) and every run based on then different components of your running fitness (threshold pace, maximum aerobic pace, anaerobic capacity), using an updated model that accounts for the importance of rest, more accurately predict your capacity for continued training (or competition) and estimate your overall cycling and running fitness into one complete picture.
Metric definitions
Dimensional Training Load (DTL)
Dimensional training load (DTL) is a composite score calculated from component analysis of the various types of effort across a ride. Referenced to your 4DP® Athlete Profile, or 3DP® Athlete Profile, it integrates duration, intensity, power or pace, and cadence data to provide a deeper understanding into how each training session challenges your body. DTL demonstrates your training stress across four dimensions — FTP, MAP, AC, and NM for cycling, or three dimensions — TP, MAP, AC for running. Each DTL component (called a load contributor) is weighted individually to reflect how different intensity loads affect fitness and fatigue. Each system contributes differently to building fitness, so tracking them separately gives a clearer picture of how your training impacts you.
For this reason, a composite DTL score for a given workout cannot/should not be interpreted in the same way as a static comparative value, like TSS. At the same time, being able to break down the training load across the four/three dimensions allows us to more accurately calculate a workout's training load impact on fitness and fatigue and demonstrate that in our Training Capacity and Fitness Score metrics.
DTL will always be a positive number, and is a value relative to all activities within the last 2 years in your Wahoo account (or since your last fitness assessment). Like most other fitness metrics, it is not an absolute value, as it generated for your efforts relative your current capacity for those efforts (as defined in your Athlete Profile) at that time.
For more details on Dimensional Training Load [DTL], see Dimensional Training Load (DTL).
Short Term Load [STL]
Short Term Load [STL] describes the total training load you have accumulated in approximately the last week as an average of the DTL values of all activities in that period. Each load contributor is weighted individually to reflect how different intensity loads affect short-term fatigue. (ex. 100 DTL from high-intensity MAP/AC efforts will leave you more fatigued for several days than 100 DTL from steady TP training.)
Long Term Load [LTL]
Long Term Load [LTL] provides a long-term view of the total impact of your training. It is a rolling average of your DTL values over several months, with adjustments made for the varied decay rates of the four/three dimensional components. Like with Short Term Load, individual load contributors are weighted separately. Long Term Load doesn’t represent fitness level, but shows the amount of work you’ve done over time. Each load contributor is weighted differently, and a decay rate is applied, based on how long its adaptations typically last - Some gains fade faster than others.
FTP/TP capacity builds the slowest but lingers longest when training decreases. Higher-intensity work (MAP, AC, or NM efforts) adds to LTL faster but those benefits also fade faster if you stop targeting those systems. A higher LTL reflects consistent training volume and indicates you can handle greater short-term training loads. Because of the math involved, LTL takes about 90 days of regular training to stabilize into a true long-term measure.
Training Trends
Technically not a metric, the Training Trends data visualization presents your composite LTL (total LTL broken down into the four key dimensions: FTP, MAP, AC and NM) on a given date and across a time horizon that you select (1 week, 1 month, 3 months, 6 months, 1 year, 2 years). It allows you to view the impact of your training to the 4DP®/3DP® component categories over time.
For more details on Short Term Load [STL] and Long Term Load [LTL] metrics and the Cycling Trends graphs, see Short Term Load (STL), Long Term Load (LTL), and Cycling Trends.
Mental Capacity
The Wahoo app now includes a mental capacity assessment that is designed to track your cognitive and emotional readiness to perform -- your mental capacity. The assessment consists of a Go/No Go task designed to measure your cognitive state based on reaction time and response inhibition coupled with an emotional self-survey.
For more details see Mental Capacity Assessments.
Training Capacity (TC)
The Training Capacity [TC] value presents your day-to-day readiness to continue training or compete (ie are you rested or fatigued) as the ratio of your Short Term Load (STL) relative to your Long Term Load (LTL) and is impacted daily by the Mental Capacity Assessment if taken.
A negative Training Capacity score, or STL > LTL, indicates you are training harder than your baseline fitness, which is necessary for building fitness. Sometimes keeping a low TC value is part of the plan to push your limits, but too long without rest can stall progress. To gain fitness, aim for 2-3 weeks with negative TC value.
A positive Training Capacity, or LTL > STL indicates your recent training is lighter, allowing for recovery. To recover, reduce your STL relative to your LTL.
Note, a negative TC value isn’t 'bad', it just means you’re fatigued, which will limit your immediate capacity to train at a high level or perform well immediately. Likewise, a positive TC value isn’t 'good', but demonstrates your current capacity to increase your training load or perform your best in the near future.
Fitness Score and State
Your Fitness Score is a measure of your overall fitness level. The Fitness Score combines your Long Term Load (LTL) and Training Capacity to provide a simple point-in-time measure of your fitness. It grows slowly over time as you train, and accounts for the impact of rest on that process.
Fitness State is Wahoo's way of connecting all of this complex training data into an easy to 'state' of how your training is affecting you, and can give insight into how you may want to train the next day, week, or month.
You’re at peak fitness (ie can perform at your best) when you’ve built strength and are well-rested. Unlike fitness models that only reward accumulated training, Fitness Score accounts for recovery. This ensures that your Fitness Score most accurately predicts your ability to perform.
For more details on the Training Capacity [TC], Fitness Score and State metrics, see Training Capacity [TC] and Fitness Score.
How the new metrics work
Calculating DTL – for cycling activities with power and cadence data
Once a ride is imported into your Wahoo account (via ride upload from the Wahoo app, an ELEMNT computer, or synced from a third party service like Zwift or Strava) the Wahoo Cloud processes the various efforts that make up each ride, analyzing the relationship between power, cadence, and time across the ride to break those efforts down by intensity. Once broken down, the efforts are categorized by types called load contributors (ex moderate efforts, power spikes, sustained high cadence) based on your 4DP® Athlete Profile, (calculated from a Full Frontal or Half Monty fitness assessment or estimated from the Athlete Profile questionnaire in the Wahoo app).
A Dimensional Training Load (DTL) score is calculated for each load contributor and the component scores are added together to provide a totaled DTL score for each ride. We are then able to provide an intensity breakdown of the efforts you produced during a ride and how much of your training load each of the various types of efforts contributed to the overall intensity of the ride.
Estimating DTL – for other activities
Currently for all activities other than cycling or running, or cycling activities that do not contain power data, the Wahoo Cloud estimates a total DTL value based on [1] the workout type, [2] the activity’s duration, and [3] the post session rating (PSR) you gave for that activity. Each workout type has an intensity value and in the absence of a post session rating, a default median PSR value is applied.
Aggregating the data
As you continue to ride across time, the Wahoo Cloud totals both the individual load contributor DTL scores ([FTP], [MAP], [AC], and [NM]) and the total DTL scores from each ride. With these aggregate values, we can provide a comparative view of your Dimensional Training Load across a variety of time intervals (1 week, 1 month, 3 months, 6 months, 1 year and 2 years).
Using our sports science model that accounts for the variable impact of different types of training on fitness (ex. Endurance takes longer to build, but sticks around longer, while anaerobic capacity or sprint workouts will show more immediate benefits, but will also fade more quickly), we are able to show the immediate and long term impacts to your 4DP® component fitness with our Training Trends metrics and graphics.
The Wahoo Cloud also calculates an average of DTL values across about a week to provide Short Term Load and a rolling average of DTL values across several months to provide Long Term Load). With these values, and accounting for the differing decay rates of the 4DP® component categories and the importance of rest as a component to effective training, we have developed more accurate Training Capacity and Fitness Score metrics.
The Wahoo Cloud analyzes the volume and intensity of your Short Term Load (STL) against your Long Term Load (LTL) to determine how much the makeup of today’s ride added to both your fatigue level and your overall fitness. A hard workout of above threshold intervals probably reduced the likelihood that you should crank out another hard workout tomorrow, especially if you’re tapering toward an event, but probably had less impact if you are well into the season’s training plan than if you just started it. At the same time, how much training you’ve been doing throughout the season will determine how much this workout moved the needle on your current fitness level.
Fitness Score + Fitness State + Mental Capacity
Fitness Score takes into account your STL, LTL, and mental capacity assessment to create a score that increases when you are building fitness and recovering. If you are following a structured program that has you leading into a race season, you'll see this number increasing; especially if you are getting plenty of rest, and taking the mental capacity assessment daily.
Your Fitness State takes this number (which is produced from a complex algorithm) and provides an at a glance state of where you body is in the training cycle: detraining, recovering, maintaining, building, or overtraining.
The Mental Capacity assessment can be taken once by day, and once calibrated (4 tests) it will provide a readiness score. This will also affect training capacity by ±12 points.
For more information about each of the individual metrics, including how / where to access them, see:
Principles of 4DP® and the Wahoo cycling Fitness Metrics
Power is a consistent and user-accessible external measure of training workload, and serves as a proxy for the internal physiological demand of an effort.
Cycling fitness is multidimensional, and how you train matters, not just how much you train.
How you generate power (cadence and torque) matters. Frequent or extended efforts well below or above your preferred cadence will induce fatigue more quickly than more moderated efforts, but you also may experience dimensional fitness benefits, the more you train a certain dimension.
Each rider is different, so different types of training will impact different riders' fatigue and fitness differently. Your training efforts, their dimensional components, and their relative impact on your training capacity and fitness are scaled to your 4DP® Athlete Profile. Being able to track cycling efforts multi-dimensionally and mapping them against your Athlete Profile improves your ability to track fitness more accurately, and therefore predict cycling performance precisely.
Group rides impact your training, often in ways that are less predictable. Being able to track and analyze the component efforts of a ride outside of a structured workout improves your ability to understand how they are impacting the fitness you are trying to build with your structured training plan.
Rest matters when targeting peak performance. More is not always better. Tapering before an event is a key component of building capacity to perform by recovering from the fatigue caused by the training before the benefits of the training fade.
Principles of 3DP® and the Wahoo running Fitness Metrics
Grade adjusted pace (GAP) is a consistent and user-accessible external measure of training workload, and serves as a proxy for the internal physiological demand of an effort.
Running fitness is multidimensional, and how you train matters, not just how much you train.
Traditional pace excludes terrain. A run with a lot of climbing should be measured differently than a flat run at the same pace with respect to the athlete's 3DP zones.
Each runner is different, so different types of training will impact different runners' fatigue and fitness differently. Your training efforts, their dimensional components, and their relative impact on your training capacity and fitness are scaled to your 3DP® Athlete Profile. Being able to track running efforts multi-dimensionally and mapping them against your Athlete Profile improves your ability to track fitness more accurately, and therefore predict running performance precisely.
Group runs impact your training, often in ways that are less predictable if they are not a specific pace workout. Being able to track and analyze the component efforts of a run outside of a structured workout improves your ability to understand how they are impacting the fitness you are trying to build with your structured training plan.
Rest matters when targeting peak performance. More is not always better. Tapering before an event is a key component of building capacity to perform by recovering from the fatigue caused by the training before the benefits of the training fade.
Requirements
Wahoo Fitness Metrics are a paid Wahoo subscription feature. The Training Progress panel on the Today tab and Dimensional Training Load summary panel will be available to non-subscribers, but further data analysis requires a paid Wahoo subscription or active trial.
For access to the full suite of metrics and visualizations, the following are required:
A paid Wahoo subscription (or active trial)
-
Cycling activities with power and cadence data in your Wahoo account*
recorded in the SYSTM app for MacOS, Windows, iOS, or Android OR
recorded on an ELEMNT GPS computer OR
-
completed in a third party app or device and synced via Strava to your Wahoo account
*As described above, any activity will generate a total DTL score, but in order to get dimensional training analysis, cycling activities have to possess power and cadence data.
-
Running activities with elevation and pace data in your Wahoo account*
recorded in the SYSTM app for MacOS, Windows, iOS, or Android OR
recorded using a COROS watch with the COROS app synced to your Wahoo account OR
completed in a third party app or device and synced via Strava to your Wahoo account
-
A 4DP® OR 3DP® Athlete Profile established in the Wahoo app
generated by completing a Full Frontal [best] or Half Monty [better] fitness assessment in the SYSTM app using the same Wahoo subscription account (cycling only) OR
-
completing the Athlete Profile questionnaire [ok*] in the Wahoo app
*The questionnaire is a great start if you are just eager to get started on your training journey, but the results of a fitness assessment (completed after a few introductory training sessions to prepare you) will always be more accurate than the estimate generated from the questionnaire.
For the best experience
Update your Preferred cadence value in the Athlete Profile in the Wahoo app (cycling only).
(Today tab > Account > Athlete Profile > Update manually > Preferred cadence). Select a cadence that you are comfortable with when engaging in a moderate effort. Taking a look at your average cadence (with zeroes excluded) from a few longer rides of at least moderate effort should give you a good starting point.Provide accurate Post Session Rating values for all recent activities that you complete that are not cycling activities with power and cadence data or running activities, and for all non-power-based cycling activities going forward.
Backfill your fitness data, if prompted, as the Wahoo Cloud needs at least 90 days of data for optimal performance, but having a longer time horizon provides even better context.
Complete a Mental Capacity assessment daily.
Understand the limitations of the system to account for activities that are not cycling activities with power and cadence data or running activities. The system does calculate a DTL value for all activities from your post session rating and the duration of the activity, but because there is no dimensional analysis possible for these activities, their dimensional impact is applied as Threshold Power/Pace (TP) DTL values and may over or underestimate their overall impact to your training load and other metrics.
A cycling example
Looking at an example of the metrics suite, here is my 4DP® Athlete Profile and a ‘moderate’ solo ride I went on through in town Atlanta recently. I haven’t been training. Almost every dimension of my Athlete Profile is an ‘opportunity’. You can see from the load contributors list, it was a lot of consistent pedaling, punctuated by a variety of stiffer efforts of varying intensity and duration. Most of those were the result of punchy little rollers or trying to stay out of the way of traffic at different points throughout the ride.
Note, the load contributor breakdown percentages are based on the proportional impact of those efforts to my training load, not purely a time in power zone calculation. As you can see from the map, as a simple distance/time calculation, I spent more time in steady state ([FTP]) efforts. But, because shorter efforts above ([AC]) or just below threshold ([MAP]) take a greater toll on the body, a shorter interval spent in one of those kind of efforts, particularly at higher torque, are weighted more heavily. Additionally, the algorithm accounts for the fact that a single effort can impact multiple physiological systems (FTP, MAP, and AC) at the same time, so any given moment in a ride may be accounted for in multiple load contributors calculations.
Because I haven’t been training, this ‘moderate’ ride shows up solidly in the red of the training load impact scale, near the highest of my efforts in the last 90 days.
Here (left image below) is the Dimensional Training Load view of that ride in the context of the last week. Two rides on the weekend with a power meter, and a short commute on Monday without one.
And then (middle image below) is the DTL impact of those two rides on my dimensional cycling fitness last week in the Cycling trends one month view. Because of the intermittent higher intensity efforts across those two rides (and the very limited riding I’ve been doing recently), the system calculated a mild increase in my Breakaway (MAP) and Attack (AC) capacities, but no change to my Sprint (NM) capacity, because neither of those rides contained true sprint (high power + high cadence) efforts.
Finally, here (right image below) is the impact of the rides from last week in the Fitness & Training Capacity one week view. Because I have been recording activities, but not training much, these two rides made a large relative impact on my short term load, a small impact on my long term load, a moderate impact on my immediate training capacity, and little impact on my overall fitness. Specifically, note how there is an inverse relationship between the increase in short term load over long term load and my training capacity. With only the short commute ride on Monday, my short term load is coming back down, and my training capacity is coming back up. In order to see a change in fitness, however, I’m going to need to progressively increase my ride volume and intensity.
A running example
Now for an example for running! The first screenshot is my running 3DP® Athlete Profile, and the second is from the Atlanta half marathon that I ran last year. This was the first half marathon I had ever run, the furthest distance that I had ever run, and a race that I trained for, for about 8 weeks in advance. My training head of the race consisted of 2 or 3 runs a week, 2 weight training sessions, and 5 cycling workouts. For context, I consider myself a cyclist first, but wanted to challenge myself by doing something different.
I spent the majority of the race being conservative. I wanted to run long, steady, not over extend, and make sure that I had something left for the final 5 kilometers. A 5K is a race distance I am very familiar with, and able to pace well. Once I hit the 5K to go flag, I lifted the pace. This is the moment the ([AC]) effort happened, and then I quickly realized: my longest training run was 8 miles. I am at mile 10. Settle into a bit of a harder pace than you were running before and finish strong.
For the first few miles, I was running about an 8 minute mile, but, since the running 3DP® algorithm uses grade adjusted pace (GAP), later in the race there was a lot of climbing, and despite my pace slowing down, it is given the moderate effort DTL load contributor.
Now, since this run was back in November 2025, and this is being written in May 2026, we need to view the Dimensional Training Load view in the context of the past year (bottom left image)
This run came right in the middle of my cycling off season build, so I was training a lot, and adding the running in compounded that. It also meant that I had no need to be fresh, so a lot of time working on threshold power ([TP]) and threshold pace ([TP]). Also, since training for this run meant being able to go longer than I had before, almost all of the training runs were also at threshold pace ([TP]).
Since we can filter by sport, you can see the individual contribution that the running I was doing had to overall DTL in the month of November (bottom middle image). Post race, I quickly dropped off in a return to cycling only.
In the final image (bottom left) we can see my Training Trends and how they match up with the Dimensional Training Load, since I was spending more time targeting threshold power/pace during that block, I gained points in that area while the rest of my 3DP® / 4DP® metrics were not being trained decreased.
For more information about each of the individual metrics, including how / where to access them in the Wahoo and SYSTM apps, see:
For more information on how to best set up your Wahoo account for the cycling Fitness metrics, see Set up your Wahoo account for cycling Fitness Metrics.