This article is the final installment in a four-part series, presented by ENGO. In this series, Matt Fitzgerald will teach you how to apply new advances in real-time training data for maximum benefit at various stages of athletic development. Learn more about ENGO here.

You work hard for your fitness. The last thing you want to do is waste it. But this is exactly what many athletes do in competition. As a result of flawed pacing, endurance racers seldom reach the finish line as quickly as they could. The gap between an athlete’s actual finish time and the time they could have achieved with better execution is—like it or not—a measure of fitness wasted.

Evidence that a majority of athletes pace suboptimally in races comes from a 2021 study by French researchers, who found that runners were able to complete a 3000-meter time trial as much as 14 percent faster when their pace was externally regulated in order to maintain a steady heart rate or oxygen consumption level than when their pace was freely chosen. The good news is that there is also plenty of evidence that athletes can improve their pacing skill with deliberate practice. Devices like ENGO that supply athletes with continuous real-time data can help in this process, which begins with understanding what it means to execute a race optimally.

What Perfect Pacing Looks Like

The defining characteristic of a well-paced race is consistency. Although it is nearly impossible to sustain a perfectly steady pace or power output throughout an entire race, research has shown that in any given race, less variation in work rate is associated with better performance. Here are a few quick examples:

A 2023 study led by Sabrina Demarie of the University of Rome found that elite 1500-meter swimmers paced themselves more evenly than junior swimmers, and that steadier pacing was associated with faster finish times at both levels.

A 2015 study published in the Journal of Science and Medicine in Sport reported that athletes who had less variation in heart rate in the uphill and downhill portions of an Ironman triathlon relative to their heart rate in the flat portions achieved faster bike splits than athletes’ whose heart rate was more up-and-down.

A 2011 study appearing in the International Journal of Sport Physiology and Performance found that the closer an individual athlete’s first-lap run pace was to their average pace for a four-lap run leg at the European Triathlon Championship, the faster their overall run time was.

As for why steady pacing yields the best results, it’s quite simple. The relationship between exercise intensity and effort sustainability is nonlinear, meaning each incremental increase in effort causes fatigue to accumulate faster than the previous increase. Hence, a steady effort is sustainable longer than a fluctuating effort even if the average is the same. ENGO makes steady pacing easier by giving athletes continuous visual access to relevant performance data.

Practicing Proper Pacing

Effective pacing isn’t quite as simple as picking a pace or power number and sticking to it. Not only do hills and winds necessitate some variation in output, but there’s no telling if the number you pick is truly the highest output you can sustain in a given race or race segment. Selecting a pace or power target based on the training you’ve done will give you a good starting point, but ultimately you have to feel your way to the right distribution of effort.

Deliberate practice is required to get better at pacing. With its continuous near-eye display of real-time performance data, ENGO has the potential to greatly accelerate the learning that occurs through deliberate practice. The most powerful way to take advantage of this technology is to periodically repeat particular courses and workouts, aiming to distribute your effort more efficiently each time. The goal is not just to go faster overall but to smooth out your effort distribution in ways that allow you to finish faster without simply pushing harder. Let’s look at a couple of examples:

Race-Pace Workout Sequence
Suppose you’re training for a half-iron-distance triathlon. A sensible training plan for this event will include some longer efforts at race intensity. Your race-pace running practice, for example, might consist of a sequence of three 8-mile efforts at half-marathon pace. If possible, do these workouts on a course similar to that of your upcoming event. In the first one, aim for an effort you feel you could sustain for 13.1 miles off the bike at your current level of fitness. Keying off your ENGO near-eye data display, try to maintain a very steady pace or power output on flat and windless segments, while allowing your effort to increase modestly when climbing or running into a headwind and minimizing the effort drop that naturally occurs when descending or running with the wind.

After completing the workout, analyze the data and look for ways to improve. Did you start out too fast and fade at the end? Did you coast too much when descending or push too hard when climbing? Repeat the workout two to four weeks later and see if you can complete the distance faster at the same level of effort by smoothing out your pacing and taking advantage of any fitness you’ve gained. Repeat this process for your third race-pace run in another two to four weeks.

Short Time Trials
Another effective way to practice race pacing is to perform periodic short time trials. The advantage of these is that, like actual races, they are all-out efforts. Their main disadvantage is that they are all-out efforts, hence hard on the body. I therefore recommend that athletes perform 20-minute time trials (or distance-based time trials that take roughly 20 minutes to complete), which aren’t terribly disruptive to the flow of training and also serve as FTP or fitness tests that athletes can use to update their intensity zones.

These short time trials can be done every three to five weeks throughout the training process. The first test of a given training cycle provides a benchmark. In each subsequent test, aim to improve your average pace or power (in the case of time-based tests) or your distance covered (in the case of distance-based tests) both by taking advantage of your fitness gains and by finding opportunities to distribute your effort more evenly based on analysis of past time trials.

Live Strava Segments

For ENGO users who are also equipped with an Apple Watch and the ActiveLook app, it is possible to use live Strava segments to practice pacing for races. This functionality allows you to track your current performance against your past best performance on a chosen segment in real time through ENGO’s near-eye display (as shown in the image above), making it much easier to improve your pacing with each repetition. You can use any local Strava segment for this purpose, but I recommend choosing routes similar to that of your upcoming race and that take roughly 20 minutes to complete.

A friend of mine recently enjoyed the opportunity to test ENGO’s Live Strava segment feature. She chose the 3.86-mile Lower to Upper Lake Mary segment in Flagstaff, Arizona, whose rolling topography was similar to that of her upcoming marathon. She completed the segment three times at tempo effort in a span of five weeks. The first time she averaged 6:41 per mile but started out faster and was barely hanging on by the end. The second time she was able to use her Apple Watch and ENGO to display her performance relative to her previous effort on the same segment (personal record or “PR” in Strava’s terms). Keying off the progress bar shown in ENGO as she ran, Lauren deliberately trailed behind her past self initially, then took advantage of the energy saved to surge ahead in the final mile, averaging 6:38 for the segment.

In her post-run analysis of the segment, she noted that her power dropped more than 10 percent below her segment average on descents that followed climbs. Seeing more room for improvement, she formulated a strategy of relaxing a bit on the climbs and pushing the descents in her third and final attempt at the segment prior to her event. As a result, she fell behind her past PR on the first hill climb but overtook her prior PR on the backside and stayed ahead till the end. She averaged 6:36 for the segment, unlocked a new PR in the process, and went into the A race with confidence and a clear idea about pacing for the event.

Avoiding Common Race-Day Mishaps

Perhaps the most common pacing mistake in races is starting with a solid plan and quickly abandoning it, carried away by adrenaline, nerves, and herd mentality. Racing with ENGO can mitigate this risk by essentially keeping the plan right in front of your face.

Another common mistake in racing, ironically, is sticking too much to plan. Instead of rigidly locking yourself into a target pace or power that you force yourself to hold regardless or topography, terrain, winds, or how you feel, configure your ENGO dashboards so that screen one shows your current pace or power and screen two shows your average for the race as a whole. Swiping to screen two periodically can assure you that you’re still on track toward your goal even when your current pace or power is necessarily off target.

Executing a perfect race is never easy, but athletes who arm themselves with an understanding of what perfect pacing looks like, and who also engage in deliberate pacing practice, stand a much better chance of not wasting their hard-earned fitness on race day. And if they incorporate real-time visual data into the process, their chances are better still.

The post How to Use Real-Time Data on Race Day first appeared on Slowtwitch News.

This article is the third in a four-part series, presented by ENGO. In this series, Matt Fitzgerald will teach you how to apply new advances in real-time training data for maximum benefit at various stages of athletic development. Learn more about ENGO here.

The fundamental goal of racing is to find your limit. When you complete a triathlon or other event, you want to look back and say, “I couldn’t have gone any faster.” That might sound simple enough, but given the unique nature of our limits as endurance athletes, achieving this level of performance is difficult. When used appropriately, devices like ENGO that supply athletes with continuous real-time data can help us become better at finding our limit, so we’re less likely to finish races with that dreadful woulda-coulda-shoulda feeling.

Let’s take a quick look at the latest science concerning the limits of endurance performance, and what it takes to find your own personal 100 percent. I’ll then describe three ENGO workouts that I have found to be especially effective in helping athletes find their limit.

The Pacing Factor

The key difference between a sprint, such as the 100-meter dash in track and field, and an endurance race, such as the marathon, is pacing. In both sprints and endurance events, the goal is the same: to reach the finish line as quickly as possible. If you’re a sprinter, the way to do this is to start the race at maximal effort and continue full-tilt until you’re done. But if you tried this in a marathon, you’d never even reach the finish line! To succeed in the goal of completing an endurance event in the least time possible, you must deliberately hold yourself back, racing not at maximal effort but rather at the highest effort you can sustain over the entire distance.

The question is, exactly how much do you hold back? And how do you actually know if you’ve succeeded in completing an endurance race in the least time possible for you on the day? Surprisingly, physiology provides no answers to these questions. Studies have consistently shown that athletes have reserve functional capacity at the point of exhaustion in endurance tests. According to measurements of blood lactate, muscle glycogen, core body temperature, and other potential physiological limiters, athletes are perfectly capable of continuing when they quit a test of this sort. But they don’t feel capable of continuing, and that, it turns out, is what limits endurance performance.

If you want to find your limit in an endurance race, science tells us, you need to make sure you reach the finish line feeling that you can’t continue any longer at your chosen pace or power. But there’s a bit more to it than that. After all, you could walk the first 26 miles of a marathon and then sprint the last 385 yards and you would cross the finish line feeling that you couldn’t go a step further.

A second hallmark of a perfectly executed race, besides feeling completely gassed at the finish line, is consistent pacing. While no athlete ever maintains a perfectly steady output during competition, studies indicate that the steadier an athlete’s pacing is overall, the better they perform in races. The reasons for this are complex, but the long and short of it is that an athlete has only so much energy they can pour into a race, and consistent pacing makes the most efficient use of this limited energy supply.

In summary, you know you’ve found your true performance limit in a race if you managed to distribute your energy very evenly, and in such a way that your rate of perceived exertion (RPE) increased linearly throughout it, culminating in maximal subjective effort (i.e., the perception that you were trying as hard as you possibly could) at the end.

ENGO Workouts to Help You Find Your Limit

Now that we’ve established what it looks like to find your limit in a race, let’s talk about how to get better doing so. Here are three workouts I’ve found to be especially effective for this purpose. While you don’t need ENGO to do them, they’re much easier to execute if you’ve got the relevant data continuously within sight in a heads-up display, and you won’t need to break stride or change body mechanics in order to read a watch.

Long Accelerations
Traditional accelerations are quite short, consisting of 10- to 15-second ramp-ups from a moderate pace to a full sprint. Long accelerations stretch this process out over several minutes, presenting a unique physical and mental challenge. On the physical side, long accelerations benefit athletes by exposing them to a full range of intensities within a single workout. On the physical side, they test and improve athletes’ ability to precisely control their effort. Here’s an example of a long accelerations workout:

15:00 warm-up
6:00 acceleration from moderate effort to full sprint
1:00 rest
4:00 active recovery
6:00 acceleration from moderate effort to full sprint
1:00 rest
4:00 active recovery
6:00 acceleration from moderate effort to full sprint
1:00 rest
15:00 cooldown

To do this workout with ENGO, configure the display 1 to show your current pace (running) or current power (cycling or running) as the primary metric in your screen (or “dashboard”). As you work out, keep your eyes on the heads-up display and try your best to sustain a gradual, continuous increase in pace/power that culminates in a maximal effort at the very end. This is exceedingly difficult to do to perfection (most athletes accelerate too quickly the first time, running out of “gears” before the end of the acceleration), but with repetition you’ll get better, and as you get better at this specific workout, you’ll get better generally at approaching your limit.

To assess your execution in a long accelerations workout, check out your pace or power graph afterward. You should see a line that ascends shallowly and steady with no dips or plateaus.

With repetition, ENGO makes it possible to align the effort you’re able to observe in real time with the curve that you see in the post-workout review.

Stretch Intervals
Stretch intervals are time-based high-intensity efforts where you try to cover slightly more distance in each repetition of a set. The last rep is an all-out effort, and the aim is to complete the first rep at an output that leaves you with just enough room to increase your output incrementally without hitting your limit before the last rep. Here’s an example:

15:00 warm-up
10 x 0:30 stretching from hard to all-out/2:30 active recovery
15:00 cooldown

If you do stretch intervals outdoors, I recommend that you drop a small, brightly colored object (such as a sock) at the end of each rep to mark the distance covered, then go back to the same starting point for the next rep. If you do them on an indoor bike, keep track of the virtual distance covered in each interval. (Note that stretch intervals aren’t suitable for motorized treadmills because the speed is preselected, removing the self-regulation element.)

To do this workout with ENGO, configure the display to show lap pace (running) or lap power (cycling or running) as the primary metric. Note that ENGO’s ActiveLook companion app manages laps differently for Apple and Garmin, however laps are available for both platforms. Complete the first interval at the highest effort that leaves you with just enough room to push a little harder in each subsequent interval. Drop your marker at the endpoint (if applicable), note your lap pace or power for the interval, and aim for a slightly faster pace or power that results in your covering a bit more distance in the second rep, and so on.

In a perfectly executed set of stretch intervals, the lap pace in each rep is just a few seconds per mile faster than the preceding, or the lap power just a few watts higher, and the last rep is a maximal effort. As with long accelerations, you won’t nail the execution the first time, but with repetition you’ll get better, and as you do, you’ll get better at finding your limit.

Locked-In Tempo
The locked-in tempo is a twist on the traditional tempo workout, where you try to maintain a perfectly consistent pace or power output throughout. Remember, a steady distribution of effort is a hallmark of perfect race execution, and this workout is an effective way to improve this ability. Here’s an example:

15:00 warm-up
15:00 @ lactate threshold pace/power
5:00 easy
15:00 @ lactate threshold pace/power
15:00 cooldown

If you don’t know your exact lactate threshold pace or power, just pick a number that is close to the fastest pace or highest power you could sustain for one hour in a race situation. To do this workout with ENGO, you’ll use the same display configuration as you do for Stretch Intervals to show your current pace (running) or current power (cycling or running) as the primary metric. Focus on the display, and try to lock in to the target pace or power from the start to the finish of each tempo block. Also pay attention to your internal perceptions of effort and output; this will help you develop a better sense of what it feels like to hold a steady pace.

The Ultimate Test

ENGO and similar devices are not only useful for training athletes in the ability to find their limit while training. They’re also helpful on race day itself. In the final installment of this series, I will offer tips on racing with ENGO.

Learn More about ENGO, or make a purchase, here.

The post Using Real-Time Data to Find Your Performance Limit first appeared on Slowtwitch News.

This article is the second in a four-part series, presented by ENGO. In this series, Matt Fitzgerald will teach you how to apply new advances in real-time training data for maximum benefit at various stages of athletic development. Learn more about ENGO here.

You’re not the same athlete you were yesterday, nor will you be the same tomorrow. Due to subtle day-to-day fluctuations in heart rate variability, maximal muscle contractile force, hormonal status, mood state, and countless other physiological and psychological variables, athletes never know exactly what they’re going to get when they start a workout.

This presents a challenge for training plan execution. Because the body is ever-changing, the workout you planned for any given day is not always the workout you need. Too often, athletes fail to realize they’ve done the wrong workout until it’s too late. For example, the plan tells you to complete eight intervals in Zone 3, but when you analyze the file after completing your workout, you discover that despite hitting the prescribed power target, your heart rate was mostly in Zone 4, perhaps due to one of the factors listed above—an overreach that could have a negative ripple effect on subsequent training.

Real Time Data to the Rescue

To avoid such self-sabotage, athletes need to make on-the-fly adjustments to ensure each workout serves its intended purpose. Devices like ENGO that feature a near-eye display of real-time training data can help. By supplying the athlete with continuous access to performance metrics such as power and pace, they facilitate swift and appropriate adjustments that prevent unintentional overreaching. But these adjustments don’t happen automatically—responsibility lies with the athlete to make the best use of the data.

The key to doing so lies in calibrating your subjective effort perceptions to objective performance metrics. One thing we all know from experience is that when we’re having an off day, we can feel it. This was shown in a 2012 study in which cyclists completed 20-km indoor time trials on two occasions. As expected, each cyclist performed slightly better in either the first or the second time trial due to small differences in their overall state. Interestingly, however, these differences were not captured by any of the physiological measurements taken during the tests. The biggest difference between the two performances was that the cyclists felt worse when they performed worse.

The goal of a time trial, naturally, is to finish as quickly as possible. Succeeding in this aim requires that you know how you should be feeling at various points. You may have a target pace or power in mind when you start, but because this number is unlikely to align perfectly with your performance limit on that day, you need to key off it in a loose way and allow perceived effort to have the final say. With ENGO, the same approach can be used in workouts to ensure they serve their intended purpose, helping you to learn to recognize how a given state of performance actually feels and ultimately eliminate post-activity surprises and disappointments.

3 Steps to Smart Adjustments

Making smart adjustments to workouts is as easy as 1-2-3. Here are the steps:

Step 1 – Calibrate your sense of effort by paying attention to how you feel at different paces, power outputs, and heart rates during your normal workouts. Your eyes are on ENGO’s near-eye display but your mind is on your internal sense of how hard you’re working, and you’re aiming to link the numbers you see to the perceptions you feel. Also pay attention to the relationship between your heart rate (a physiological measure of intensity) and your power and pace (output measures of intensity), which can also be useful in making adjustments to workouts, as we’ll see momentarily.

The table below, which shows how rate of perceived exertion (RPE) correlates with different intensities in the most widely used zone scale, will assist you with this calibration process. Note that this zone sale can be used with any intensity metric.

Step 2 – Test your ability to maintain a steady pace, power, or heart rate between glances at your data. Let’s say you’re running 3-minute intervals at 7:00 per mile. In this scenario, you might check your pace every 30 seconds to make sure you’re on track and adjust as necessary. The rest of the time you’re using perceived effort to stay locked into that pace. ENGO is especially helpful here because you can shift your focus back and forth between your data and the road instantly and effortlessly, without breaking stride to look at your wrist or dropping your head to look at your bars.

Step 3 – Adjust your pace, power, or heart rate in workouts as necessary to ensure they stay true to their purpose. In general, this means reducing your output to make sure workouts aren’t harder than they’re supposed to be when RPE is higher than normal relative to pace, power, or heart due to fatigue from prior training, poor sleep, challenging weather, hormone levels, life stress, an inadequate breakfast, or some other factor.

4 Common Scenarios

Let’s take a look at four different scenarios and how an athlete who has mastered these steps will respond to each.

Scenario 1: The athlete is doing a threshold workout targeting functional threshold power (FTP), which for them is 225 watts. Normally, this intensity corresponds to an RPE of 6, but today, for whatever reason, it’s a 7.

Response: The athlete swipes to screen 2 on their ENGO eyewear, which shows their current heart rate. When subjective effort is above normal, heart rate is sometimes also elevated, allowing the athlete to adjust their workout simply by switching from power or pace to heart rate as their primary intensity guide. Sure enough, the athlete finds that their current heart rate is 165 BPM, whereas it is normally 160 BPM at FTP. So, the athlete reduces their output and completes the threshold segment at 160 BPM.

Scenario 2: The same thing happens as in scenario 1, except this time the athlete’s heart rate is normal—only their RPE is elevated.

Response: Knowing that FTP falls toward the upper end of Zone 4, the athlete swipes back to screen 1 and reduces their power to the lower end of Zone 4. After checking internally to confirm that their RPE is now at the desired 6 rating, they note their current power, which happens to be 215 watts. This number become the new target for the remainder of the segment.

Scenario 3: Same thing again, only this time the athlete feels unusually strong, their RPE barely exceeding 5 at 225 watts.

Response: 4: The athlete sticks to the plan, completing the threshold segment at the prescribed wattage. The following week, however, the athlete does an FTP test that confirms they’ve gotten fitter and earned new zones. Discipline is required to avoid getting carried away when you’re having a great workout, but prudence dictates that you do indeed hold back and reinvest your gains in future training.

Scenario 4: The athlete is doing a 2-hour run in Zone 2, which for them has an upper limit of 140 BPM. But today this intensity feels harder than normal.

Response: Instead of adjusting their pace, the athlete maintains it but shortens the run to 90 minutes. Keying off ENGO, they stop at the point where their heart rate begins to decouple from their pace (i.e., when HR rises above 140 BPM despite no change in pace). This is generally the better way to go in long endurance workouts, where the challenge comes from the duration of the session rather than from the intensity.

Remember, the better you are at truly understanding relative effort—in real-time—the more effectively you’ll be able to predictably manage effort, and set and achieve goals accordingly.

Looking Ahead

There are other possible workout scenarios requiring adjustments, but these examples cover the most common situations athletes encounter. In part three of this series, I will present a set of workouts that function especially well with ENGO as tools for testing and redefining performance limits.

Learn More, or Shop ENGO, here

The post When and How to Deviate from Your Training Plan first appeared on Slowtwitch News.

Most endurance athletes train wrong. This isn’t my opinion—it’s science. For example, a 2021 study appearing in the journal Sports reported that amateur triathletes who were tracked for six weeks leading up to an Olympic-distance race completed just 47 percent of their combined swimming, cycling, and running at low intensity, far below the recommended 80 percent.

The dividing line between low and moderate intensity falls at the first ventilatory threshold, which equates to around 80 percent of maximum heart rate. Athletes tend naturally swim, bike, and run just above this threshold in training sessions that they intend to do at low intensity, drifting ever so subtly over the line into moderate intensity. This is no big deal in a single workout, but when it becomes habitual—as it appears to be for the majority of athletes—the consequences snowball, with athletes carrying away a bit too much fatigue from each and every session, accruing a chronic burden of unresolved physiological stress that compromises performance in key workouts and stifles the body’s adaptations to training.

Real Time Data to the Rescue

As a coach, I make it my highest priority to correct such errors with each new athlete I bring on. Real-time training data is my best friend in this effort. In the bad old days, when the only metric athletes could track in real time during workouts was time itself, coaches just had to hope that athletes would execute correctly. Modern training devices have removed hope from the equation, functioning almost as surrogate in-person coaches that ensure their the athlete’s heart rate, power, and pace are where they should be and that segment distances and durations are precise.

Things have only gotten better with the advent of near-eye data displays as found in ENGO performance eyewear. Now, real-time training data is always within the athlete’s field of vision, available on command with only a slight shift in eye focus. With ENGO and similar products, heart rate, pace, power, and other data are essentially built into the training experience, similar to perception of effort and proprioception.

The mere availability of data does not guarantee effective use of that data, mind you. To get the most out of ENGO, athletes need guidance. Research indicates that endurance athletes move through different stages in their use of training devices—but not every athlete successfully graduates from one stage to the next. As a coach, I divide the process of mastering device usage into three stages:

Stage 1: Better Adherence to the “Letter” of Workouts

As I mentioned above, most endurance athletes make frequent errors in executing workouts. They set out intending to do one thing and end up doing something else, with unfortunate consequences. Near-eye displays of real-time data help athletes who struggle with adherence to execute workouts correctly. I’ll say more about this below.

Stage 2: Better Adherence to the “Spirit” of Workouts

The problem with planned workouts—as with all plans—is that they are essentially predictions, and predictions are seldom perfectly accurate. In these instances, I count on the athlete to understand and adhere to the spirit of the workout rather than to the letter.

Real-time data has a role to play at this second stage too, but it’s more nuanced. I’ll share my thoughts about how to use ENGO to ensure that the underlying purpose of each workout is met despite gaps between expectation and reality in part two of this series.

Stage 3: Better Self-Regulation of Training and Racing

The ultimate goal of every serious endurance athlete is to reach their full potential. Achieving this goal requires that the athlete become adept at self-regulation, or using internal feedback to find their absolute performance limit. That’s because the limit is kind of squishy in endurance sports—as much a matter of perception as of physiology.

I’ll share my thoughts on using ENGO in this third stage of device mastery in part three. The fourth and final installment in the series will address the special topic of using this new technology in competition.

Yes, But What Data

It’s easy to understand how continuous access to real-time data can help athletes better adhere to workout prescriptions. But there are many different types of data that might be used for this purpose, and they can’t all be equally useful in every situation. This is where coaching comes in. Athletes need to know which specific metrics to pay attention to when.

Following are examples of how I teach athletes to configure ENGO for three basic categories of workouts: low intensity (e.g., recovery runs, long rides), moderate intensity (e.g., tempo runs, critical power intervals), and high intensity (e.g., hill repetition runs, VO2max interval rides), along with my reasoning.

Note that ENGO allows athletes to configure three separate screens, which they can cycle through by waving a hand in front of the lenses. For now let’s focus on the primary screen configuration—we’ll look at other options in later installments of this four-part series.

Low-intensity Workouts

Data Field 1: Elapsed Time
Data Field 2: Distance
Data Field 3: Heart Rate

We’ve seen that endurance athletes often struggle to stay at low intensity in workouts they intend to do at low intensity. Better compliance in these training sessions requires that athletes hold themselves back. Heart rate is preferable to other intensity metrics for this purpose because it is not performance-relevant. Focusing on pace or power makes athletes want to push harder, but heart rate does not. To the extent that workouts are games, athletes feel they are “winning” when they are ahead of their pace and power targets, but with heart rate, “winning” means staying below a predetermined ceiling. For this reason, heart rate should have pride of place on your ENGO display in low-intensity workouts.

Moderate-intensity Workouts

Data Field 1: Lap Time
Data Field 2: Lap Distance
Data Field 3: Lap Pace/Power

Whereas in low-intensity training sessions your top priority is making sure you’re not pushing too hard, in moderate-intensity workouts it’s making sure you’re working hard enough (yet also not too hard). Performance measures—namely pace or power—therefore take the place of heart rate as the primary intensity metrics in your data screen configurations.

Time and distance information remain important in moderate-intensity workouts because they tell athletes where they are within session—how far they’ve come and how long they have to go. What matters more in moderate-intensity workouts, however, is not total elapsed time or distance covered but segmental (or “lap”) time/distance. For example, when you’re in the middle of a 20-minute tempo effort, you don’t care how deep you are into the entire workout, which perhaps started with a 15-minute warmup; you care only about how deep you are into those 20 minutes that really count.

Nor, for that matter, do you care about your average pace or power for the entire workout, including the warm-up. You want to know your average pace or power for the specific target range for the tempo segment you’re in the middle of, so you can thread the needle between too easy and too hard.

High-intensity Workouts

Data Field 1: Lap Time
Data Field 2: Lap Distance
Data Field 3: Cadence

I lied. I told you I was going to present the primary data screen configuration for each category of workout, but the example you see here is actually my recommended secondary screen for high-intensity workouts. That’s because the primary screen is the same for both moderate-intensity and high-intensity workouts.

The obvious difference between this configuration and the preceding is the presence of cadence. Why cadence? Because both stride rate in running and RPM on the bike are tightly coupled with intensity. When you’re hitting your target intensity in a high-intensity interval, your cadence will hover within a narrow range—until you start to fatigue and lose your form, at which point your cadence will begin to drop. I’ve found that by focusing on cadence as a supplement to pace or power in high-intensity workouts, athletes are better able to maintain their form as fatigue builds.

Looking Ahead

The guidelines I’ve provided here are not the last word on using products like ENGO to improve workout execution. But if you’re among the many athletes who struggle in this area, you should find them helpful. And if you’ve already mastered adherence to the letter of workouts, stay tuned; the next article in this series will discuss how to use near-eye displays of real-time data to adapt your workout execution on days when you feel better or worse than normal or when conditions are different than anticipated.

Editor's Note: This series of articles from Matt Fitzgerald will look at specific opportunities where real-time data can help you improve as an athlete. This series is part of our partnership with ENGO, and so you'll see mentions of their product throughout these pieces. However, these lessons are applicable to almost all athletes who wear some type of device during a workout. We hope you enjoy. To learn more about ENGO, click here.

The post Training with ENGO: Better Data For Specific Workouts first appeared on Slowtwitch News.