What Hyrox Athletes Need That No Wearable Gives Them

You just finished a sled push. Your heart rate is 187. Your legs are screaming lactate. You have about fifteen seconds before you cross the mat and start your fifth 1km run.

Your Garmin thinks you’re doing strength training. Your Whoop just logged a strain spike. Neither one has any idea what’s about to happen to your run split.

This is the fundamental problem with wearable tech and Hyrox. The sport breaks every model these devices were built on.

The Sport That Doesn’t Fit

Hyrox is simple to explain and brutal to execute. Eight rounds. Each round is a 1km run followed by a functional workout station. Ski erg. Sled push. Sled pull. Burpee broad jumps. Rowing. Farmers carry. Sandbag lunges. Wall balls. In that order, every time.

Total running distance: 8km. Total work stations: eight. Total time for a competitive open athlete: somewhere between 60 and 80 minutes of controlled suffering.

Here’s what makes Hyrox different from almost every other endurance event. The metabolic demand changes violently, repeatedly, within a single race. A marathon runner holds a relatively steady heart rate for two to three hours. A CrossFit competitor does short, intense bursts with programmed rest. A Hyrox athlete does neither.

You run at 75% of max heart rate. Then you push a 152kg sled for 50 metres and your heart rate jumps to 95%. Then you immediately run again. Your body hasn’t recovered. Your legs are full of lactate from the push. And your watch has absolutely no framework for understanding what just happened or what it means for the next 40 minutes.

Why Training Load Models Break

Every major wearable platform calculates training load using some version of the same approach. They estimate the physiological cost of a session based on heart rate data, duration, and activity type. Garmin uses Training Effect scores. Whoop calculates Strain. Apple Watch tracks Exercise Load. They all work on the same basic principle: classify the activity, model the expected stress, and place it on a recovery timeline.

The problem is classification. These systems need to put your workout in a box. Running goes in the aerobic box. Weight training goes in the anaerobic box. Hyrox doesn’t go in any box.

When you log a Hyrox simulation workout on a Garmin, the device defaults to “Other” or sometimes “Strength” depending on your heart rate profile during the session. That classification determines how the device models your recovery needs, your training readiness the next day, and your long term load management.

Get the classification wrong and everything downstream is wrong too.

We tested this ourselves. Same athlete, same Hyrox simulation session, logged on a Garmin Forerunner 965 and a Whoop 4.0 simultaneously. The Garmin reported a Training Effect of 4.2 (aerobic) and 2.1 (anaerobic). Whoop reported a Strain of 16.4. The Garmin suggested 72 hours of recovery. The Whoop recovery score the next morning was 41%.

Neither device could tell us the thing we actually needed to know: which station cost the most, and how did it affect the runs that followed?

The Heart Rate Transition Problem

This is where it gets interesting for anyone who trains Hyrox seriously.

Your heart rate during a Hyrox race or simulation doesn’t follow any pattern that wearable algorithms expect. It doesn’t steadily climb like a tempo run. It doesn’t spike and recover like interval training. It does something entirely its own.

Picture this. You finish the rowing station. Heart rate: 178. You stand up, walk to the transition zone, cross the mat, and start running. Within the first 200 metres of that run, your heart rate drops to 162. By 600 metres you’re at 155. Then you hit the next station (farmers carry with 2x24kg kettlebells) and within 30 seconds you’re back at 175.

These transitions happen eight times in a single race. Each one is different because each station taxes your body differently. The sled push is posterior chain dominant and brutally anaerobic. The ski erg is upper body and aerobic. The burpee broad jumps are full body and destroy your hip flexors for the run that follows. Wall balls, the final station, are a quad destroyer right when your legs have nothing left.

No training load algorithm accounts for the compounding effect of these transitions. They see heart rate data. They don’t see that your sled push HR spike at 95% is a completely different physiological event than your rowing HR spike at 92%. Same number on the watch. Totally different metabolic cost. Totally different recovery demand.

Concurrent Training Is the Real Gap

Here’s the deeper issue that Hyrox exposes. Training for this sport requires concurrent training, which means developing both aerobic endurance and muscular strength in the same training block. Often in the same session.

This is well studied in exercise science and the conclusion is clear: concurrent training creates interference effects. Heavy strength work can blunt endurance adaptations and vice versa. Managing this interference is the entire game for Hyrox preparation.

Your wearable has no concept of this.

Garmin’s training load model separates “low aerobic” from “high aerobic” from “anaerobic.” It doesn’t model the interaction between them. It doesn’t know that your heavy sled pull practice on Tuesday is going to compromise your tempo run quality on Wednesday. It just sees two separate sessions and calculates load independently.

For Hyrox athletes, the relationship between sessions matters more than the sessions themselves. A standalone 10km run is easy to recover from. A standalone sled session is easy to recover from. Do them within 24 hours of each other, the way Hyrox training demands, and the recovery picture changes completely.

No consumer wearable models this interaction. Not one.

Pacing Strategy Needs Station Cost Data

Ask any experienced Hyrox athlete what separates a good race from a great one and they’ll tell you the same thing. Pacing.

Not just run pacing. Station pacing. Knowing which stations you can push hard on and which ones will blow up your subsequent run split if you go too deep.

The sled push is the classic example. It’s station two. You’re fresh and amped. The temptation is to go all out, finish it fast, and bank time. But a maximal sled push effort can add 15 to 20 seconds to your next 1km run. If you don’t know that about your own body, you can’t make an informed pacing decision.

This is exactly the kind of insight that cross-signal analysis was built for. You need heart rate data, yes. But you also need GPS pace data from the runs, time data from the stations, heart rate recovery curves during transitions, and a model that connects them all together.

Which station costs you the most on your subsequent run? How does fatigue accumulate across the race? Where is the optimal effort level for each station given your specific physiology?

These are answerable questions. Just not by any device you can buy today.

What a Real Hyrox Training Model Would Look Like

If you could model Hyrox training properly, here’s what it would track.

Station-specific metabolic cost. Not just “you burned 800 calories in this session” but “your sled push cost you 12% more energy per metre than last week, and your run split after it was 8 seconds slower.”

Transition efficiency. How quickly does your heart rate settle into a sustainable running rhythm after each station type? This is trainable. It improves with sport-specific preparation. And it’s completely invisible to current wearables.

Concurrent training interference. When your strength and endurance sessions are too close together, your performance in both suffers. A proper model would flag this before it happens, not after you’ve had a terrible run and don’t know why.

Cumulative fatigue modelling across the race. Stations one through four feel different from stations five through eight. By the time you hit wall balls (station eight), your quads have absorbed the accumulated damage of every sled push, every lunge, every burpee. A flat training load number doesn’t capture this cascading fatigue.

The Brisbane Test

The Hyrox APAC Championships hit Brisbane on 9 to 12 April. Thousands of athletes will race across Open, Pro, and Doubles categories. Every single one of them will be wearing at least one device. And every single device will miss the most important story of their race.

Not the total time. Not the average heart rate. Not the calorie burn.

The story of how each station affected the next run. The moment where pacing fell apart. The transition that cost them their target time.

This is the gap. Not in hardware. Not in sensors. In the intelligence layer that sits on top of the data.

Hyrox athletes generate incredibly rich, multi-dimensional training data every single session. Right now, that data gets flattened into a single number: Strain. Training Effect. Exercise Load. One number for a sport that demands eight different answers.

That’s what needs to change. And that’s exactly what P247 is building toward.