Hybrid or multimodal competitions, such as HYROX®, combine running segments with standardized functional exercise stations. The rapid succession of these sequences requires a strong ability to manage quick transitions between efforts of different types1.
What is a HYROX® competition?
A HYROX® race includes 8 distinct stations interspersed with running. Table 1 summarizes the sequence, including the various distances and loads used. Although popular, these standardized competitions have received limited attention from the scientific community. Early findings suggest that a HYROX® event induces a high and sustained internal load (physiological strain), with substantial cardiorespiratory intensity and a significant contribution from anaerobic pathways, particularly during the functional stations2. The challenge is twofold: athletes must perform well in each station individually and be able to sustain the overall sequence—i.e., repeated efforts back-to-back.
What did we do to determine the demands of this type of competition?
While it is easier to measure effort and metabolic constraints for each individual station, it is more difficult to determine—or quantify—the sequential effect of this type of race on the athlete.
To address this gap, I decided to measure several metabolic parameters during a simulated Half-HYROX® (half the distances of a full HYROX®, same loads, i.e., Women Open loads). Multiple measurements were collected from one participant during this Half-HYROX® simulation.
The participant was experienced in this type of event and completed all stations in approximately 40 minutes. To make the simulation more realistic, she was assisted by a pacer to mimic race conditions. The Half-HYROX® was conducted indoors, and the running was performed on a motorized treadmill with the participant self-selecting her speed.
She wore a portable gas analyzer to quantify oxygen consumption (VO2Master), a heart-rate monitor (Wahoo) to measure heart rate, a temperature sensor (COREtemp) to measure core and peripheral body temperature, a NIRS sensor to measure thigh muscle oxygen saturation (Moxy Monitor), and a power sensor to measure running mechanical power (Stryd). Power outputs on ergometers (SkiErg and RowErg) were recorded using the PM5 consoles on the machines.
Special thanks to Émilie Boileau (participant) and Magalie Frappier (pacer) from Centre Team Boileau, who generously agreed to take part in this project.
Which variables were measured to determine the required effort?
In this project, the following variables were measured:
- VO2: VO2 (oxygen consumption) is the volume of oxygen the body uses per minute to produce energy, primarily via aerobic metabolism. As exercise intensity increases, VO2 rises (up to an individual limit: VOmax). In practice, it is measured via respiratory gas analysis: the athlete breathes through a mask and an analyzer (often breath-by-breath) quantifies inspired and expired oxygen, allowing continuous VO2 estimation during exercise—including in the field with portable systems.
- V̇E (minute ventilation): V̇E is the total volume of air breathed in 1 minute—essentially, how much air you move to bring in oxygen and eliminate CO2. It depends on breathing frequency (breaths/min) and tidal volume (air per breath). It is measured with the same type of system as VO2 (mask + metabolic analyzer), which measures airflow on each breath.
- HR (heart rate): Heart rate is the number of heart beats per minute (bpm). With a chest strap, measurement is obtained via electrodes in contact with the skin that detect the heart’s electrical signal (ECG-like) and measure R–R intervals (time between beats). HR is then calculated from these intervals and transmitted (Bluetooth/ANT+) to an app. Data can be filtered to limit artifacts (poor contact, motion, etc.).
- SmO2 (muscle oxygen saturation): SmO2 is an estimate of local muscle oxygen saturation measured at the sensor site. It reflects the balance between O2 delivery (blood flow/oxygenation) and O2 utilization by the muscle. It is measured with a NIRS sensor (near-infrared spectroscopy) placed on the skin: the sensor emits infrared light, analyzes the light returned by tissues, estimates the relative proportion of oxyhemoglobin and deoxyhemoglobin in the sampled volume, and converts it into SmO2 (%). During exercise, SmO2 typically decreases when O2 utilization exceeds delivery (rising intensity), and increases when intensity drops or during recovery (reperfusion/re-oxygenation).
- Core and peripheral temperature: Core temperature refers to the temperature of “deep” organs (trunk, brain, heart)—the internal temperature the body aims to keep within a narrow range to ensure proper physiological function. During exercise it tends to rise because metabolic heat production increases. Tracking core temperature is useful as an indicator of thermal strain: as it rises, the body must mobilize thermoregulation mechanisms (increased skin blood flow, sweating), which can affect performance, perceived exertion, and overheating risk in hot/humid conditions. It was measured using a sensor positioned on the trunk. Peripheral temperature is the skin temperature at the sensor site; it is much more variable, as it depends strongly on the environment and heat exchange (outside temperature, wind, rain, clothing, sweat/evaporation, sun exposure, etc.). In practice, skin temperature provides insight into how the body dissipates (or retains) heat at the surface.
- Mechanical power: Mechanical power represents work performed in the physics sense. Running power was measured using a foot-mounted power sensor. For SkiErg and RowErg segments, the built-in console sensors provided the values (Concept2 PM5).
How can we evaluate the effort required for each station?
Using the metabolic data, it was possible to derive indicators to evaluate the constraints imposed by each segment of the simulated HYROX® event in our participant.
I examined the difference in each variable between the start and end of every station. To obtain a clearer reading, values were normalized through a small mathematical procedure. This normalization makes it easier to compare values across stations and across individuals. Below are the details of the variable used to quantify the metabolic demands of each station “individually”:
DISN
DISN (Normalized Intra-Section Drift) is an indicator describing how much a variable increases or decreases during a section, by expressing that change relative to the participant’s individual physiological reserve.
First, compute the “raw” drift over the section:
- end 15 s: average value over the last 15 seconds of the section
- start 15 s: average value over the first 15 seconds of the section
- end 15 s − start 15 s: change over the section
Then normalize by the available reserve:
- base: pre-start reference value
- max: maximum observed (or individual maximum) value
DISN allows drift comparisons between athletes or between variables even when absolute values differ, because everything is expressed as a fraction of physiological headroom.
- A high positive DISN indicates the variable rises substantially during the section relative to remaining reserve, and is associated with high resource demand.
- A DISN near $0$ indicates a stable variable during the section, typically reflecting relatively moderate intensity for that variable.
- A negative DISN indicates the variable decreases during the section and suggests acute recovery.
I also combined some variables to create a potentially more complete picture. For example:
O2/SmO2
This is a simple way to express systemic demand (VO2) relative to local muscle oxygenation state (SmO2). In other words, how much oxygen the body consumes while the working muscle is more or less oxygenated.
A higher ratio (high VO2 and/or low SmO2) suggests a situation where the exercise creates a high metabolic demand and/or substantial muscle deoxygenation. This mismatch between systemic and local behavior may reflect a high physiological cost that is hard to sustain (i.e., a big effort that produces fatigue). A lower ratio (lower VO2 and/or higher SmO2) suggests better matching between delivery and utilization at the muscle for a given systemic demand, potentially indicating a more economical or better-tolerated effort locally.
How can we measure the cumulative effect of the event sequence?
To determine whether certain stations induce fatigue that carries over and affects the next segment, I created a variable intended to quantify residual fatigue.
Here is the normalized residual load:
CR
Normalized CR (residual load) aims to quantify the physiological level present at the very beginning of a section—i.e., what the participant carries over from the previous segment (incomplete recovery, transition too short, demanding sequence).
We compare the start of the section to the reference value (base), then express the difference as a fraction of individual reserve:
where:
- Start 15s: average over the first 15 seconds of the section (entry state)
- base: pre-start reference (rest/initial value)
- max: individual maximum (observed/estimated ceiling)
- max-base: physiological reserve for that variable
This provides a standardized measure of effective recovery between sections: the higher the CR, the more residual fatigue is present at the start of the next section. It helps identify costly transitions or sequences with insufficient recovery.
- CR approx 0 or CR <0 indicates adequate recovery with little residual fatigue.
- A large positive CR indicates substantial residual load; recovery is incomplete and prior fatigue persists and may impair subsequent performance.
How can we combine these factors?
To quantify overall effort more broadly, I simply added, for each station, the effort produced by that station to the residual load to obtain the overall physiological strain for that station.
Total strain (“Sollicitation”)
Total strain is a global indicator designed to summarize, for a given section, the physiological constraint by combining:
- what you “inherit” at the start (incomplete recovery/transition cost)
- what the section “adds” during execution (intra-section drift)
With:
So:
Interpretation:
- It represents the level reached at the end of the section, expressed as a fraction of the physiological reserve (max-base).
- High value: the section ends “high” relative to individual potential causing high overall strain.
- Low/near 0: end of section near baseline means low strain (or low-cost section, or good recovery/management).
- It is useful for comparing overall intensity across sections (run vs station, successive segments, etc.) while neutralizing inter-individual differences.
It also distinguishes two profiles leading to the same final strain:
- High CR + low DISN: you start already fatigued; the section adds little additional fatigue.
- Low CR + high DISN: you start fresher; the section drives the variable upward strongly.
What turned out to be the most difficult during the simulation?
Table 2 presents the systemic and peripheral demands of each stage of the Half-HYROX® performed by the participant, broken down into section-specific demand (DISN), cumulative carryover (CR), and total strain.
Green shaded areas represent periods where metabolic load decreases and some recovery is observed. More specifically, green zones under DISN indicate that the effort during that segment enables systemic and/or peripheral recovery depending on the measure (systemic oxygen consumption or thigh muscle oxygen saturation, respectively). Green zones under CR indicate low transfer of fatigue from the previous segment.
Orange shaded areas represent periods where metabolic load increases markedly and fatigue appears. Orange zones under DISN indicate a high effort during the segment, whereas orange zones under CR indicate substantial fatigue transfer from the preceding segment.
Stages (rows) with the most orange zones indicate moments when effort is high and fatigue accumulation is non-negligible. Notably, the H2-SkiErg stage marked the first major moment of high effort and fatigue both systemically and peripherally. Such an early effort must be followed by a recovery phase to avoid progressive fatigue accumulation, which inevitably leads to performance decline. The next run (HC3-Run) should therefore be performed at an intensity that allows peripheral re-oxygenation and appropriate matching between systemic effort (VO2) and peripheral status.
Still in Table 2, we can see that the systemic demands of that run (VO2 DISN: -0.11) allowed some recovery but were insufficient to ensure thigh muscle re-oxygenation (SmO2 DISN: 0.64). The H2-SkiErg and HC3-Run combination led to substantial lower-limb fatigue accumulation, as shown by residual load values for HC3-Run and H4-Sled Push (SmO2 CR: 0.97 and 0.93, respectively). If H4-Sled Push had been longer (as in full events), the H2–HC3–H4 sequence could have impaired performance and potentially negatively affected overall results (reduced subsequent performance due to excessive fatigue accumulation).
The H6-Sled Pull stage was well tolerated systemically, but caused more difficulty peripherally (SmO2 DISN: 1.85), generating fatigue that could not be recovered during HC7-Run and H8-Burpee Broad Jumps. This fatigue accumulation could reduce the ability to generate power during H8, decreasing distance per jump and increasing the number of jumps required to cover the distance.
After H6-Sled Pull, systemic residual load (VO2) remained relatively constant through H16-Wall Balls, suggesting an inability to fully restore systemic capacity.
The H10-Row stage substantially affected the lower limbs (SmO2 DISN: 1.99 with total strain 2.19), and this peripheral fatigue could not be cleared during the subsequent run (HC11-Run).
From H10-Row onward, we observed considerable fatigue and a fairly high effort level targeting the lower limbs, mainly due to the residual load from rowing and the nature of the subsequent exercises (run, loaded carry, and lunges). The sequence from HC11 to HC15 markedly reduced thigh muscle capacity, potentially reducing their contribution during Wall Balls and shifting emphasis to the upper body to complete the task.
In hindsight, a less aggressive effort on H2-SkiErg and possibly one or two run segments (HC5 and HC7) starting more conservatively to promote greater thigh re-oxygenation might have enabled a faster finish (HC13 and HC15). This strategy might have produced a faster overall time.
Figures 1 and 2 present the full sequence of demands: section-specific effort for each stage (Figure 1) and cumulative residual load throughout the event (Figure 2).
Practical takeaways
In light of these data, it may be beneficial for the athlete to focus on improving peripheral capacity (tolerance to local muscular fatigue) rather than trying to further improve systemic capacity (aerobic capacity, etc.). With this in mind, it becomes relevant to target local muscular endurance development as well as anaerobic power. Improving these qualities could yield small gains in the more “functional” segments, limit fatigue accumulation, and reduce reliance on running as a recovery segment.
That said, it is difficult to gain substantial time in the functional segments of a Half-HYROX®-type event; most gains tend to come from running. However, to achieve this, the athlete must: 1) avoid accumulating too much fatigue during functional stations, and 2) be able to sustain a relatively high running speed without accumulating fatigue.
Of course, the approach must be individualized to each athlete’s strengths and limitations. In this case, the athlete has a high aerobic capacity; improving it further would require substantial resources for marginal gains. Improving station performance would not drastically reduce total time. The goal then becomes to improve the physiological qualities required for functional segments—not necessarily to complete them much faster, but to complete them in an acceptable time while minimizing fatigue. This allows running to be performed at a higher intensity and potentially reduce overall time more effectively, without fatigue spilling over into the next segment.
More concretely…
To sustain the systemic load required for a short multimodal event (such as a Half-HYROX®), it is preferable to avoid running intensities exceeding about 85% of aerobic capacity. Because the running segments are flat, we can estimate that each 1 km/h corresponds to about 3.5 mLO2 x kg-1 x min-1. Running at 10 km/h is therefore approximately 35 mLO2 x kg-1 x min-1. A minimal aerobic capacity to sustain 10 km/h over 500 meters while avoiding fatigue accumulation would be around 42 mLO2 x kg-1 x min-1, ideally closer to 45-47 mLO2 x kg-1 x min-1.
The higher the aerobic capacity, the more a “fatigue-free” running speed can be sustained—and the more it becomes possible to reduce overall race time. Since running accounts for more than 60% of total event duration, it is valuable to be able to hold a higher intensity without generating fatigue, in order to avoid a progressive build-up of fatigue (residual load) from one functional station to the next—ultimately leading to performance drops or even withdrawal.
For the functional stations, it is harder to define minimal requirements. However, it is possible to gain very little time on these segments, and “opening the engine” on them risks creating excessive fatigue, leading to too large a slowdown in running or even a straightforward DNF. A HYROX® athlete therefore needs to complete the functional stations with adequate speed, but above all while accumulating just enough fatigue to still be able to run at roughly 80% of aerobic capacity and clear peripheral fatigue (SmO2 re-oxygenation).
In our participant’s case, a complete stop of 15 to 20s immediately after a functional station appeared sufficient for thigh SmO2 values to return to baseline (observation of the last recovery). With a full stop, muscle oxygen consumption drops drastically, while the ventilatory and cardiovascular systems continue to deliver substantial amounts of oxygen to the muscles. This decoupling between muscle oxygen consumption and oxygen delivery allows muscle oxygen concentration to rise quickly and markedly. This strategy—brief, complete stopping at the end of a demanding functional segment—could make it easier to maintain a slightly higher running speed without having to “refill” muscle oxygen while running. This “loss of time” of a few seconds could help prevent excessive fatigue accumulation. If a functional station turns out to be very difficult, it seems more beneficial to take a complete pause rather than a light jog in order to clear a large part of the fatigue.
Regarding the intensity used during functional stations, as a rough guideline it seems preferable to hold an intensity that could be sustained for 30% to 50% of the station’s actual duration. For example, if a sled push requires about 60 s to cover 25 m at full throttle, then in competition the athlete should hold an intensity allowing them to complete the station in 75 to 90s, to minimize excessive fatigue accumulation while keeping performance time acceptable. On the rowing ergometer, if the athlete’s best time is 2 min 20s, they should maintain a pace enabling completion of the 500 m between 2 min 40s and 3 min 45s, depending on the fatigue level present at the start of the station.
What seems fairly certain is that trying to go all-out at every step of a multimodal event leads to too much fatigue accumulation for overly modest time gains (a small reduction in time on functional stations, but too large a reduction in running speed due to fatigue).
In conclusion, multimodal events require preparation tailored to the athlete and enabling the best strategy to be applied. It is therefore important to accurately assess the athlete’s capacities relative to the demands of each segment, and to consider the cumulative effect of the efforts performed.
References
1. Villarroel López, P. & Juárez Santos-García, D. High Intensity Functional Training in Hybrid Competitions: A Scoping Review of Performance Models and Physiological Adaptations. Journal of Functional Morphology and Kinesiology 10, 365 (2025).
2. Brandt, T., Ebel, C., Lebahn, C. & Schmidt, A. Acute physiological responses and performance determinants in Hyrox© – a new running-focused high intensity functional fitness trend. Frontiers in Physiology 16(2025).