Diplomatic Security Service (DSS) Officers
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What Australian SF Selection Can Teach American Candidates About Recovery, Resilience, and Readiness

Selection isn’t just about who’s the strongest, not even close. It’s about who can keep going when their body and mind are breaking down, and then keep going again the next day.

That’s exactly what a recent study (2024) by Angela et al on the Australian Special Forces Selection Course (SF-SC) set out to understand: what actually happens to the human body under this kind of sustained stress, and how long it takes to bounce back.

Over nearly 3 weeks, 93 soldiers endured relentless physical training, 50–60 kg rucks, brutal terrain, food and sleep deprivation, and an estimated energy deficit of ~3,800 calories per day (expenditure: 7680 ± 1095 kcal/day, intake: 3859 ± 704 kcal/day). Researchers tracked their physiology before, immediately after, and for weeks following the course.

The results? Significant losses in both fat and lean mass, hormonal crashes, and a suppressed metabolism, even in highly trained military personnel. And while most markers eventually returned to baseline, recovery wasn’t instant. Let’s break down the methodology and key findings from the research, and more importantly, what lessons American SOF candidates should take away from it.

1. research methodology, sample space, and metrics

1.1 Sample Space

This study included 93 healthy, active-duty male soldiers from the Australian Defence Force who voluntarily attempted the 2021 Australian Special Forces Selection Course (SF-SC). Participants averaged:

  • Age: 28.1 ± 3.6 years
  • Service: 7.4 ± 3.2 years in the military
  • Height: 1.81 ± 0.07 m
  • Body mass: 85.1 ± 8.1 kg
  • Lean mass: 71.3 ± 6.3 kg
  • Body fat: 13.7 ± 2.3%

? Only those who successfully completed the selection course were tracked in follow-up testing for recovery.

1.2 Data Collection

Participants were assessed at six points:

  • Baseline (after 14-day hotel quarantine)
  • Immediately post-course
  • 1 week post-course
  • 3 weeks post-course
  • 5 weeks post-course
  • 8 weeks post-course

Let’s take a quick look at how everything was measured:

Body Composition: Body fat, lean mass, and regional tissue loss were measured via DXA scans, taken in fasted states, post-rest, and following standard prep procedures. Scans were conducted at 0600–0900 to control for circadian variability.

Hormones: Blood draws measured hormonal shifts in testosterone (total and free), cortisol, SHBG, IGF-1, and thyroid hormones (T3, T4, TSH) using validated, sensitive assays. These were used to track both catabolic and anabolic physiological shifts during and after the Special Forces Selection Course.

Metabolic Rate: Resting metabolic rate was measured via indirect calorimetry using the Parvo Medics TrueOne metabolic cart. Data was normalized to fat-free mass for accurate comparison across time points.

Energy Expenditure: TDEE was assessed using the gold-standard doubly-labelled water (DLW) technique during the first 10 days of the course. This made sure the researchers had precise data on caloric burn under extreme military conditions.

Energy Intake: Food intake was meticulously tracked by sports dietitians, using actual kitchen recipes, pre-/post-meal food weights, and returned ration components. Intake was compared against TDEE to determine the magnitude of energy deficit.

1.3 Metrics of Success

Unlike traditional performance metrics like pull-ups or run times, this study focused on physiological survival and recovery as its core success measures. These included:

  • Loss and recovery of body mass (fat and lean)
  • Changes in hormonal markers (testosterone, cortisol, SHBG, etc.)
  • Resting metabolic rate before and after the course
  • Energy balance (caloric intake vs. expenditure)
  • Time required for physiological systems to return to baseline

There were no pass/fail physical standards analyzed. The study’s core aim was to understand the toll of SF selection on the human body and how long recovery truly takes.

2. Energy Intake and Expenditure

As expected, the attrition rate of the SF-SC was crazy high. Among the 93 participants who started the course, only 24 (25.8%) completed it. And 20 (21.5%) were subsequently selected for SF qualification training (next round).

Ask any operator what crushes candidates during selection, and the answer won’t just be the mileage or the weight on their back: it’s the energy drain.

2.1 A Daily Deficit Approaching 4,000 Calories

During Phase One of the SF-SC (the first 9 days), total daily energy expenditure (TDEE) was measured using the doubly-labelled water method, the gold standard for energy tracking in extreme environments. For the 34 candidates whose data were viable, average energy expenditure clocked in at a staggering 7,680 ± 1,095 kcal per day.

Now, compare that to what they were eating; it comes out to be just 3,859 ± 704 kcal per day. That’s a daily caloric deficit of roughly 3,823 kcal, or nearly 50% less than what they were burning. And that was just Phase One.

2.2 Macronutrient Breakdown by Phase

Let’s break it down even further. Phase 1 saw a mix of fresh food and combat rations. Phase 2 relied entirely on CRPs, but total intake slightly increased.

PhaseTotal Energy IntakeProtein (g/day)Carb (g/day)Fat (g/day)
Phase 13,859 kcal163 g (1.9 g/kg)463 g (5.4 g/kg)142 g (1.7 g/kg)
Phase 24,139 kcal136 g (1.6 g/kg)611 g (7.2 g/kg)148 g (1.7 g/kg)
Phase 3446 kcal23 g (0.3 g/kg)58 g (0.7 g/kg)14 g (0.2 g/kg)

Phase 3, the hardest phase involving intentional sleep and food deprivation, dropped calorie intake to an average of just 446 kcal/day. That’s survival-level nutrition, not performance fuel.

2.3 Insights for American SOF Candidates

Whether you’re prepping for the Q-Course, BUD/S, or RASP, you need to understand what sustained caloric deficit actually does to your body. You’re not just “getting leaner,” you’re burning through fat, muscle, and hormones (as we’ll see with the next metric).

Even with carefully prepared military rations, the operational demands of SF selection massively outpace intake. And that deficit is by design, not a logistics failure.

To summarize, it basically highlights the need for pre-course physical preparation (especially muscle mass and endurance), tactical eating strategies (when possible), and most of all, mental resilience to keep performing when your tank is empty.

3. Body Composition

Special Forces Selection isn’t a fat-loss bootcamp. Calling it a full-body breakdown instead would be more apt. The energy deficit we discussed earlier burns far more than just calories, it carves away at your muscle, fat, and overall mass. Let me explain.

3.1 Average Losses During the Course

By the end of the 19-day selection, this what happened:

  • Average body mass dropped by 6.8 ± 1.9 kg, or 8.2% of total weight.
  • Fat mass dropped by 4.2 ± 1.0 kg, a whopping 36.1% on average.
  • Lean mass (i.e., muscle) dropped by 3.0 ± 1.7 kg, or 4.3%.

And the most interesting part? Every result had a p-value < 0.01, meaning these were statistically significant, not flukes.

3.2 Regional Body Composition

Not all weight loss is equal, especially under extreme stress. Thanks to the DXA scans, we can break down exactly where candidates lost fat and muscle across the body. Here’s how the regional breakdown looked:

Baseline (n=20)Immediate follow-up (n=20)1 week follow-up (n=17)3 week follow-up (n=14)5 week follow-up (n=19)8 week follow-up (n=17)
Trunk      
Lean Mass (kg)33.6 ± 2.6232.40 ± 2.8634.7 ± 3.1435.10 ± 2.5634.30 ± 3.1033.70 ± 3.45
Fat Mass (kg)4.84 ± 1.092.55 ± 0.693.49 ± 0.805.04 ± 0.774.87 ± 0.765.59 ± 0.98
Lower Limbs      
Lean Mass (kg)23.6 ± 1.7322.20 ± 1.7523.80 ± 1.9224.50 ± 1.4324.00 ± 1.8623.50 ± 1.79
Fat Mass (kg)4.39 ± 1.122.95 ± 0.893.38 ± 0.934.31 ± 0.814.17 ± 0.884.94 ± 1.06
Upper Limbs      
Lean Mass (kg)9.21 ± 0.788.97 ± 0.789.18 ± 0.939.63 ± 0.829.46 ± 0.969.36 ± 0.98
Fat Mass (kg)1.31 ± 1.210.93 ± 0.201.06 ± 0.211.33 ± 0.161.37 ± 0.201.55 ± 0.26

Trunk (core & torso):

  • Lean mass dropped from 33.6 kg to 32.4 kg (?1.2 kg, p < 0.01), but rebounded by Week 1.
  • Fat mass nearly halved, dropping from 4.84 kg to 2.55 kg (?2.29 kg, p < 0.0001). It shot back up after Week 1, and exceeded baseline levels (5.59 kg, p < 0.05) by Week 8.

Lower limbs (legs):

  • Lean mass dropped from 23.6 kg to 22.2 kg (?1.4 kg, p < 0.01), then recovered by Week 1–3.
  • Fat mass fell from 4.39 kg to 2.95 kg (?1.44 kg, p < 0.0001), and again, like the trunk, surpassed baseline by Week 8 (4.94 kg, p < 0.05).

Upper limbs (arms):

  • Lean mass barely changed, staying close to 9.2 kg throughout. Not statistically significant.
  • Fat mass, however, dropped from 1.31 kg to 0.93 kg (p < 0.0001) — the most extreme percentage loss of fat anywhere. And again, by Week 8, it had climbed past baseline (1.55 kg, p < 0.01).

In conclusion, the trunk and legs took the biggest hit in both metrics. And while muscle mass came back quicker, fat not only made it back to baseline, but also overshot at times.

3.3 The Recovery Window

Box and whisker plots of changes in A: Body mass (kg), B: Lean mass (kg), C: Fat mass (kg), D: Fat mass % over time
  • Body mass and lean mass returned to baseline by Week 1 post-course.
  • Fat mass, however, took longer, returning to baseline around Week 3.

Here’s the frequency of how quickly candidates gained recovered:

  • +0.123 kg of total body mass per day
  • +0.090 kg of fat mass per day
  • +0.036 kg of lean mass per day

So yes, recovery happened, but it wasn’t overnight. If you’re planning a long training pipeline (like most U.S. SOF candidates are), you need to factor in this lag time.

4. Hormones

This is where things get ugly (and/or fascinating). The body doesn’t just burn through calories and mass under stress… it scrambles the hormonal dashboard too. After nearly three weeks of punishing workload and deprivation, here’s what happened to key hormones:

4.1 Hormonal Cost of Pushing Your Limits

What Crashed (and Hard):

  • Total Testosterone (TT): Dropped 86.3%
  • Free Testosterone (FT): Down 92.6%
  • IGF-1: Decreased 71.4%
  • Thyroid hormones: T3: ? 58.3%, T4: ? 44.1%

This hormonal nosedive mirrors what we see in severe overtraining (and/or starvation). It’s the body’s way of conserving resources. But make no mistake: these are the very hormones that keep you sharp, strong, and resilient.

What Spiked:

  • Cortisol, the classic stress hormone, went up by 74.9%
  • SHBG, which makes free testosterone even less available, rose by 131.1%

That’s a double whammy if you ask me. Not only are testosterone levels bottomed out, but what’s left is bound up and unusable.

Box and Whiskers Plot for A. Total Testosterone and B. Free Testosterone
Box and Whiskers Plot for C. SHBG and D. Cortisol
Box and Whiskers Plot for E. IGF-I and F. TSH
Box and Whiskers Plot for G. T3 and H. T4

4.2 Recovery Timeline

Let’s talk about recovery now. Total Testosterone, Cortisol, and SHBG went back to baseline as early as week 1. In comparison, Free Testosterone, T3, and T4 came back to baseline by the third week instead.  Finally, IGF-1 was within the reference range after week 1 but full baseline recovery was not reached even after week 8.

4.3 Insights for American SOF Candidates

If you’re heading into back-to-back training cycles (like we often do post-selection in the United States), this is your warning sign. Just because your testosterone levels look recovered on paper doesn’t mean everything is running at 100%. IGF-1, which plays a major role in growth and tissue repair, takes longer.

You need to build recovery time into your training or risk hitting the next phase underpowered, hormonally compromised, and with a suppressed ability to adapt to stress. It’s better to have a 1 on 1 coach (such as myself) planning and personalizing your training in real-time based on your needs.

5. Resting metabolic rate

Baseline (n=20)Immediate follow-up (n=20)1 week follow-up (n=17)3 week follow-up (n=14)5 week follow-up (n=19)8 week follow-up (n=17)
RMR (kcal/day)1970 ± 1671810 ± 1542240 ± 2062130 ± 1792140 ± 2912070 ± 173
RMR (kcal kg/FFM)27.0 ± 1.7525.9 ± 2.3330.3 ± 2.0628.1 ± 1.8228.8 ± 3.6328.4 ± 2.55

Most SOF candidates assume the only thing dropping during selection is weight. But what happens to your engine, the resting metabolic rate (RMR), is just as critical.

During the SF-SC, RMR dropped by an average of 162 kcal/day (~8%). That’s quite a big hit, especially considering it happened in highly trained personnel who were already near peak conditioning. And the drop was statistically significant (p < 0.01) too.

By Week 1 post-course, RMR jumped to 2240 kcal/day, which is significantly above baseline. This rebound was statistically significant as well (p < 0.001) and stayed elevated through Week 5, only beginning to taper by Week 8.

When adjusted for lean mass (kcal/kg FFM), the same pattern holds.

What does this actually mean? The research team found conclusive evidence that your body doesn’t just recover after a selection course, it actually overcompensates.

This rebound effect suggests your system is trying to quickly rebuild what it lost. From a training perspective, this is an ideal window: your metabolic engine is fired up, recovery systems are in high gear, and you’re more anabolic than usual. Of course, you also need to provide proper fuel to your body as well.

Final Thought

The TDEE for the Australian SF-SC was higher than US Special Forces Assessment and Selection (~5182 kcal/day) and US Ranger Assessment (~4262 kcal/day). The difference is likely due to longer duration, more intense sustained activity, and heavier load carriage (50–60 kg vs 20 kg in US courses).

Selection strips away everything that isn’t essential, be it physical, mental, or emotional. This study is a reminder that the process is biologically designed to break you down. Your preparation must be equally intentional, not just in how you train, but in how you recover and rebuild.

If you want to optimize your selection prep, you can reach out for 1 on 1 coaching.

Source: The physiological consequences of and recovery following the Australian Special Forces Selection Course by Angela C. Uphill, Kristina L. Kendall, Bradley A. Baker, Stuart N. Guppy, Hannah M. Brown, Michael Vacher, Bradley C. Nindl, G. Gregory Haff (Applied Physiology Nutrition and Metabolism, 2025, link)