Category: Sports Science

Turning Up the Heat: Passive Heating as a Stimulus for Systemic and Muscle-Level Adaptation

For a long time we treated heat mainly as a problem to be managed — something that degrades performance and has to be defended against. That framing is increasingly out of date. A growing body of work, including studies from my own group, points to the same conclusion: a controlled dose of heat is a genuine physiological stimulus in its own right, capable of driving adaptation from the whole-body oxygen-transport system all the way down to the regenerating muscle fibre. In this post I want to bring together two recent papers on the systemic side and connect them to what we have learned about heat at the muscle level.

The through-line is simple. If we stop thinking of heat as merely a stressor to survive and start treating it as an additional training input — layered on top of, or alongside, the usual mechanical and metabolic load — we open up practical ways to enhance adaptation without adding more hard training. That matters for athletes managing fatigue, for those returning from injury, and for anyone trying to hold on to hard-won gains.

The systemic story, part 1: passive heat and VO₂max

The first study I want to write about, from Jenkins and colleagues at Cardiff Metropolitan University and published in The Journal of Physiology, asked a clean question: can passive heat — hot-water immersion, which lets athletes keep training normally rather than compromising session quality — reproduce the haematological and aerobic benefits usually attributed to exercise-in-the-heat? Ten well-trained runners completed five weeks of hot-water immersion (5 × 45 min per week at ≥ 40 °C) in a within-subject, counterbalanced crossover against a time-matched control, alongside their habitual training.

INFOGRAPHIC · HEAT AS A PHYSIOLOGICAL STIMULUS

Passive heat boosts VO₂max

5 weeks of hot-water immersion · 10 well-trained runners · within-subject crossover · 5 × 45 min/week at ≥ 40 °C

+33 g

Haemoglobin mass — the strongest independent predictor of the VO₂max gain

+284 mL

Blood volume — expansion of total circulating volume

+10 mL

LV end-diastolic volume — greater cardiac filling, with strain unchanged

+0.8 km/h

Speed at VO₂max — the adaptation translating toward performance

+2.7 mL·kg⁻¹·min⁻¹ VO₂max

Coordinated gains across the oxygen-transport chain — without adding a single hard training session.

Jenkins et al., J Physiol 2025 · DOI 10.1113/JP289874

The results are striking for a passive intervention. Hot-water immersion increased haemoglobin mass by 33 g, expanded blood volume by 284 mL, and raised left-ventricular end-diastolic volume by 10 mL — without altering systolic or diastolic strain mechanics. Those coordinated changes drove a 2.7 mL·kg⁻¹·min⁻¹ improvement in VO₂max and a 0.8 km/h increase in the treadmill speed at VO₂max. Crucially, haemoglobin mass was the strongest independent predictor of the VO₂max gain, with cardiac adaptation adding further explanatory value. The take-home is that passive heat acts on multiple convective links of the oxygen-transport chain at once — more blood, more of it carrying oxygen, and a heart filling a little more with every beat.

The systemic story, part 2: locking in altitude gains

The second study, from the same group in Experimental Physiology, tackles a problem every altitude-camp practitioner knows too well: the haemoglobin mass you build at altitude tends to melt away within about a week of coming down. If heat can expand haemoglobin mass, could it also preserve an altitude-induced expansion after descent? Twenty-one adults spent 14 days at 3800 m and, on descending to 1250 m, were assigned either to hot-water immersion (45 min at 40 °C for four days) or to a control condition.

INFOGRAPHIC · HEAT AS A PHYSIOLOGICAL STIMULUS

Hot water locks in altitude gains

21 adults · 14 days at 3800 m, then descent to 1250 m · post-descent hot-water immersion (45 min at 40 °C × 4 days) vs control

+24 g haemoglobin mass gained

across all participants during the 14-day altitude sojourn

CONTROL: –18 g

gains lost within days of descent

HOT WATER: +9 g

expansion maintained

Preservation occurred independent of EPO — circulating erythropoietin fell equally in both groups, so the mechanism remains to be resolved.

Jenkins et al., Exp Physiol 2026 · DOI 10.1113/EP093944

The divergence after descent is the headline. Haemoglobin mass rose by 24 g at altitude across the whole cohort. Back at low elevation, the control group lost 18 g — the familiar wash-out — while the hot-water group actually held on, drifting up by 9 g. Interestingly, this preservation was not explained by sustained erythropoietin: EPO declined similarly in both conditions, and plasma-volume expansion was comparable. So heat protected the red-cell expansion through a route we have not yet pinned down. Mechanism aside, the applied message is immediate: a few days of hot-water immersion after an altitude block is a low-impact, practical way to defend the adaptation athletes travelled a long way to earn.

From the bloodstream to the muscle fibre

If those two papers make the case for heat as a systemic stimulus, our own recent work makes the complementary case at the tissue level. In a study led by colleagues at Aspetar and published in The Journal of Physiology, we examined how different thermal treatments influence human muscle regeneration after a simulated injury. Thirty-four participants underwent an electrically stimulated eccentric-contraction protocol that triggers genuine myofibre necrosis and regeneration, then completed ten days of daily lower-body immersion in cold (12 °C), thermoneutral (32 °C), or hot (42 °C) water, with muscle biopsies before and at five and eleven days post-damage.

The findings ran against the reflex to reach for ice. Hot-water immersion produced lower perceived muscle pain and lower circulating creatine kinase and myoglobin than both thermoneutral and cold water. It up-regulated heat-shock proteins 27 and 70 and raised the anti-inflammatory cytokine interleukin-10, while blunting the rise in nuclear factor-κB seen in the other conditions. Cold-water immersion, by contrast, did not improve pain or reduce markers of damage, and appeared to dampen the heat-shock-protein response. In short: heat supported the muscle’s own regenerative machinery; cold did not. This is a muscle-level adaptation — a shift in the molecular environment toward repair — driven by the same physical stimulus that, systemically, expands haemoglobin mass and cardiac filling.

Why this matters: heat as an additional stimulus

Read together, these three studies tell a coherent story. At the systemic level, passive heat expands haemoglobin mass, blood volume and cardiac filling to lift VO₂max, and can preserve the haemoglobin expansion won at altitude. At the muscle level, heat tilts the local environment toward regeneration through heat-shock proteins and a more favourable inflammatory profile. The common thread is that heat is not merely a comfort measure or a stressor to be tolerated — it is a controllable physiological input that produces real, measurable adaptation on two fronts at once.

For practitioners, that reframing is the point. Heat can be programmed deliberately: to add an aerobic-adaptation stimulus in athletes who cannot absorb more mechanical load, to protect red-cell mass in the days after an altitude camp, and to support tissue repair during return-to-play rather than reflexively cooling everything down. The doses in these studies were modest and passive — 45 to 60 minutes of hot-water immersion — which makes them realistic to implement. As always, individual responses vary and heat carries its own cardiovascular and hydration considerations, so it should be dosed and monitored like any other training variable. But the direction of travel is clear, and I suspect we are only beginning to map what a well-designed heat stimulus can do.

I will keep writing about this as the evidence develops. If you are applying heat with your athletes and seeing effects — systemic or muscular — I would be glad to hear about it.

References

  • Jenkins EJ, Killick JA, Zerilli O, Douglas AJM, Corr L, Hughes MG, Tremblay JC, Stembridge M. Long-term passive heat acclimation enhances maximal oxygen consumption via haematological and cardiac adaptation in endurance runners. The Journal of Physiology, 2025. DOI: 10.1113/JP289874 (via PubMed).
  • Jenkins EJ, Koep JL, Douglas AJM, Maier LE, Howe CA, Sheitelman S, Corr LD, Siebenmann C, Hughes MG, Tremblay JC, Ainslie PN, Gibbons TD, Stembridge M. Daily hot-water immersion preserves altitude-induced haemoglobin mass expansion following descent independent of erythropoietin. Experimental Physiology, 2026. DOI: 10.1113/EP093944 (via PubMed).
  • Dablainville V, Mornas A, Normand-Gravier T, et al., Cardinale M, Candau R, Bernardi H, Racinais S. Muscle regeneration is improved by hot water immersion but unchanged by cold following a simulated musculoskeletal injury in humans. The Journal of Physiology, 2025;603(23):7603-7625. DOI: 10.1113/JP287777 (via PubMed).

What’s New in the Lactate Threshold App: Anaerobic Speed Reserve, Flexible Training Zones, Maximum Speed and More

The Lactate Threshold app started as a simple tool to turn a step test into a clean set of threshold values. Over the past few development cycles it has grown into something closer to a complete profiling and prescription workspace. This post walks through the most significant additions — anaerobic speed reserve, maximum speed determination, switchable 3- and 5-zone models — and the smaller refinements that came with them.

Anaerobic Speed Reserve (ASR)

The headline feature is the ability to determine an athlete’s anaerobic speed reserve — the velocity range that sits between the speed at maximal oxygen uptake (vVO2max, or maximal aerobic speed) and maximal sprinting speed (MSS). Everything an athlete does above their aerobic ceiling happens inside this band, which is exactly why it matters for events decided by surges, kicks and repeated high-intensity efforts.

The concept owes much to the work of Dr Gareth Sandford and colleagues, who showed that ASR and maximal sprint speed are “untapped tools” for differentiating the world’s best middle-distance runners and for understanding the complexity of athlete profiles that traditional aerobic categories miss. Two athletes with an identical vVO2max can have very different reserves above it — and therefore very different tolerances to supramaximal work — information that is invisible if you only look at threshold and VO2max.

Dr. Martin Buchheit’s research extends this directly into programming. Prescribing high-intensity work as a percentage of maximal aerobic speed alone ignores the differing mechanical ceilings between individuals, so the same session can impose very different relative stress on two athletes. Anchoring supramaximal efforts to a percentage of the ASR instead normalises that stress, and the evidence shows it reduces the inter-individual variability of physiological adaptation. The app now makes that calculation a single step rather than a spreadsheet exercise.

Maximum Speed Determination

Because ASR depends on having a reliable upper anchor, the app now supports maximum sprint speed (MSS) determination as a first-class input. Enter the result of a short maximal sprint and the app uses it as the top of the reserve, pairing it with the aerobic anchor derived from the step test. This closes the loop: from a single profiling session you get the threshold values, the aerobic speed, the sprint ceiling, and the reserve that connects them.

Flexible Training Zones: 3 or 5

Training-zone prescription is now configurable. You can choose between a 3-zone model — the classic below-LT1, between-thresholds, above-LT2 structure favoured in polarised approaches — and a more granular 5-zone model for coaches who want finer resolution across the intensity spectrum. Zones are generated directly from the athlete’s own threshold and speed anchors rather than from generic percentages, so the prescription reflects the individual profile the test produced.

Switching between the two models takes a tap, which makes it easy to align the output with whichever periodisation philosophy a given athlete or training block calls for.

Other Improvements

Alongside the marquee features, this round of work brought a number of refinements: cleaner presentation of the threshold detection results, a more consistent workflow from data entry through to zone output, and better handling of the speed-based inputs that the ASR and MSS features rely on. The aim throughout has been to keep the app fast to use rink-side or track-side while quietly adding depth for those who want it.

Development is ongoing, and I’ll keep posting updates here as new capabilities land. If you’re using the app and have feedback or feature requests, I’d be glad to hear them. If you use it for any purposes make sure you reference it:

A note for team-sport coaches: if you are specifically after a tool to plan HIIT sessions with change-of-direction (COD) prescriptions, I’d recommend Dr Martin Buchheit’s dedicated COD shuttle prescription app, available here. It is purpose-built for that use case and complements the profiling work the Lactate Threshold app is designed for. A screenshot is below.

Key References

  • Sandford GN, Allen SV, Kilding AE, Ross A, Laursen PB. Maximal Sprint Speed and the Anaerobic Speed Reserve Domain: The Untapped Tools that Differentiate the World’s Best Male 800 m Runners. Sports Medicine, 2019.
  • Sandford GN, Laursen PB, Buchheit M. Anaerobic Speed/Power Reserve and Sport Performance: Scientific Basis, Current Applications and Future Directions. Sports Medicine, 2021.
  • Buchheit M, Laursen PB. High-Intensity Interval Training, Solutions to the Programming Puzzle. Part II: Anaerobic Energy, Neuromuscular Load and Practical Applications. Sports Medicine, 2013.

Protecting Young Athletes: reflections from my talk at the 1st CYSM Conference in London

Last Friday I had the pleasure of speaking in London at the Centre for Youth Sports Medicine (CYSM) Annual Conference 2026, on a topic close to my heart: how we protect young athletes while helping them develop. My talk was titled “Protecting young athletes: performance progressions, realistic expectations and injury prevention,” and what follows is a short summary of what I covered, the science behind it, and a new project I shared at the end

Young athletes are not mini-adults

The starting point of the talk is a simple but frequently ignored idea: a young athlete is not a scaled-down version of a senior one. Youth development sits on an individually unique and constantly changing base of physical growth, biological maturation and behavioural development. Because of this, success at an early age does not guarantee success at senior level, and selection systems in most sports quietly favour early maturers — children who happen to be bigger and stronger sooner, not necessarily those with the most long-term potential.

This matters because the way we coach, test and select needs to account for where a child actually is in their development, not simply how many years have passed since their birth.

Age is not just a number

A large part of the talk dealt with the difference between three kinds of age:

  • Chronological age — years since birth.
  • Training age — how many years a young person has spent in structured training.
  • Biological age — where the individual actually sits on the maturation curve, based on physiological markers.

Two children of the same chronological age can be years apart biologically. Around the growth spurt — the period of Peak Height Velocity (PHV) — this gap becomes especially important for training and injury risk. I walked through the methods we use to assess maturity status and timing, from skeletal age estimation (Tanner–Whitehouse, Greulich–Pyle, Fels) to anthropometric approaches based on height, leg length and body mass. I also flagged an important caution from our own work: prediction methods developed on one population can systematically over- or under-predict in another, so the difference between skeletal and chronological age should be used to put test results into context rather than as an absolute truth (for some recent work on this, read this paper from Dr Lorenzo Lolli here).

Talent, the relative age effect, and the road from youth to senior

I then turned to talent identification and the relative age effect — the well-documented bias in which athletes born early in the selection year are over-represented in youth squads and ranking lists. Across athletics and team sports such as Italian football, the data show how strongly birth-quarter skews youth selection. Yet relatively younger or later-maturing athletes often progress better when they transition to senior level — the so-called “underdog hypothesis.”

This connects to one of the central findings I shared, drawn from analyses of tens of thousands of athletes’ careers: early success is not a prerequisite for success as an adult. In jumping events in track and field, only around 8% of males and 16% of females ranked in the world top 50 at age 16 went on to reach the top 50 as seniors. In sprints, on average only about 17% of men and 21% of women were in the top 50 both as under-18s and as seniors. Different pathways can lead to similar outcomes, and many talented juniors never make the transition — for reasons ranging from maturation and selection bias to injury, burnout, loss of funding, or simply moving to another sport.

Injuries and load in young athletes

The final scientific section focused on injury. Young athletes face a distinct set of growth-related conditions — Osgood-Schlatter disease at the knee, Sever’s disease at the heel, gymnast’s wrist, Little League shoulder and elbow, apophysitis around the hip, and more. Our own prospective work in a full-time athletics academy was, to our knowledge, the first to examine growth rates and skeletal maturation as injury risk factors in a large adolescent cohort engaged in full time athletics. We found that rapid growth in stature and leg length, a younger skeletal age and a faster maturity tempo were all associated with an increased risk of bone and growth-plate injuries.

This raises hard questions about how we manage load. Most studies still quantify training simply as “time,” without accounting for what athletes actually do in that time — two athletes can train for the same number of hours doing completely different work. Better load monitoring, including the thoughtful use of wearables and AI, is one of the areas where I think we can genuinely improve.

The book chapter: The Young Athlete

Much of this material is drawn together in a chapter I co-authored with Gennaro Boccia, Paolo Riccardo Brustio, James Baker and Eirik Halvorsen Wik — Chapter 9, “The Young Athlete,” in the Sports Physician Handbook (Fourth Edition of the FIMS Team Physician Manual), edited by Pitsiladis, Yung, Hutchinson and Pigozzi (Academic Press, 2026, pp. 199–235, the link the book is here).

The chapter brings together the themes of the talk into a single reference for clinicians and practitioners: defining the elite young athlete, understanding growth and maturation and why they matter, the relative age effect and the junior-to-senior transition, performance progression and realistic expectations, and the prevention and management of youth injuries and illness — including data from recent Youth Olympic Games.

A thank you to the CYSM, ISEH and the audience

I want to thank the Center for Youth Sports Medicine and the Institute of Sport, Exercise and Health for hosting me and for the care they put into convening this event. The ISEH has been a genuine centre of excellence for sport and exercise medicine since its creation as a legacy of the 2012 London Olympic Games, and its commitment to the health of young athletes is exactly the kind of leadership this field needs. I was equally grateful for the audience — the questions, the engagement and the obvious dedication of so many practitioners to getting this right. Youth sport sits at the intersection of health, development and performance, and it is genuinely encouraging to see so much interest in protecting the young people at the centre of it.

Bringing athletics data to life: a new (experimental) project

One recurring frustration in this area is that the data needed to put a young athlete’s results into context — how the best in the world actually developed over time — is hard to access and harder to compare against. So I have been building something to help coaches interested in Athletics.

I am sharing here an early look at the Athletics Performance Tracker, an AI-assisted project that brings athletics results databases to life and makes them accessible to everyone. The aim is to let coaches, athletes, parents and researchers explore how performance develops with age and compare a young athlete’s results against those of top-ranked athletes.

It currently covers around 30 World Athletics events with thousands of athletes and tens of thousands of performances, and includes:

  • Development curves showing how the world’s best progress from age 12 to 40, with mean values and confidence intervals across the top 10, 20, 50 or 100 athletes.
  • Year-on-year analysis of absolute and percentage improvements for individual athletes or whole cohorts.
  • World top lists for every event, with comparisons to the previous year.

You can explore it here: athletics-tracker.fly.dev.

An important caveat: this is very much an experimental project and still under active development. It is intended for research and exploration, it is not affiliated with World Athletics, and features and data will continue to change. I would welcome feedback as it evolves.

In summary

Early success is not a requirement for success as an adult. Assessing maturity status is key to interpreting training and test results. Training should be progressive, varied and developmentally appropriate, and we need to understand injury patterns — and load — far better than we currently do, with more work needed on young female athletes in particular. Above all, health and longevity in sport should always come before performance at a young age. If we get that balance right, we give more young athletes the chance to fulfil their potential — and to stay healthy doing it.