Shownotes

Is training response repeatable within the same person?

01:15 -

• The first study is from a Norwegian group led by Odden, and it asks whether individual training responsiveness is repeatable within the same person.
• The design is clean.
• Untrained participants, roughly half men and half women, completed an eight-week programme, then detrained for eight weeks until their fitness returned to the original baseline, then repeated the identical eight-week programme. 
• The question was whether the same person, starting from the same baseline and doing the same training, produces the same physiological and performance adaptation the second time around.
• Training was three sessions per week on average, some weeks two and some weeks four, at about 45 minutes each, built from threshold-style intervals and short VO2 max intervals, plus four by five minutes at maximal intensity that was used to progressively overload and set the power targets for the other sessions.
• Outcome measures included VO2 max, blood markers such as haemoglobin, and 15-minute time-trial power.
• At the group level, the average gains were similar across the two periods.
• The 15-minute time-trial power rose by about 17 watts in the first block and 22 watts in the second, roughly a 15 to 16 percent improvement, which is a good gain and one that makes sense given how untrained the group was to start with. 
• At the individual level, the relationship between how much a person improved in the first block and how much they improved in the second was poor to nonexistent.
• The best responder the first time was not necessarily the best responder the second time. The title states it plainly: limited reproducibility of individual physiological adaptations to repeated endurance exercise training.

Takeaways

05:23 -

• The first thing this connects to is the family of fitness-fatigue models built into so much training software, which take training load, intensity or volume as inputs and try to predict future performance. 
• If the response to identical training is not repeatable within the same person, it is hard to see how a model like that can predict future performance with any precision.
• On that reading the study challenges most of the commercial implementations that claim to do exactly that.
• The implication in those models is rarely stated outright, but plenty of athletes read them as meaning more load equals more performance, and this is an example of where that does not hold.
• Reading the statistics more carefully, though, I am not convinced the practical picture is as stark as the title suggests.
• Most participants still improved by a meaningful amount in both blocks. What varied was the size of the improvement, so someone might gain 10 watts in the first block and 30 in the second, or 30 in the first and 20 in the second.
• That variation drives the poor correlation, but it is roughly what I would expect from humans rather than robots.
• Reproducibility here is measured with an intraclass correlation, and when a large number of people are clustered around a 15-minute power of about 150 watts and move to 160 or 170, the changes are small and close together, which drags the correlation down.
• A variable with more spread between people would look more reproducible even if the underlying biology were noisier.
• The authors raised this statistical point themselves, though in a different part of the discussion rather than as a limitation. I am not critical of the study. It depends on what you expected reproducibility to look like.
• My first assumption from the title was that perhaps half the group would fail to improve at all in one of the blocks, and that was not the case.
•  The training response to an identical programme is not very predictable once you stop controlling everything outside training. 
• Diet, life stress, sleep and psychosocial load were not controlled, and any of them can shift whether the body is in a responsive state in a given period.
• With a 24-week protocol per person, even the time of year matters. Running the first block in cool spring weather and the second in summer heat could push adaptation either way, adding heat stress that drives more adaptation or simply degrading the quality of the second block.
• The lab's climate control was not described, so this cannot be ruled out.
• The conclusion the authors draw is that you cannot expect an identical result every time you repeat a programme, so it is better to optimise training at the group level than to over-read a single individual response.
• Responding poorly once to a good programme does not mean you will respond poorly the next time. Heraclitus fits here: no one steps in the same river twice, because neither the river nor the person is the same again.
• This also points at the overlap between neurology, psychology and endurance adaptation, the psychobiological side of training, where emotional and psychosocial state during and after training influences the molecular signalling behind aerobic adaptation, things such as PGC-1 alpha and mitochondrial biogenesis. 

Results for a decent amateur athletes

17:10 -

• The expectation is more reproducibility, not less. A good follow-up would split trained and untrained groups and rerun the analysis, and it does not need professional athletes, just well-trained ones.
• Well-trained athletes standardise everything around training, sleep, recovery and nutrition, so there is less outside noise to disturb the response.
• In untrained, non-competitive participants, life outside training can be disrupted far more easily, and that is exactly what moves the adaptation around.
• The same warning applies to time-crunched amateurs. It is not only about the training.
• The wider point stands, that most of these athletes did improve both times, but with real differences of size for the same person on the same programme from the same baseline, so something outside training was doing a lot of the work.

Heavy strength training for cyclists: a meta-analysis

20:25 -

• My first pick is a systematic review and meta-analysis on the effects of heavy strength training on the physiological determinants of endurance cycling performance.
• They describe it as the first meta-analysis to look exclusively at cyclists rather than pooling cyclists, runners and triathletes, which was a surprise, since there are plenty of mixed-sport meta-analyses.
• Heavy strength training here meant at least 80 percent of one-rep maximum, which they translated to roughly a seven-rep maximum, the kind of load you can lift about seven times.
• Outcome measures were VO2 max, threshold, maximum metabolic steady state, gross efficiency and other measures of efficiency, peak power output, anaerobic capacity as the 30-second Wingate power, and cycling performance as time-trial or time-to-exhaustion tests.
• They included 17 studies with 262 participants, 60 of them women.
• The findings line up with earlier single studies.
• No effect on VO2 max, threshold or anaerobic capacity, but moderate effects on time-trial and time-to-exhaustion performance and on anaerobic power, which was the one-to-five-second peak power, and a small effect on cycling efficiency, which they suggest feeds the performance improvement.
• Reanalysing and aggregating the raw data confirms what the narrative reviews had been pointing at, that strength training works.
• The recommendations are useful. A typical prescription is at least an eight-week block of two strength sessions per week, after which the gains can be held for up to 13 weeks on a single session per week, or maintained through six to eight weeks of no strength training at all.
• For session content they recommend four lower-body exercises, mixing bilateral and unilateral movements, for example squat, single-leg leg press, leg curls and single-leg calf raises, at three to four sets per exercise with two to three minutes of rest between sets, progressing from an 11-rep maximum down to a four-rep maximum, roughly 70 to 90 percent of one-rep maximum.
• That progression looks like the authors' own practical recommendation rather than the exact protocol used in the trials, and it is a reasonable one.
• For triathletes I would do this a little differently.
• In a triathlon strength programme there is more to fit in, so I would cut back to two or three of these heavy lower-body lifts per session and add one or two plyometric exercises, along with whatever running injury-prevention work an individual athlete needs for their weak spots, which sometimes overlaps with the heavy lifts and sometimes does not.
• If the programme runs longer than eight weeks and is more or less year-round, four heavy lifts every session is not needed, and two or three heavier lifts per session is plenty, most likely for similar results, though that specific comparison has not been tested.
• The usual objection to strength training is logistics, particularly holding it through the competition period, but in 2026 that objection is weak.
• Gyms are everywhere, and one session per week in-season is not physiologically costly if the rest of the week is planned around it.

Home-based equipment 

28:25 -

• Even basic equipment at home covers a wide range of exercises, and you do not need machines or a leg press when free weights in a small space will do. 
• There is also a more expensive all-in-one option, a portable unit with a handle and cable resistance that lets you cover deadlift and squat-type movements in a small footprint.
•  The main advantage of training at home is that it removes the commute, which is the first thing to get skipped when time is short, even when the gym is only five minutes away.
• The meta-analysis tested whether the effect depended on muscle mass, age or sex, and found no such moderating factor.
• Anecdotally I would have guessed strength training does more for athletes with lower muscle mass, whether smaller male athletes, female athletes, or older athletes carrying some muscle atrophy, but the data did not support that.
• And for anyone interested in the mechanisms, figure five in the paper maps out the proposed pathways from strength training to cycling performance, and the paper is open access.
• The improvements are structural and neuromuscular rather than metabolic, and it is not fully clear which neuromuscular adaptations are responsible.
• Better muscle recruitment is part of it, and pedalling technique may be another part, since one study linked technique to cycling efficiency through a reduction in the dead spots of the pedal revolution.
• A Rønnestad study found that after strength training the peak torque was reached earlier in the pedal revolution, which leaves more of the revolution in a phase where blood flow can increase, a plausible link between strength training, improved efficiency and improved performance.

A 50-year review of intensity, VO2 max, mitochondria and capillaries 

35:30 -

• The next study is the big one, a very large retrospective review from a Norwegian group, covering roughly 50 years of endurance training studies up to 2024, on the order of 500 studies and 6,000 participants.
• It examines how low and high intensity training affect VO2 max, muscle capillarisation and mitochondrial adaptation.
• Three categories were compared: low intensity below the second threshold, high intensity above the second threshold, and sprint training, meaning maximal or submaximal efforts up to about 20 to 30 seconds with long recoveries, distinct from short VO2 max intervals.
• The first takeaway, and the one people most often miss, is convergence.
• Both low and high intensity produce similar aerobic adaptations, improved VO2 max, improved mitochondria and improved capillarisation, and even sprint training produces VO2 max and mitochondrial gains.
• It is not the case that zone 2 builds your mitochondria while VO2 max work builds your VO2 max. Everything converges toward a similar aerobic phenotype.
• That cuts straight against the social-media framing of any one intensity as a magic bullet.
• The same trends held in both untrained and trained participants, with the 30 VO2 max group showing the same pattern as the 55 to 60 group.
• Lower fitness meant a bigger absolute improvement, but the trends themselves were reproducible across fitness levels.

Intensity zones

41:15 -

• The second takeaway is what happens when you standardise per unit of time. Hour for hour, higher intensity gives greater aerobic adaptation. 
• That is intuitive, but worth stating because the social-media version sometimes implies that an hour of zone 2 builds more mitochondria than an hour of high intensity, which it does not.
• The trap is to conclude that you should therefore do as much high intensity as possible.
• You cannot, because the tolerable weekly volume of low intensity is far higher, as it is less stressful and less straining.
• Low intensity is not better per unit of time, it is the only way to add the volume that complements the small, powerful dose of high intensity you can absorb without accumulating too much strain.
• The answer stays pyramidal or polarised, and the share of low intensity should scale with total volume, so the lower the total volume, the smaller the proportion that needs to be easy.
• The reproducibility study is an extreme illustration of that, since at 2 hours 15 minutes per week, the participants did slightly more than half their time in the heavy-to-severe domain and still improved substantially without a large aerobic base.

Intensity stimulus

45:40 -

• The third takeaway, and the most interesting, is the time course. Most training studies run two to six weeks, and over that window, higher intensity drives faster gains.
• But over longer timeframes, the picture changes. Sprint training appears to plateau earliest, around four to six weeks, high intensity around 15 weeks, while low intensity keeps yielding for longer.
• These are trends rather than exact numbers. The practical read is that to play the long game you base a large share of training on low intensity and concentrate high intensity into specific periods of the year, taking advantage of its fast but early-plateauing effect.
• Training frequency mattered too. 
• Comparing two, four and six sessions per week, higher frequency had a positive effect on most or all of the measured variables, which is a useful data point for single-sport athletes training only three times a week, where adding even short sessions could help.
• An open question is whether splitting a given daily load into double sessions changes adaptation. There is evidence that it lowers next-day strain, but no human adaptation data.

VO2 max improvement

48:15 -

• VO2 max is in this analysis directly, and stroke volume is the main determinant of VO2 max, so from the VO2 max values you can reasonably assume similar trends for stroke volume.

Lactate threshold as a share of VO2 max, and why VO2 max still rules 

50:36 -

• My second pick, by Johansen and colleagues from Norway, is a brief report asking whether elite aerobic endurance performance is really related to lactate threshold expressed relative to peak oxygen uptake.
• It uses test data already gathered and published from a large group of athletes, 292 in total, made up of 71 elite, 158 national-level and 63 regional-level athletes, across running, cycling and cross-country skiing, and 212 men and 80 women.
• Lactate threshold as a percentage of VO2 max averaged about 79 to 80 percent in all three groups, with no difference between them, though the range was wide, from roughly 70 to 90 percent within every group.
• VO2 max itself differed clearly, about 71 for the elite athletes, 66 for the national level and 58 for the regional level.
• Speed or power at threshold also differed between the groups, but moved directly with VO2 max and economy.
• The classic model treats fractional utilisation at threshold as one of the main determinants of endurance performance, but that idea came from studies of homogeneous elite groups, where everyone already has a high VO2 max and the percentage of VO2 max at threshold becomes an important separator.
• Across a broader range of ability it no longer separates the groups, and VO2 max does.
• The authors also noted, citing earlier work, that lactate threshold as a percentage of VO2 max is not easy to move through training, which I had not seen stated so directly before.
• The practical message is that VO2 max is underrated, especially among triathletes, where you sometimes hear that it stops mattering at Ironman distance. It matters at every distance, and this is a solid dataset showing it.
• A practical rule of thumb that fits this is that a road cyclist can compensate at most five to seven VO2 max points through superior economy and fractional utilisation.
• A rider at 75 can race with someone at 80 to 82, but a rider at 68 will never overcome someone at 80 on economy and fractional utilisation alone, because those two vary far less than VO2 max does. 
• Economy is genuinely important as well, which is where strength training comes back in, since for both cycling and running it is one of the few known ways to improve economy or gross efficiency, alongside simply doing a lot of volume.
• Beyond those, the options thin out to some sprints on the bike or strides on the run, with little data behind them.

VO2max testing

59:15 -

• What is worth having is a good VO2 max, not necessarily a measured number. You can get a decent read on it without a lab.
• Five-minute power maps onto VO2 max reasonably well, and a change in ramp-test performance usually tracks a change in VO2 max, which is why a ramp test on an indoor platform such as ROUVY works as a rough monitor even though it is a poor way to set FTP.
• A past guest, Michael Rosenblatt, has discussed this. The caveat is that a better five-minute power, or a better ramp result on short 30-second to one-minute steps, can come partly from an improved W prime or anaerobic reserve rather than a true VO2 max change, so the test design matters.  
• Estimates of economy are not available that way, but within a given athlete economy changes little, so the estimate holds up reasonably.
• The VO2 max figures from a Garmin are less useful, since those algorithms fold in heart rate, which makes little sense, and I would not read much into them.
• For an already-trained athlete there is little training rationale to pay for a lab VO2 max test, since knowing the number does not tell you how to structure training. It is mostly curiosity.

Fractional utilization of VO2 max

1:05:20 -

• Fractional utilisation is more promising for individualising sessions. A recent paper from the same Norwegian group, involving Odden and Rønnestad, suggests you can pick a session format from it.
• With a low fractional utilisation of VO2 max at threshold, short intermittent VO2 max intervals help hold a high fraction of VO2 max through the session, while with a high fractional utilisation the long intervals, around four minutes, sustain a high percentage of VO2 max at least as well.
• The problem is estimating fractional utilisation in the field. You can take a ratio of critical power, treated as the second threshold, to five- or six-minute power, treated as power at VO2 max, but that ratio is not the same as true fractional utilisation, because you cannot know how much of that five- to six-minute power is anaerobic reserve.
• It works to compare athletes against each other, not to pin down an individual's absolute number. 
• As a coach with a large database you can build a distribution and read an individual against it, but an athlete on their own cannot tell whether their ratio is high or low without gathering the same data from a club or training group.
• One way to push it further would be to add a one-to-two-minute time trial, categorise athletes as likely high, medium or low W prime, and build a separate distribution for each category, though that is probably overcomplicating it.
• It is a genuine research project for anyone with power-meter data and matching lab tests, and a linear regression there could let athletes estimate this without a lab visit.
• Where a lab test does earn its place is comparing technologies.
• Testing two or three pairs of super shoes to find the one you are most economical in is worth it, as is checking the effect of equipment or position changes on economy, and fractional utilisation from a metabolic test can add something for training in a way the threshold-versus-VO2-max question on its own does not.

LINKS & RESOURCES

LINKS & RESOURCES

• Follow Gabriele and KnowledgeIsWatt on his website, Substack and Instagram
• The shownotes for today's episode can be found here. 
• The full podcast episode archives (including category filters) can be found here. 
• Limited reproducibility of individual physiological adaptations to repeated endurance exercise training - Odden et al. 2026
• Heavy strength training effects on physiological determinants of endurance cyclist performance: a systematic review with meta-analysis - Llanos-Lagos et al. 2025
• Effects of Exercise Training on Mitochondrial and Capillary Growth in Human Skeletal Muscle: A Systematic Review and Meta-Regression - Mølmen et al. 2024
• Elite Aerobic Endurance Performance: Is It Really Related to Lactate Threshold Expressed Relative to Peak Oxygen Uptake? - Johansen et al. 2025
• Strength training improves performance and pedaling characteristics in elite cyclists - Rønnestad et al. 2014
• Five-Minute Power-Based Test to Predict Maximal Oxygen Consumption in Road Cycling - Sitko et al. 2022