When “just add more volume” stops working

A common pattern I see in competitive endurance athletes — cyclists, ultrarunners, triathletes — goes something like this. You’ve been training seriously for years. Your weekly hours keep creeping up. And at some point the returns start to flatten. Volume that used to drive meaningful performance gains now just costs you recovery capacity. You’re tired more often, sharper less often, and the PRs aren’t coming the way they used to.

When that happens, the default prescription tends to be “do more.” More hours. More base. Another long ride on Sunday. The reasoning feels intuitive: more time on the bike must equal more fitness. But a case study published in Trends in Sport Sciences in early 2026 offers a useful counterpoint — and it comes from one of the most extreme performances endurance sport has ever recorded.

In this article, we’ll walk through what the data says about how Christoph Strasser broke his own 24-hour cycling world record in 2021, why the mechanical power and energy cost findings are relevant to athletes training for far shorter events, and how the current peer-reviewed literature on intensity distribution and late-race fueling connects to everything the case study found. The aim isn’t to give you a single prescription. It’s to give you a clearer lens on what’s actually moving the needle — and what may not be.

The athlete, the event, and the record

Christoph Strasser, an Austrian professional ultra-cyclist, first set the 24-hour cycling world record in 2015. At that point, he was 1.86 m tall and weighed 78 kg. He completed his record attempt at Tempelhof Airport in Berlin, riding laps of 11.7 km in varying weather, including stops to change clothes and manage equipment issues (Forte et al., 2026).

He returned to the record attempt in 2021. This time the venue was Zeltweg Air Base in Austria, on a 7.58 km circuit at 670 m elevation. Weather was cloudy, temperature held steady at 15°C, and it rained intermittently for nine hours of the event. He completed 136 laps — 1,026.2 km — at a mean cycling speed of 42.8 km/h, becoming the first person to cover more than 1,000 km in 24 hours (Forte et al., 2026).

The 2026 case study by Forte and colleagues analyzed both record attempts — training volume leading in, mechanical power output during, energy cost, and estimated time of arrival variability across 6-hour splits. It’s the kind of rare, granular data set sports science almost never gets from elite performances, and the first thing that stands out is what didn’t change between the two records.

What changed in his training (and what didn’t)

In the 365 days before his first world record, Strasser logged 1,093 hours of training with a total training stress score (TSS) of 44,300. In the 365 days before the new world record, he logged 1,101 hours — eight hours more — with a TSS of 44,345 (Forte et al., 2026).

Put differently: his total time and total training load were, for practical purposes, the same. Volume was not the lever.

What the paper describes is a shift in the shape of that training. In the lead-up to the new world record, Strasser’s preparation was weighted toward more high-intensity interval training and less low-intensity basic training compared with his preparation for the first record (Forte et al., 2026).

This single case study, on its own, would be an interesting anecdote. What makes it worth sitting with is how closely it lines up with what the broader intensity-distribution literature has been pointing at for more than a decade. Stephen Seiler’s 2010 review of endurance training practices found that well-trained endurance athletes, across multiple sports, tended to converge on a training distribution that’s heavily weighted toward low-intensity work — but with a deliberate and sustained share of truly high-intensity work, and relatively little accumulated time in the moderate “threshold” zone in between (Seiler, 2010).

A 2014 randomized study by Stöggl and Sperlich extended that observation experimentally. In well-trained endurance athletes, a polarized training model — most time at low intensity, a smaller but deliberate share at high intensity — produced greater improvements in key performance variables than threshold-focused, HIIT-only, or high-volume-only models (Stöggl & Sperlich, 2014). The effects were not huge in absolute terms, and individual variation existed, but the pattern was consistent.

So what the Strasser case study seems to show, and what aligns with the broader literature, is this: at a certain point in an endurance athlete’s development, the distribution of intensity may matter more than the total hours. Adding more low-intensity volume, without adjusting how the hard work is placed, may not be the most productive lever.

What the mechanical power data across the race actually showed

The Forte et al. (2026) analysis broke each 24-hour record attempt into four 6-hour splits (0–6 h, 6–12 h, 12–18 h, 18–24 h), and compared several biomechanical variables between the two records within each split.

The variables analyzed included:

• Pd — power to overcome aerodynamic drag
• PRR — power to overcome rolling resistance
• PTOT — total mechanical power
• Energy cost (Ec) — energy expended per meter and per lap
• ETA — estimated time of arrival (pacing)

The finding: across all assessed variables, the new world record showed statistically significant improvements over the old record for every 6-hour split (p < 0.001). Effect sizes were large by Cohen’s d criteria — for example, Pd differences ranged from d = −2.05 to d = −5.03 across splits, and PRR from −2.26 to −6.06 (Forte et al., 2026).

Practically translated: Strasser was producing significantly more mechanical power, against significantly higher rolling resistance and drag, during every six-hour window of the new world record compared with the old one. This wasn’t a fast first quarter that faded. It was sustained higher output, end to end.

Between-groups variance analysis showed large eta-squared effects (η² > 0.140) for all the main variables within each world record, meaning the differences between splits within a single record were also meaningful — not a flat, steady-state effort but one with real dynamics over the 24 hours (Forte et al., 2026).

Why late-race energy cost rises — and what it means for fueling

The most practically useful finding in the paper, in my view, isn’t the raw power numbers. It’s what happened to energy cost over the course of the event.

In both the old and new world record attempts, energy cost per meter and per lap changed significantly across 6-hour splits (Forte et al., 2026). In plain language: the energy it took Strasser to move a meter was not constant over the 24 hours. The later it got, the more expensive movement became per unit of distance, even at lower average power.

Why does this matter for an athlete who isn’t chasing a world record? Because the underlying physiology shows up in shorter events too — it’s a matter of degree, not kind.

What drives rising energy cost during long events

Several factors, individually and in combination, can push per-meter energy demand up as an event progresses:

• Fatigue-related biomechanical changes. As the neuromuscular system fatigues, movement economy can drift. Posture changes. Pedaling smoothness degrades. Running gait alters.
• Aerodynamic drift. Fatigue-driven position changes can increase drag.
• Heat and dehydration. Gastrointestinal function — particularly gastric emptying — can slow meaningfully when athletes are dehydrated, hyperthermic, and working at high intensity (de Oliveira et al., 2014). Fuel that sat fine earlier can sit heavy later.
• Cumulative glycogen depletion. As carbohydrate availability drops, the body shifts toward a higher proportion of fat oxidation, which is less efficient per unit of oxygen consumed at moderate-to-high intensity (Burke et al., 2017).

The practical implication is significant: late-race fueling needs may increase, not decrease, as an event wears on — even when pace is dropping. A falling pace tempts athletes to eat less. The current literature on carbohydrate intake during endurance exercise generally suggests the opposite is often more appropriate when duration is long, within the limits of an individual’s trained gut capacity (Jeukendrup, 2014).

Asker Jeukendrup’s 2014 review on personalized carbohydrate intake during exercise described intake ranges that scale with duration: lower targets for events under 60 minutes, moderate targets for 1–2.5 hour events, and higher targets — up to 90 g/hour using multiple transportable carbohydrate types — for events running past 2.5 hours (Jeukendrup, 2014). Those are ceilings athletes work up to through training the gut, not starting points (Jeukendrup, 2017). You may not have a trained gut for high-end intake today, and the literature is clear that gut training is a weeks-to-months process, not a race-week adjustment.

Translating the case study to your own training

A 24-hour cycling world record is not a training template. It’s a data point — one elite athlete, in one event, under specific conditions, with a physiology and training history that doesn’t generalize to the average competitive endurance athlete.

That said, several of the principles the data illustrates have broader support in the peer-reviewed literature, and they’re worth examining in your own training if you recognize the plateau pattern described at the top of this article.

1. Audit your current intensity distribution

Start by looking at a typical training week in hours, not sessions. How much time do you actually spend below your first ventilatory threshold (roughly Zone 2 or below, depending on your zone model)? How much above your second ventilatory threshold (truly hard work)? And how much in between?

The polarized training literature suggests that well-trained endurance athletes often converge on something like 75–85% low intensity, 10–20% high intensity, and a relatively small share at moderate/threshold intensity (Seiler, 2010; Stöggl & Sperlich, 2014). These numbers are illustrative, not prescriptive — individual responses vary, and periodization matters. But if you look at your week and see a lot of moderate-intensity time that isn’t quite easy and isn’t quite hard, that’s often the first place to examine.

2. Make your hard sessions genuinely hard

A common failure mode I see in athletes who think they’re training polarized is that their “hard” sessions aren’t actually hard — they’re moderate sessions mislabeled. If you aren’t regularly hitting real HIIT work (short intervals at high fractional VO₂max, longer intervals sustained at or above your critical power / threshold pace), adding more easy volume won’t fix what’s missing (Stöggl & Sperlich, 2014).

3. Scale fueling to duration, not just intensity

Your per-hour carbohydrate intake target should be set against the event you’re training for, the intensity you’ll sustain, and the gut capacity you’ve actually trained. Generic advice like “60 grams of carbs per hour” is a reasonable starting point for middle-distance efforts, but scaling in either direction is often appropriate — and the scaling question is worth asking session by session, not once at the start of a block (Jeukendrup, 2014; Jeukendrup, 2017).

4. Let recovery keep up with intensity

More high-intensity work means more recovery demand. If sleep, nutrition timing, and spacing between hard sessions aren’t supporting the load, shifting your distribution toward harder work won’t help — it will accumulate fatigue. The case study athlete logged the same annual hours between records, but the assumption underlying that is that he also recovered well enough to absorb a harder weekly structure. That’s not guaranteed to transfer to an athlete whose life stress, sleep, or fueling aren’t already in order.

What this case study does not say

Being honest about what the data does and doesn’t support matters — especially when an athlete is considering meaningful training changes based on it.

A few things worth naming:

• One athlete is not a population. This is an n = 1 case study, and Christoph Strasser’s physiology, training history, and contextual factors don’t generalize cleanly to other athletes. Case studies generate hypotheses; they don’t confirm them.
• Zone 2 is not “dead.” Strasser still logged substantial low-intensity volume. The question is distribution, not elimination. Most of the polarized training evidence base still points to the majority of weekly training time being at low intensity, not the minority.
• The causal direction isn’t proven. The improved performance in the new record coincided with a shift toward more HIIT and less base volume. It could be that the shift drove the performance. It could also be that six additional years of cumulative development, equipment changes, course differences, weather, pacing strategy, or any number of other variables contributed (Forte et al., 2026).
• Your sport, distance, and stage of development matter. A 24-hour cyclist’s optimal distribution isn’t the same as a marathoner’s, a 70.3 triathlete’s, or a masters-age gravel racer with two hours of training time per day. Principles transfer; specifics don’t.

The reasonable takeaway isn’t “switch to HIIT.” It’s “examine whether your current distribution is still serving you, and whether your fueling and recovery are structured to absorb whatever shift you make.”

Frequently asked questions

Work with Kyla and the Nutritional Revolution team

If you’re navigating a performance plateau, a complex race calendar, or a fueling strategy that isn’t holding up at the pointy end of your events, we help competitive endurance athletes move from generic plans to programming built around their physiology, their event demands, and the current peer-reviewed evidence.

Our work covers everything from sweat testing and lab work review to periodized nutrition, race-week protocols, and ongoing coaching through training cycles. We consult with cyclists, ultrarunners, triathletes, and multi-sport athletes, and we’re willing to update our approach as the literature evolves — because that’s how evidence-based practice is supposed to work.

References

About Kyla Channell, MS

Kyla Channell, MS, is a sports nutritionist specializing in high-performing endurance athletes. She holds a Master of Science in Nutrition and Human Performance (graduated with high distinction), an International Olympic Committee Sports Nutrition Diploma, and a Bachelor of Science in Clinical Dietetics from UC Davis. At Nutritional Revolution, Kyla consults with competitive endurance athletes — cyclists, ultrarunners, triathletes — designing customized nutrition programming grounded in current peer-reviewed sports science. Her practice integrates sweat testing, laboratory work review, and periodized fueling strategies so athletes can perform at their highest level.