Right fuel, Right Time, Wrong Protocol? Lessons From a Recent Study

Feb 02, 2024

With the athlete I coach, I promote what I call the “Right Fuel, Right Time” approach to nutrition for endurance training, as discussed in blogs and on our courses. By "Right Fuel, Right Time," I mean advocating for the timely management and adaptation of nutrition, particularly carbohydrate intake, according to training demands. These objectives may aim to maximize acute performance within the session or facilitate high rates of fat oxidation.

In the literature, we come across the term "Periodised carbohydrate intake," which is an approach that follows a very similar principle and is seeing increasing research interest (1, 3).

The rationale for this approach is that adequate carbohydrate should be consumed to support the quality of training sessions. However, we should avoid over-consuming carbohydrates on easier, less demanding days, as this may blunt the signals that lead to positive adaptive responses (2). Carbohydrates and fats are the body’s primary fuels. While fat stores are effectively unlimited in the context of exercise, carbohydrate reserves, stored as glycogen in muscles and in the liver, can be depleted by long-duration or intense exercise (4–6). Therefore, training our body to more effectively utilize fat to support prolonged exercise during training and competition is helpful, as it reduces glycogen depletion and staves off fatigue.

Recently, a group of authors based primarily in Spain (11), including Iñigo San-Millan (coach of Tadej Pogačar), published a study that assessed the effectiveness of periodised carbohydrate intake during a five-week cycling training program. The study featured a cohort of pretty well-trained cyclists, with a mean V̇O2max of ~71 mL.kg.min-1, which certainly grabbed my attention.

Furthermore, the study found that periodizing carbohydrate intake around training was not beneficial, which grabbed our attention further! However, upon reading the study, I noted a few points to consider when evaluating its conclusions.

Let’s break the study down here…

What did the study find?

In the study, 17 cyclists—pretty well-trained—were randomly allocated to either a periodised carbohydrate intervention or high carbohydrate control intervention for five weeks. The two groups completed the same training program for five weeks, but the periodised carbohydrate group performed 13 of their training sessions with lowered carbohydrate availability. The high carbohydrate control group performed all training sessions with high carbohydrate availability.

 Before and after the intervention period, the cyclists undertook a battery of tests to assess their performance. These included a maximal lactate steady-state (MLSS) test, involving finding the highest power output at which blood lactate concentrations can stabilize during 30 min of exercise. They also did a time-to-exhaustion test—cycling at a fixed intensity for as long as possible—and measured fat and carbohydrate oxidation rates during cycling.

The main outcomes were that power output at MLSS improved similarly in both groups (~3-5%), time-to-exhaustion was not statistically improved in either group, and substrate oxidation rates were unchanged. So, in short, periodizing carbohydrate intake around training didn’t seem to have an impact on training outcomes—at least those measured—in this study.

As always, the devil is in the detail. Like I said, I’m not writing periodised carbohydrate intake off just yet. As with any study, the outcomes are highly specific to the study protocol. While the study was good, and I don’t write this to be overly critical, I have some thoughts on the protocol and intervention that caution against over-interpreting the outcomes. While there are also some nuances with the statistics used for the time-to-exhaustion trial, I’m just going to focus on some of the simpler observations here. Let’s go.

First, as is often the case, the sample size in this study was small—with only 17 participants overall, nine in the periodised carbohydrate group, and eight in the high carbohydrate group. I know how hard these studies are to complete; in fact, I’ve been involved in a training intervention study with these exact participant numbers (7). The reality is that this is a very small number in a study with parallel-groups (which means participants don’t undertake both interventions), as different athletes have different responsiveness to training even under normal circumstances. If, for example, periodising carbohydrate intake around training does enhance training outcomes, but you, by random chance, have two or three participants in the periodised carbohydrate intake group who are very weak responders to training (we all know those athletes who see very slow improvements in performance with training, compared to those who see enormous bumps in only a few weeks), you’ll obscure the ‘true’ effect of the nutrition intervention. This makes interpreting the results of training studies with small numbers challenging, and why—acknowledging that this is very difficult to do in practice—we need bigger numbers for studies of responses to training interventions.

My second point to note is that, even in the periodised carbohydrate group, daily carbohydrate intake was still pretty high at nearly ~6 grams per kilogram of body mass, per day. For a 70-kg athlete, that’s around 400 grams of carbohydrate per day. This was by design—so this is not a criticism of the researchers, but an acknowledgment of the intervention protocol. To create conditions of low-ish carbohydrate availability for the 13 ‘manipulated’ sessions, this meant the periodised carbohydrate intake group consumed most of their carbohydrates following their training sessions. That would have resulted in significant glycogen replenishment.

These participants then refrained from carbohydrate intake at breakfast prior to the low carbohydrate sessions, which probably meant they did these sessions with only slightly depleted liver glycogen (as carbohydrate is released from the liver to maintain blood glucose concentrations overnight). Therefore, to my eye, these participants didn’t do much training without fully topped-up muscle glycogen stores, and so may not have given their body the incentive to make adaptations to fat metabolism that we look for with the “Right Fuel, Right Time” approach. Personally, I’d lower the overall carbohydrate intake further in the periodised carbohydrate intake and increase the fat intake (which was pretty similar between groups) this would have ensured that some of the training sessions were performed with properly lowered muscle glycogen stores. This drives up fat oxidation (8).

Thirdly, adaptations to fat metabolism were assessed during the exercise capacity test at the pre-intervention MLSS power output. This was an interesting choice, as fat oxidation is pretty minimal at intensities that high (9). Rates of fat oxidation are high at low-to-moderate intensities, and then decline as carbohydrates become the dominant fuel source at higher intensities (10). Fat oxidation rates typically peak at or close to the first lactate or ventilatory threshold, which is sometimes referred to as the ‘aerobic threshold’ or the top of ‘Zone 2’. As MLSS is a marker of the second threshold—similar to the ‘critical power,’ ‘lactate turnpoint,’ or ‘anaerobic threshold’—we’d expect fat oxidation rates to be low in this test. For me, it would have been more insightful to look at how fat oxidation rates changed during exercise at lower intensities.


Like I said, I don’t want to trash this study—it’s a good one—I just think the results are not really an investigation of the way I see this “Right Fuel, Right Time” or periodised carbohydrate intake approach best implemented, and so I will interpret it in that way.



  1. Impey SG, Hearris MA, Hammond KM, Bartlett JD, Louis J, Close GL, Morton JP. Fuel for the work required: A theoretical framework for carbohydrate periodization and the glycogen threshold hypothesis. Sports Medicine 48: 1031–1048, 2018. doi: 10.1007/s40279-018-0867-7.
  2. Hawley JA, Lundby C, Cotter JD, Burke LM. Maximizing cellular adaptation to endurance exercise in skeletal muscle. Cell Metab 27: 962–976, 2018. doi: 10.1016/j.cmet.2018.04.014.
  3. Marquet LA, Hausswirth C, Molle O, Hawley JA, Burke LM, Tiollier E, Brisswalter J. Periodization of carbohydrate intake: Short-term effect on performance. Nutrients 8: 755, 2016. doi: 10.3390/nu8120755.
  4. Maunder E, Kilding AE, Plews DJ. Substrate metabolism during Ironman Triathlon: Different horses on the same courses. Sports Medicine 48: 2219–2226, 2018. doi: 10.1007/s40279-018-0938-9.
  5. Bergström J, Hermansen L, Hultman E, Saltin B. Diet, muscle glycogen and physical performance. Acta Physiol Scand 71: 140–150, 1967.
  6. Areta JL, Hopkins WG. Skeletal muscle glycogen content at rest and during endurance exercise in humans: A meta-analysis. Sports Medicine 48: 2091–2102, 2018.
  7. Maunder E, Plews DJ, Wallis GA, Brick MJ, Leigh WB, Chang WL, Watkins CM, Kilding AE. Temperate performance and metabolic adaptations following endurance training performed under environmental heat stress. Physiol Rep 9: e14849, 2021. doi: 10.14814/phy2.14849.
  8. Rothschild JA, Kilding AE, Stewart T, Plews DJ. Factors influencing substrate oxidation during submaximal cycling: A modelling analysis. Sports Medicine 52: 2775–2795, 2022. doi: 10.1007/s40279-022-01727-7.
  9. Maunder E, Plews DJ, Kilding AE. Contextualising maximal fat oxidation during exercise: Determinants and normative values. Front Physiol 9: 1–13, 2018. doi: 10.3389/fphys.2018.00599.
  10. van Loon LJC, Greenhaff PL, Constantin-Teodosiu D, Saris WHM, Wagenmakers AJM. The effects of increasing exercise intensity on muscle fuel utilisation in humans. Journal of Physiology 536: 295–304, 2001. doi: 10.1111/j.1469-7793.2001.00295.x.
  11. Prieto-Bellver G, Diaz-Lara J, Bishop DJ, Fernández-Sáez J, Abián-Vicén J, San-Millan I, & Santos-Concejero J. A Five-Week Periodized Carbohydrate Diet Does Not Improve Maximal Lactate Steady-State Exercise Capacity and Substrate Oxidation in Well-Trained Cyclists compared to a High-Carbohydrate Diet. Nutrients, 16(2), 318 2024 https://doi.org/10.3390/nu16020318



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