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Marathon Madness
Goals and training approaches - Getting the ball rolling
We talked a little about my last attempt at the marathon distance in this newsletter. If you haven’t read it, please check it out first.
I’ll start by saying marathons are not my bag! I prefer staring death in the face for 5000m much more than the slow descent into madness that the marathon distance entails. That said, I don't back down from a challenge and now and then I forget how crazy they are.
These are my marathons to date:
Year | Age | Race | Result |
2010 | 40 | Frankfurt | 3:15 |
2015 | 44 | Stockholm | 3:13 |
2015 | 45 | Amsterdam | 3:11 |
2021 | 51 | Uppsala | 2:59 |
I did the New York Marathon in 2018 too, but I put that one down to tourist sight-seeing and a lot of portaloo visits (3:40).
On first look at the table, the times look okay. All are BQ times but as we discussed last week BQ times are well off genetic potential. In hindsight, I had no real idea how to train for them. I trained my general run fitness and hoped for the best.
For a bit of context between 2010 and 2018 I was doing triathlons + swimruns and from 2019 to now only swimruns. Early in that period I discovered the FIRST (Furman Institute of Running and Scientific Training) program which had been popularized in the book Run Less, Run Faster. The approach appealed to me as I just didn’t have time for high running volume whilst balancing swim, run, bike, a full-time job, and three kids. FIRST is quite different from traditional marathon training philosophies, focusing on high-intensity running and incorporating cross-training instead of additional easy runs.
Key Aspects of the FIRST Approach
Three Key Runs Per Week:
Track (interval) workouts: These are designed to improve speed and VO2 max, with faster-than-race-pace intervals.
Tempo runs: These are at or just below threshold pace, meant to boost lactate threshold and running efficiency at higher intensities.
Long runs: These are done at a pace faster than typical long-run paces in traditional programs, often prescribed to be at or close to marathon goal pace.
Cross-Training:
On non-running days, FIRST emphasizes cross-training activities such as cycling, swimming (that was convenient). These are intended to replace the easy or recovery runs found in other plans, and they aim to build aerobic fitness and strength without the added impact of running.
Focus on Quality Over Quantity:
Rather than piling on miles, the FIRST plan seeks to make each run purposeful, emphasizing speed, threshold, and race-specific pace to maximize time efficiency.
It was a fit for me at the time but I acknowledge it has its shortcomings.
One major critique of the FIRST program is that its reduced mileage does not sufficiently develop the aerobic base required for optimal marathon performance.
The reduced mileage doesn’t adequately prepare you for the late-stage fatigue of a marathon, where muscular endurance plays a critical role.
Since all three key runs each week are relatively intense (intervals, tempo, and long runs at a faster pace), the intensity is mentally and physically draining.
While cross-training provides cardiovascular and muscular benefits, it’s not a perfect substitute for the specific adaptations that come from running. The specificity of running (muscle-fiber recruitment, foot-strike mechanics, etc.) is difficult to replicate with cross-training.
My hypothesis on upper limits for this approach
Sub-3:30 to around 2:50 Marathon - I believe the FIRST approach can be effective for recreational runners aiming for a sub-3:30 to around 2:50 marathon. This time range often represents a point where runners benefit from focusing on quality over quantity, which aligns well with the FIRST philosophy. The program's combination of high-intensity runs and cross-training can help runners improve their speed and aerobic capacity without needing to log massive volume.
Sub-2:50 - Once a runner is targeting faster times, the limitations of the FIRST approach become more apparent. Runners in this range often require high-volume training to build the endurance and efficiency needed to sustain faster paces over the marathon distance. At these levels, I believe that more specific marathon-paced runs, frequent aerobic work, and a focus on endurance are critical. Without those components, it becomes challenging to reach your highest potential for a marathon performance.
In short, the FIRST approach is excellent for many recreational runners, but at higher levels, a traditional higher-mileage, more marathon-specific program becomes necessary to maximize performance.
If I am going to go faster I will need a new approach! But let’s first discuss the estimation of race potential.
Estimating Potential
If I put my 5k, 10k, and half marathon times into a race calculator you would have got better predictions than the marathon times I ran. This is common for the majority of recreational athletes. So let’s have a look at those prediction models.
We should start with the father of all models, the Riegel Formula. The Riegel Formula is a widely used method for predicting race times over different distances based on a known performance at another distance. Developed by Peter Riegel, a research engineer and marathoner, the formula takes into account how running performance decreases as distance increases, largely due to factors like fatigue and energy system demands.
The Riegel Formula T_{2}=T_{1}×(D_{2}÷D_{1})^{1.06}
Where:
T₁ = Time for the known race distance (in seconds or minutes),
D₁ = Distance of the known race,
T₂ = Predicted time for the new race distance,
D₂ = Distance of the new race,
The exponent 1.06 represents the rate at which performance declines as distance increases. This value was derived by Riegel based on empirical data from race results.
How the Formula Works
The Riegel formula predicts that performance will decrease at a rate proportional to the distance raised to the power of 1.06. The exponent 1.06 captures the idea that as race distance increases, it becomes harder to maintain the same pace, primarily due to muscle fatigue and energy system changes.
This formula assumes that an athlete is equally well-prepared for both the known and predicted distances, and that the physiological factors affecting performance (like endurance and energy system efficiency) apply consistently across the distances.
Why the Exponent 1.06?
The value of 1.06 was derived empirically by Riegel after analyzing race performances. The value indicates that for every doubling of distance, a runner's pace will slow down by around 6%. This exponent allows for adjustments in performance as distances grow longer, reflecting the increasing demands on the aerobic system and the impact of fatigue.
Limitations of the Riegel Formula
Training specificity: The formula assumes that the athlete is equally well-prepared for both shorter and longer distances. This begs the question of what is “equal preparation” across the demands of different race distances. Evidently, my training approach has not provided equal preparation for the marathon distance.
Fatigue and nutrition: The formula doesn't account for race-specific factors like heat, glycogen depletion, hydration, or fueling, which has a larger impact on performance in long races like the marathon. I discussed in the Running with Power newsletter that two of the key factors for me going sub-3 were 1) nailing my fueling plan and 2) the heat was not an issue (2 degrees Celsius at the start).
Exponent variability: The exponent 1.06 is an average; it may not apply perfectly to every individual, as some athletes experience more or less performance decline over longer distances.
Applicability: We should remember that Riegel developed exponent 1.06 as an average in the 80s, this is when the idea that 4 hour marathons are something to boast about was only just emerging. Marathon results in the early 1980s had a faster average time and less statistical distribution compared to today.
The Riegel formula is modeled on high-level performances. Recreational runners take at least an hour more to run their marathons compared with elite runners, so the margin for error is greater. If you think about it, when an elite or sub-elite runner bonks, their performance declines in absolute terms is smaller than when the rec runner bonks.
Whereas the Riegel formula is often cited as being too aggressive, you would see the opposite trend in the true elite 2020s fields due to super-shoes, scientific training methods, and improved fueling strategies.
In summary, the Riegel Formula is a useful tool and still widely used for predicting performance across different distances based on a known race time. It provides a generalized framework for understanding how pacing slows as race distance increases, but its accuracy depends on consistent training and preparation for the specific demands of each distance.
If you plug in your numbers you’ll see they provide challenging predictions. Rounding my 10km time up to 38 minutes I get a predicted marathon time of 2 hours 50 minutes. I checked another prediction model; the Daniels VDOT model and I got 2 hour 55 (which would be a factor of 1.0624) - so a similar ballpark.
Equal Preparation
The key to these predictions is the caveat that you are trained for the marathon. So what does that really mean?
Unless you are running 150+ km a week you’re not actually training for the marathon. You’re just getting fit and hoping it goes well.
So let’s say my “hope” factor was 5 to 10% By adding this to the predicted time to account for the fact you haven’t specifically trained for the unique demands of the marathon. So without high-volume marathon training, a runner who can run a 10K in 38 minutes might then reasonably expect to run a marathon in the range of 2:58 to 3:08, though this will depend on their existing aerobic base, pacing ability, and fueling strategies.
Looks like my “hope” went a long way coming in at the faster end of that span. But next time I don’t want to rely on race day magic, digging around the internet I found this:
We can see that up to elite times <2:30 the models have similar predictions - probably where most of Riegels data was taken. The key difference in the Vickers-Vertosick model is that it takes one or two race times and combines that with your typical weekly training mileage.
Putting in my 5k time 17:32 and 10K time 37:28 it suggests to get down to the VDOT predicted 2:55 I’d need 87 miles (140km) and the Reigel predicted 2:50 I’d need 100+ mile weeks (160km).
Looks like the model agrees with Max! Weekly volume is key to maximizing your potential in specific marathon programs.
One question I have is the relationship between distance and duration. A world-class marathoner would have an easy aerobic pace of maybe 4:00/km. That makes a difference when converting distance into training hours. For simplicity, I have used a proxy average pace.
Day | Distance (km) | Duration at 4:00/km (h:m) | Duration at 5:00/km (h:m) | Duration at 6:00/km (h:m) |
Monday | 10 | 0:40 | 0:50 | 1:00 |
Tuesday | 20 | 1:20 | 1:40 | 2:00 |
Wednesday | 16 | 1:04 | 1:20 | 1:36 |
Thursday | 12 | 0:48 | 1:00 | 1:12 |
Friday | 22 | 1:28 | 1:50 | 2:12 |
Saturday | 15 | 1:00 | 1:15 | 1:30 |
Sunday | 35 | 2:20 | 2:55 | 3:30 |
Total | 130 | 8:40 | 10:50 | 13:00 |
We can see that for a 130km week the elite runner is training 8:40 hours. An interesting reference point is that the Stryd Steve Palladino Marathon Level 4 Plan (which is power and duration-based) tops out at 8:30 hours. I think there is a physiological (and practical) limit on duration and therefore the Vickers-Vertosick model should have a ‘red zone’ basically to say that a 38 minute 10km isn’t a fast enough point on the power curve to sustain a 2:50 marathon rather than allowing the distance component to stretch to 160 km to model it.
Another caveat is that a specific goal like a BQ or qualification to the Age Group World Championships might not need you to maximize your marathon potential. Alternatively, maybe you will get more from your run training by focusing on shorter distances and really committing to those training modalities rather than “pretend” marathon training. We each have a power/pace curve. Each distance is supported by and built on paces above and below. This exists in a dynamic relationship. All systems need to be trained to raise the curve. Getting fit and fast at shorter distances whilst adding a bit of hope when moving up distance could be an approach that takes you further on limited training time.
If you are the kind of person who is motivated by aspirational target marathon times, below are the qualifying times for the 2025 AbbottWMM MTT Age Group Marathon World Championships.
With the Valencia Marathon on the cards for 2025, I aim to crack the marathon code. A one age-group down goal of 2:48 gives a target pace of 04:00/km. That is spicy! So holding my 2021 prediction of 2:55 (4:09/km) might be a more realistic target. To do this VDOT Calc suggests I’d need these equivalent results at shorter distances:
Distance | Time | Pace |
1500m | 4:52 | 3:15/km |
3000m | 10:34 | 3:31/km |
5000m | 18:16 | 3:39/km |
10000m | 37:53 | 3:47/km |
Half Marathon | 1:23:50 | 3:58/km |
In the coming months, I’d like to dig into the training methods of Daniels, Hanson-Brooks, Lydiard, Magness, Canova, Frankel, and other leading coaches to find common ground and the differences.
Another component is that I plan to make full use of the Stryd training platform to monitor training history and set effective power-based training zones. I’d like to assess whether the available plans by coach Steve Palladino are a good fit.
It should be interesting. I’ll keep you posted.
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