This weekend is the Western States 100. If you are not familiar, this is the Super Bowl of ultramarathons in the United States. It is the race most ultra runners dream about. I will be watching from afar, watching youtube, and refreshing the live tracker more than I probably should. So this week felt like the right time to dig into a study that just analyzed 18 years of Western States data. Not a training intervention. Not a "do this and run faster" study. Just a detailed look at how thousands of finishers actually paced one of the hardest 100-mile races in the world.
ARTICLE BELOW:
The Research
A 2025 study published in Nature pulled official results and checkpoint splits for every Western States finisher from 2006 to 2023. That is 3,837 runners across 18 race years, with elevation data and 17 checkpoint times for each one. Researchers calculated how each runner's pace changed at every checkpoint relative to their overall race pace, then grouped runners by gender, age, and performance level to see how pacing patterns differed.
I want to be upfront about what this study is and is not. This is purely observational. There was no intervention, no controlled variable, no if-then conclusion to draw. The researchers collected data and described what happened. That makes this an educational piece, not a prescriptive one. We can learn from the patterns without treating them as proof of what works best.
What They Found
The research suggests these are the key takeaways
🟡 Moderate evidence: large, well-analyzed dataset spanning 18 years, but purely observational with no controlled variables. These are patterns worth understanding, not causal conclusions about optimal strategy.
Every single performance group showed positive pacing. Nobody negative split this race. Everybody slowed down from where they started. The question was never whether runners would slow down. It was how much.
The front of the pack paced the most consistently. These are largely professional and highly experienced ultra runners who know the course and have raced 100 miles before. They got out fast and stayed fast longer than anyone else.
The back of the pack also paced consistently, just at a slower overall speed. They showed less variability between checkpoints than the middle of the field.
The middle of the pack showed the most erratic pacing and the largest slowdown of any group. They faded the hardest.
Men showed significantly more pacing variability than women across almost every age group. Women paced more consistently throughout the race.
What This Means For Your Training
Here is where I want to be careful, because the study does not answer the question everyone wants answered: is this optimal? Is it actually a mistake for middle-of-the-pack runners to go out fast and fade, or is that simply what happens at this distance regardless of strategy? The data shows what happened. It does not prove what should have happened. Some people will argue the middle-of-pack fade is a pacing error. Others will argue it might not matter much over 100 miles. That was not what this study was built to settle, and I am not going to pretend it was.
What I will say is this: a lot of the men in the middle of the pack going out fast looks like ego more than execution. Getting swept up in the start line energy, running with people who are objectively faster than your training supports, and paying for it in the back half. Putting the ego aside and running your own race, especially in a hundred-mile event, is not a new idea. But seeing it show up this clearly in 18 years of data makes the point land differently.
A friend of mine, also an ultra runner, said something to me once that has stuck. In most races we talk about your fastest splits. What are your best miles. In an ultramarathon, what matters more is your slowest mile. Not because the fast miles do not count, but because the size of the gap between your fastest and slowest mile tells you more about how well you managed the day than any single split does.
My Own Numbers
I have real data on this, not just a rough memory. At my first Ice Age 50 miler, my fastest mile was 7:40. My slowest was 26:33. That is a delta of nearly 19 minutes between my best and worst mile of the day.
To be fair to myself, that 26:33 mile included a long, rough aid station stop. I never paused my watch at either race, so every stop, every fumble with a gel wrapper, every moment standing still is baked into these numbers. But that is also the point. Race time is race time. If you are standing still for three minutes at mile 38 because you are falling apart, that is still part of your day and part of your pacing story.
The next year, same race, my fastest mile was 8:41 and my slowest was 11:43. A delta of just over 3 minutes. My overall finish time dropped by over 2 hours and my place went from 81st out of 196 runners in my first year to 16th out of 240 runners in my second year.
But the time drop is not actually the part I find most interesting. It is the shape of the data. In year one, starting around mile 21, my splits become genuinely erratic, climbing into the double-digit minutes, swinging wildly mile to mile. In year two, from roughly the same point in the race, my splits stay locked in a tight 9 to 11 minute band almost the entire rest of the way, depending mainly on whether I stopped at an aid station or not.
That is the Western States data showing up in my own training log. Year one, I was the middle-of-the-pack runner this study describes, fast and excited early, then falling apart and never recovering. Year two, I paced more like the front and back of the pack in this study, consistent, controlled, no wild swings.
Same race. Same course. Same person. Completely different execution.
🏆 How To Apply It
Track your splits in training and in races, but stop only looking at your fastest mile. Calculate the delta between your fastest and slowest mile. That number tells you more about your pacing discipline than your fastest split ever will.
Set a realistic expectation for where you will likely finish in the field before the race starts. If you know you are a middle-of-the-pack runner by training and experience, plan your early pace accordingly rather than getting pulled along by faster runners around you at the start.
Treat the first quarter of a long race as the place where pacing mistakes get made, not the place where the race gets won. The front-of-pack and back-of-pack runners in this data paced most consistently. The middle got into trouble early and never recovered.
If you are racing an ultra or a marathon this year, write down your delta after the race. Then compare it to your next one. My own 19-minute to 3-minute improvement is the clearest single number I have from my own racing career, and it came directly from paying attention to this.
This weekend, if you watch any of the Western States coverage, watch the leaders and watch the pacing patterns. You will see exactly what this data describes playing out in real time.
Hit reply and tell me: have you ever gone out too fast and paid for it late in a race?
-Keep running happy, healthy, and strong
Spencer
Next week I want to dig into my roots with some Physical Therapy/injury research
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