Introduction
The backyard ultra (BYU) concept is a relatively new race format in the ultra-running world, with the first event taking place in 2011. Since then, the volume of BYU races around the world has slowly increased, although they typically maintain a down-to-earth, non-commercialised atmosphere.
The concept is simple. Each runner has an hour to complete a 4.167 mile lap (known as a ‘yard’ in BYU parlance). This target is very attainable for the vast majority of runners. Runners are then required to repeat the same lap on the hour every hour until only one runner remains. Run. Rest. Repeat. The last person standing is the race’s winner, with all other runners marked as Did Not Finish.
My own experiences of running BYUs have reinforced to me just how important it is to have a meaningful pacing strategy and approach to these events. Finding the sweet spot between controlling one’s pace to conserve energy versus maximising rest time between laps is the key. Have I found it yet? To be honest, I don’t think I have. I still feel that I am completing laps too quickly. Other competitors who are running slower than me are often lasting longer into the race.
I have seen competitors adopt a variety of strategies. Runners used to shorter formats typically run their laps faster than the majority. Some runners like to insert a fast lap every few hours to gain a lengthier than normal rest time. Others who struggle with running slower than they are used to will run fast over the first 3 miles and then walk the remainder. The strategy can also be influenced by the hilliness of the course.
This has led me to wonder if analysing results from previous BYUs can unlock insights into the optimal approach to BYU success, and what the factors are that either boost or limit performance.
Other strategic aspects such as mental approach and refuelling are also key but go beyond the reach of this investigation.
Analysis Method
Firstly, it has been necessary to collate lap-by-lap timings per runner from as many BYUs as possible. Individual lap times are recorded at some but not all BYU events. The most comprehensive source of these races is Webscorer. This data in most cases also includes the runner’s age and gender.
The data has been collated from 25 separate BYUs and 1167 runners with results ranging from 1 lap to 47 laps. The dataset will be added to as further race results come on stream. If anyone reading this has further data available, please let me know at ian@onemoremile.run.
Some races record lap times exclusive of rest time between laps, for other races the lap time is inclusive of rest time between the previous lap and the latest lap. This has necessitated the removal of rest times for some races, so that the data is standardised.
Alongside the lap times, the elevation of the course has also been included in the data.
Data analysis has then been performed on the superset of BYU data, with the results and insights described below. The following factors have been assessed:
-
Lap times
-
Pacing variability
-
Course elevation
-
Age
-
Gender
What is the Optimal Lap Pace?
Does the pace of a runner have an impact on their overall performance in a BYU?
Let’s look at the average lap time per runner plotted against the number of laps that runner completed, in the form of a heatmap.
Insights
There is no single ‘perfect’ lap time, but trends emerge.
Most runners settle on a pace between 48-52 minutes per lap.
The 46-52 minutes per lap band is a successful strategy for runners completing 30+ laps.
Runners achieving 40+ laps operate in the 47-49 minutes per lap band.
Faster runners (<45 minutes/lap) encounter early exhaustion and rarely reach high lap counts.
Slower runners (>55 minutes/lap) have reduced recovery time and struggle to sustain endurance over many laps.
Outliers exist but they are rare.
These insights confirm that managing effort and maintaining a balanced pace is crucial for maximizing laps in a backyard ultra.
Does Consistent Pacing Aid Performance?
Which results in better performance, sticking to a consistent pace or significant variations in pace from lap to lap?
In the visualisations below, the timing of a runner’s last lap has been removed, as a runner may choose to either deliberately speed up or take their time if they know it’s their last lap. Otherwise, this would introduce spurious variability.
Firstly, here is the individual variability in lap time based on the number of laps that a runner completed.
Below we can see the aggregated variability in lap time based on the number of laps that runners completed.
We can also see the level of lap time variability breaking down runners into 4 variability quartiles.
Insights
There is no absolute trend that runners with lower lap time variability complete significantly more laps.
Some high-lap runners have low lap time variability, but others have moderate variability.
Equally, some low-lap runners have low lap time variability too.
Runners with extreme variability (high fluctuations) tend to complete fewer laps, suggesting pacing inconsistency might be a factor.
This supports the conclusion that slight variation in lap times (< 4 minutes) is fine, but extreme fluctuations may hurt endurance.
Does Course Elevation Impact the Optimal Approach?
Elevation/climb data is not available for all the BYUs included in this exercise, so we are dealing with a smaller data sample (1091 runners) than elsewhere in this document.
Let’s start by looking at whether the lap times are impacted by the elevation.
Now, we can see the relationship between elevation and the number of laps completed. The sample size is reflected in the size of the data point marker on the chart.
This visualisation overlaps elevation against both average lap time and laps completed, to determine the best pacing strategy for maximum distance on hillier courses.
Finally, this heatmap shows the impact of elevation on lap time variability.
Insights
Lap Times:
Unsurprisingly, there is a clear relationship demonstrating that lap time increases as elevation increases.
There is an obvious outlier at 220 feet, where the average lap time is significantly higher than the trend would predict. This data relates to the Lagunitas BYU held in Bolivia, the likely explanation for this spike being that the race is held at very high altitude (between 1000 – 11000 feet).
We determined earlier that the 46-52 minutes per lap band is a successful strategy for runners maximising their lap count. For the hillier courses, a more effective approach is to churn out laps in the 50-54 minutes band.
Distance:
Somewhat surprisingly, the hilliness of the course has little impact on the distances covered by the competitors. The relationship between elevation and endurance is not strictly linear.
A possible explanation for this is that the more experienced or better trained runners are more likely to take on the tougher courses.
Note the outlier at 108 feet of climb, where runners completed 31 laps on average. This relates to the UK BYU National Championships which would have had a much higher standard of runner than the average BYU event.
Pacing Consistency:
Most runners maintain a moderate level of pacing consistency regardless of the elevation.
Inconsistent pacing is more likely to feature at the lower elevations. The comparative ease of these courses provides more leeway and flexibility for varied pacing strategies.
Higher elevations involve longer lap times, leading to less room for manoeuvre with pacing.
Does Age Have an Impact on Performance?
What happens if we now factor age into the equation? Does age matter in a BYU?
Firstly, let’s breakdown the endurance capabilities by age.
Here we can see the impact of age on pacing consistency (excluding each runner’s last lap due to its unpredictable nature as mentioned above). Note that the chart has been ‘smoothed’ with an age window of 5 (+/- 2 years) to indicate the trends more clearly.
The correlation between age and speed/lap times looks like this (smoothed in the same way as the previous chart):
Insights
Distance:
The highest distances are covered by runners in the 30-50 age bracket. This aligns with the typical peak endurance age range.
There is a clear reduction in endurance and stamina capabilities in the under 20s and over 60s.
Pacing Consistency:
Age impacts pacing discipline, with the most consistent pacing occurring in middle-aged runners.
The lowest lap time variability is seen in runners aged in their 40s and 50s.
Younger runners (15–25) generally show more erratic pacing. Inconsistent pacing may be a key reason why younger runners underperform in long-duration events. Younger runners might benefit from pacing education and strategy coaching. The comparatively small sample size of 137 runners aged 25 and under could be a factor here.
Variability rises slightly in older age groups (60+), though this may be skewed by a small sample size due to not many 60+ runners participating in BYUs.
Lap Times:
Runners in their 30s and 40s are typically the most efficient pacers.
Younger runners (15–25) tend to have slightly higher average lap times, possibly due to inconsistent pacing or inexperience. Youth alone doesn't equal better pacing; experience plays a huge role.
Older runners (60+) also show slower average lap times, likely reflecting natural endurance limitations.
Age-related trends are visible but not extreme, showing that with the right strategy, pacing can be strong at almost any age.
Does Gender Have an Impact?
Now let’s look at whether gender has an impact on overall BYU performance, given the factors considered above.
Insights
Females:
Show slightly lower lap time variability, suggesting more consistent pacing.
Run similar average lap times to males—no significant speed difference.
Tend to be slightly older on average.
Males:
Complete slightly more laps on average.
Show higher lap time variability, possibly due to more aggressive or riskier pacing.
Summary:
Pacing consistency is a strength for female runners, aligning with broader ultramarathon research.
Men may go further, but women pace more evenly.
Overall, both genders perform similarly, and success in backyard ultras is not strongly gender dependent.
Conclusion
From the data available, we can see that the attributes of a successful BYU athlete include:
|
Lap Pacing |
Overall, 46-52 minutes per lap band is the desirable pace for longevity in a BYU.
This narrows to 47-49 minutes when achieving 40+ laps.
For hillier courses, the desired pace sits in the 50-54 minutes range. |
|
Pacing Variability |
Some variability in lap times has little impact on performance.
Extreme fluctuations may hurt endurance, so pacing variability should be kept to below 4 minutes. |
|
Course Elevation |
To compensate for hillier courses, a sliding scale of 1-4 minutes should be added to a runner’s typical lap time on a flat course. |
|
Age |
The furthest distances are covered by runners in the 30-50 age bracket.
But there is ample evidence of runners outside that range still covering significant distances. |
|
Gender |
Success in backyard ultras is not strongly gender dependent.
Men complete slightly more laps, but women pace more evenly. |
On a personal note, yes I have been running my laps too quickly!
All constructive feedback, whether data-based or driven from personal experience, is welcome. Please contact me at ian@onemoremile.run.
As more race results come on-stream, these will be incorporated into the master dataset to provide more detailed insight.
References
Race data has been taken and analysed largely from the Webscorer website for the following BYUs:
|
Race |
Country |
Elevation (feet) |
Results |
|
2025 |
|
|
|
|
Longbridge Winter |
United Kingdom |
623 |
|
|
2024 |
|
|
|
|
Winona Forest |
United States |
200 |
|
|
Brighton |
New Zealand |
164 |
|
|
Borlange |
Sweden |
147 |
|
|
Longbridge Summer |
United Kingdom |
623 |
|
|
Cursores |
Finland |
150 |
|
|
Longbridge Winter |
United Kingdom |
623 |
|
|
Cappys |
United States |
292 |
|
|
Big Tex |
United States |
39 |
|
|
Campeonato Mundial Satelital |
Bolivia |
200 |
|
|
Rumi Chaki |
Bolivia |
120 |
|
|
Lagunitas – Kuntur |
Bolivia |
220 |
|
|
La Paz – Mallasa |
Bolivia |
200 |
|
|
Cappy's Backyard Ultra |
United States |
295 |
|
|
2023 |
|
|
|
|
Brighton |
New Zealand |
164 |
|
|
Brunei Backyard Ultra |
Brunei |
Unknown |
|
|
Cursores |
Finland |
150 |
|
|
Rockys Backyard Ultra |
United States |
Unknown |
|
|
Taipei |
Taiwan |
88 |
|
|
2022 |
|
|
|
|
UK Backyard Satellite National Championships |
United Kingdom |
108 |
|
|
Borlange |
Sweden |
147 |
|
|
Cursores |
Finland |
150 |
|
|
Brunei |
Brunei |
Unknown |
|
|
Backyard Ultra Costa Rica Chapter 1 |
Costa Rica |
Unknown |
|
|
2019 |
|
|
|
|
Devil's |
Canada |
754 |
Ian Wilson
March 2025