John Litschert, RunScribe Biomechanist

Achieving Pace Consistency in Endurance Running

overhead shot of marathon

Pace consistency is at the heart of a runner’s training and is important for endurance races like the marathon. Coaches help athletes find their rhythm early as to not burn energy. Achieving pace consistency seems simple, but mechanically our bodies make constant and subtle adjustments.  We know pace is a simple equation: Pace = Stride Length x Stride Rate. But what is their relationship when fatigue strikes?

Races are great place for running research. With a set course, we’re able to eliminate variables and focus on a runner’s mechanics. We did a substantial study at the 2015 NYC marathon using RunScribe. But we also attended the 2014 NYC Marathon armed with RunScribe prototypes, which allowed us to dig into pace mechanics.

The Basics:

The 2014 experiment was a challenge for a few reasons: 1.) We knew nothing about logistics at a marathon – you can imagine how that went. 2.) We used prototype hardware and 3.) Onboard processing hadn’t been implemented yet, so we collected raw data that was processed after the marathon.  Despite this, we got 11 full sets of quality data, which allowed us to do a reasonable analysis.  

The Analysis:

We were fortunate in that a wide spectrum of runners volunteered. We quickly determined it would be advantageous to group them based on how their pace changed during the marathon.

  • Group 1 – Held a consistent pace throughout race
  • Group 2 – Consistent through first half and then slowed slightly during 2nd half
  • Group 3 – started slowing at around 10k and dropped off significantly toward the end

The following plot illustrates the groups.  Orange represents the super consistent group, pink the group that slowed during the 2nd half, and grey represents the group that started slowing after 10k and really struggled.  The blue line is the average of all groups.

Pace vs Distance (Grouped by Consistency)

Notice that each curve has a similar “shape” even though the general slopes are different.  These peaks and valleys are primarily due to characteristics of the race course.  For example, just before the 25k mark is the hill on the Queensboro bridge which corresponds to the slowest point in the race.  Between 25k and 30k the course is mostly downhill, reflected by an increased pace in all the curves. Finally, it looks like almost everyone mustered energy to increase their pace at the end.

The Scoop:

This data clearly indicates that fatigue hits Stride Length(SL) first. The consistent group’s plot is as expected – consistent. Their Stride Rate (SR) varies between 88.4 and 89.0 str/min which is less than one percent and their SL varies between 2.26 and 2.18 meters which is about 3%.  But by comparing the consistent runners to our other groups, we get a clearer picture.  

Pace, Stride Length & Stride Rate vs Distance (Consistent Group)


The runners who slowed a little during the last half of the race had a SR that went from 86.9 to 86.3 str/min which is still less than a 1% drop.  But the average SL of these runners varied between 2.43 and 2.16 meters or about 11% drop.  So the reduction in pace seen during the race is almost entirely due to the reduced SL.

Pace, Stride Length & Stride Rate vs Distance (Slightly Slowing Pace)

The next plot shows a more extreme version of this same story.  This data is from the runners that started slowing early and continued to do so throughout the race.  You can immediately see how much faster their pace drops off and also how much more SL is reduced compared to the other groups.  Their average SL peaks at 2.34 meters early in the race and drops to 1.67 meters at 40k.  A drop of 29%.  And, their SR starts at 88.0 and drops to 80 str/min.  A drop of over 9% compared to less than 1% for the other two groups.  In this case both SL and SR played a significant role in the runner’s pace drop off.  

Pace, Stride Length & Stride Rate vs Distance (Dramatically Slowing Pace)

So what can we deduce?  Clearly a shortening SL is the first sign of fatigue during an endurance run.  That makes sense because in order to maintain a given SL, runners have to continue to generate enough force during the stance phase to propel themselves through the air to the next step.  As fatigue increases, runners have a reduced capacity to generate the required force.  It appears SR is less energetically costly to maintain so in the early phases of fatigue it changes very little.  But as we see in the last plot, as we continue toward exhaustion, changes to both SR and SL contribute significantly to the reduction in pace.  

We know fatigue is inevitable in endurance racing.The best we can do is prepare adequately before hand with a well developed long term training plan (12 to 16 week marathon training plans are not enough!).  Including bounding drills and hill repeats in training are a good way to build strength and power. Introducing some cadence training into long runs or tempo workouts will make it easier to alter cadence when necessary during a race.  By tracking stride length throughout training, you can measure progress and make adjustments to strategy. For example, slightly increasing cadence to make up for the SL reduction that occurs with fatigue can be an economical way to maintain pace a little longer.