Patrick Smyth placed 10th in the New York City Marathon on Nov. 6 in a time of 2:16:34. During the race, he wore a Stryd power meter foot pod which provided data that measured his power, pacing and fatigue. You can see in the gallery of slides and images below, Smyth’s information from Stryd. For more insights, we asked his coach Ryan Bolton—the founder and head coach of Bolton Endurance Sports Training (B.E.S.T.) and The Harambee Project elite training group in Santa Fe, N.M.—to analyze Smyth’s power data.
Patrick Smyth's Power Data
Pace (blue), Power (yellow), and Elevation (purple) are shown here in Stryd's analytic platform Power Center. Overall, Patrick Smyth ran a very steady pace and tried to avoid the mass accelerations that are often seen on New York’s rolling course profile, especially in the 16- to 19-mile range.
Time in Power Zones
Patrick's average power for the entire race was 306.58 watts. The first half was 8 percent higher than the second half at 319.41 watts and 293.95 watts, respectively. Total power is a measure of how much effort/intensity went into his race. In the Stryd file the most notable drops in total power are early on in the race on the downhill section of the Varrazano-Narrows Bridge (4:50 to 10:20) and then later on the downhill of the Queensboro bridge (1:17:10 to 1:21). The first drop in power was due to both a slowing in pace (they slowed slightly for that mile or so) and with a lesser need to push power on a downhill section. The drop in power on the Queensboro Bridge didn't coincide with a decrease in pace and was solely due to the “easier” downhill running. This would suggest that he could have ran both of those sections slightly faster and maintained power with not much more effort. As will be seen in the next slide, his form power actually increased during both of those sections due to the increase in down force and less efficient form on these sections. As the race progressed, and particularly from the 1:20 mark and on, power decreased in direct proportion to a decrease in pace (slowing). This would be expected in that it takes less overall power as pace slows. Had he increased his pace in the second half his total power would have actually increased in the second part of the race. The chart shows above how much time was spent at different power ranges measured in watts. As can be seen, nearly all of the time was between 280 and 350 watts.
Form Power in Relation to Total Power
Less efficient runners have a higher form power, especially in relation to total power. Basically, as run form diminishes your form power increases. Patrick has a very efficient running technique and thus has relatively good form power. His average form power was 65.28 watts, but he did see saw increase in form power of 2.2 percent from the first half to the second half. This means that as the race progressed he did get less efficient, which is to be expected. However, the increase isn't nearly as much as can often be seen in amateur athletes and competitors at the end of triathlons. Basically, Patrick did slow slightly in the second half, but he didn't let his form fall apart much. When looking at form power in relation to total power, it's most useful when expressed as a fraction of total power. As stated above, Patrick is efficient and form power in the early parts of the race is 20 percent of total power. That's solid. However, as the race progresses and he gets more fatigued, form power is near 30 percent of total power, showing a decrease in efficiency.
Vertical oscillation is a measurement of how much an athlete travels up and down while running forward, with normal values ranging 8 to 14 cm. Patrick's average vertical oscillation was 8.1 cm during the marathon, which is certainly on the low end of the scale. As a marathon runner, being this efficient is very helpful. Excessive vertical oscillation results in poor running economy and excess energy expenditure. Therefore, you'll often see successful marathon runners on the lower end of the oscillation scale. However, there is a happy medium and some oscillation is necessary for running economy. Too high (15 cm plus) or too low (7 cm or below) is not good. Ground time measures how long the foot is contact with the ground from foot strike to toe off. Typical numbers to see for ground time are in the 150 to 300 ms range. This number varies with run speed and efficiency. Shorter ground contact times are associate with a more efficient stride, and, thus, a better use of energy. That can really add up over the course of a marathon. This chart shows vertical oscillation broken down between the air time (yellow) and ground time (orange) components, as well as the total (blue). By looking at the vertical oscillation in this way we can gain a more meaningful insight into fatigue. Typically what happens when fatigue sets in is that ground time oscillation goes up while air time oscillation goes down as you tend to spend more time on the ground. Such a diverging trend is a great indicator of running fatigue. Patrick's ground time average for the race was 175.29 ms. That's in the low end of the range, which is what would be expected from a runner of his caliber. As the race progressed his ground time increased, which is also expected as an athlete fatigues. However, the highest value he hit in the entire race was around 240 ms, which is still well within the recommended range. Ground time did increase in the second half by 8.4 percent, which is notably almost directly related to his decrease in speed.
Power Data Comparison
Notably, at the beginning of the race, Patrick's vertical oscillation values were higher and as the race progressed they gradually dropped. This decrease is closely correlated with his leg stiffness. At the beginning he has more stiffness and more oscillation. As the race progresses, he lost stiffness and oscillation, showing that maintaining at least some oscillation is important. Leg Stiffness is a measurement of how much energy a runner can recycle. An increase in stiffness is generally good and a decrease is generally bad. Vertical oscillation and ground time are closely correlated. Higher levels of vertical oscillation and shorter durations of ground time both equate to greater leg stiffness. Therefore, just as Patrick's vertical oscillation decreased and ground time increased, his leg stiffness also decreased as the race progressed. This shows a sign of fatigue, albeit not to a great extent. A good cadence range for marathoners is in the 180 to 200 steps per minute (SPM). Patrick averaged 182.85 SPM and held very steady throughout the race, even when fatigue was setting in. This chart summarizes Patrick's overall average, first half average and percentage change for many of the key Stryd measurements. Without knowing his overall time, a lot could be concluded by just looking at these numbers.
2016 New York City Marathon
The big question now is, how can we use this data to guide Patrick's training and racing going forward? The most notable items in all of the data is what happened to Patrick's form in the latter half of the race, and even more specifically from mile 16 to 26. His form power decreased and became a higher percentage of his total power, indicating a loss of efficiency. Leg stiffness, ground time, and vertical oscillation also indicated this. The good news is, all of these parameters are interrelated. When we work on one, the others have potential to improve. Therefore, in future training sessions, especially ones that induce significant fatigue, we will use the Stryd data as both immediate feedback and in post workout analysis to work on improving his weaknesses. Ground time is certainly a good parameter to measure in real time, where we can focus on “quick feet,” which will also improve leg stiffness and vertical oscillation. Additionally, we will incorporate specific drills during easier sessions that improve his overall form. While Patrick didn't fall off the deep end late in the race, he did show some signs of inefficiency that can be corrected with proper training and feedback from power files. Over time, these small improvements in each parameter will pay large dividends in future races. Photo: PhotoRun.net