This is a very interesting analysis of runner performance with and without the Nike Vaporfly. I'd expect this to be of interest to the running and sports science community, and also the general public as it shows how new technologies can impact the outcome of competitive events. In a case such as this, the early adopters will gain a competitive advantage for however long the benefits of the new product remain unknown to the broader pool of competitors. I hope this analysis will reach the most relevant communities. I have a few questions and comments below. Some of these might be worth commenting in the paper, but for the most part they are for my own curiosity. 1. The analysis notes a performance improvement for athletes who have switched from non-Vaporfly to Vaporfly. Are there any instances of runners going in the other direction, from Vaporfly to non-Vaporfly? If yes, do you find anything interesting in the first performance back without Vaporfly. If not, do the authors believe this is because there has not been sufficient time to observe such a switch or because the performance enhancement is noticeable enough to the athletes that they would not want to switch? 2. Your model includes a random effect for each marathon, which I suppose captures any factors associated with all runners in that race running faster or slower than usual, e.g., bad weather, wind, etc. Have you considered to include a course effect for any marathons in your dataset that were run over the same course in different years, e.g., Boston 2016 and Boston 2017. Would this possibly help tease out any additional variation in course-day variation? 3. Presumably athletes who switch to the new shoe would want to know whether the shoe is going to help their performance specifically, rather than just a positive association over the population of all runners who wear the shoe. Is it possible to draw a casual relationship from the results of this analysis? The authors mention some potential confounding factors, such as cost of the shoe and runners knowing whether they are training well for an upcoming race. If one were to attempt such a causal inference, what additional analyses should be carried out? 4. I'm curious whether any of the authors have actually worn the Vaporfly. Can the authors provide any anecdotal evidence about their experience with the shoe, particularly in comparison to their experience with other (apparently inferior) shoes.
This article presents a clear and well-written study of the association between wearing the vaporfly running shoe and race time in the context of elite marathon runners. I have several comments.
We collected marathon performance data from a systematic sample of elite and sub-elite athletes over the period 2015 to 2019, then searched the internet for publicly-available photographs of these performances, identifying whether the Nike Vaporfly shoes were worn or not in each performance. Controlling for athlete ability and race difficulty, we estimated the effect on marathon times of wearing the Vaporfly shoes. Assuming that the effect of Vaporfly shoes is additive, we estimate that the Vaporfly shoes improve men's times between 2.1 and 4.1 minutes, while they improve women's times between 1.2 and 4.0 minutes. Assuming that the effect of Vaporfly shoes is multiplicative, we estimate that they improve men's times between 1.5 and 2.9 percent, women's performances between 0.8 and 2.4 percent. The improvements are in comparison to the shoe the athlete was wearing before switching to Vaporfly shoes, and represents an expected improvement rather than a guaranteed improvement.
➤ Version 1 (2020-02-14)
Joseph Guinness, Debasmita Bhattacharya, Jenny Chen, Maximillian Chen and Angela Loh (2020). An Observational Study of the Effect of Nike Vaporfly Shoes on Marathon Performance. Researchers.One, https://researchers.one/articles/an-observational-study-of-the-effect-of-nike-vaporfly-shoes-on-marathon-performance/5f52699d36a3e45f17ae7e40/v1.