After the Boston Marathon on Monday, the New York Times has a thought provoking analysis of marathon finish times. Theoretically, marathon finish times should be relatively evenly distributed around a mean. In particular, there’s no real reason why, say, a 3:29 finish should be more common than a 3:31. But it is.
I don’t think this clustering is really that weird. I think it’s a natural function of our common need for competence, and the way we use benchmarks and progress tracking to achieve goals.
It’s fairly common for a runner to set a goal time for a race. That goal is typically, although not always, a round number. Some runners may have multiple goals. For example, when I ran my marathon, my stretch goal was 4 hours, my second goal was 4:30, and then my ultimate goal was just to finish. It’s also fairly common for runners to obsessively track their progress in some way. I know many people who use GPS-enabled watches or apps and get auditory feedback during the run. I fall into a kind of middle-tech group, where I use only a stopwatch while running. Even people who don’t make the effort to get progress feedback normally are subjected to it during organized races, when typically there are clear mile markers and often digital clocks displaying the time since the start gun.
Well, we know tracking progress all by itself improves performance, both for food intake (Hollis et al., 2008; Kruger, Blanck, & Gillespie, 2006) and physical activity (Bravata et al., 2007). Understanding current performance gives people information they can use to improve it. In the context of a marathon, if you have that goal time in mind, you can use your progress tracking to calibrate your efforts.
Imagine you’re nearing the end of the race and you’re tired. Suddenly you look down at your watch as you pass the last mile marker, and realize the data suggests you can make your goal time if you hustle. You might normally keep your pace steady or even slow down with fatigue, but the promise of achieving the goal puts some gas in the tank. I would bet that if we could look at a mile-by-mile breakdown of the folks who finish just under a milestone time, you’d see they gained speed in the last mile or so. I think that statistically significant bump of finish times right under the milestone comes from people who used tracking to achieve their goals.
If you run, do you find yourself speeding up at the finish line to make a goal time?
- Hollis, J. F. et al. (2008). Weight loss during the intensive intervention phase of the weight-loss maintenance trial. American Journal of Preventative Medicine, 32(5), 118-126.
- Kruger, J., Blanck, H. M., & Gillespie, C. (2006). Dietary and physical activity behaviors among adults successful at weight loss maintenance. International Journal of Behavioral Nutrition and Physical Activity, 3.
- Bravata, D. M., et al. (2007). Using pedometers to increase physical activity and improve health: A systematic review. Journal of the American Medical Association, 298(19), 2296-2304.