Wednesday, April 01, 2015

The 100 Meter Sprint: What Can 2014 Tell Us About 2015?

2014 was probably not the most exciting year for the men's 100m sprint. There was no world championship or Olympics that year. Usain Bolt was out for most of the season after an ankle injury. Yohan Blake was absent due to a hamstring injury. Asafa Powell and Tyson Gay served drug bans for much of the year. Only Justin Gatlin made big headlines after winning the IAAF Diamond League and running with an impressive time and a personal best of 9.77s making him the fifth fastest human being of all time.

I graphed the best year times of over a dozen of the fastest 100m track sprinters currently active and then extrapolated. I chose a quadratic fit. It gave relatively good R-squared values meaning a close fit, and modelling a sprinter's progression over time seems to be parabolic: they start with a time of 10.3-ish, then progress further down maybe to 10, if they are good they can get a sub-10 time, let's say 9.9. But after reaching that peak (or minimum) they get older, more injury-prone, and slower. Our sprinter now runs at 9.98. The next year he's running in the low 10's. After that he runs 10.5 and then his professional career is probably over. 

A linear fit doesn't seem right, since sprinter's don't get faster forever: it's only useful for a short period of time. I would not consider their progression exponential either. No one (well almost no one) jumps from 10.1 in one year to 9.8 the next. If we increase the power and move to cubic, quartic or higher, the R-squared value increases, but the equation gets very dynamic, making modelling difficult. A moving average takes away much of the fluctuation and shows long term trends, but cannot be used to extrapolate and an appropriate period must be chosen.

Note that the extrapolations are probably no good after three years or so. It's all right to make an extrapolation for the next year, but after that your confidence level decreases. Sprinting is a very complex sport and is difficult to accurately predict a race's result.

Of course there are exceptions: Justin Galtin is a big one. His R-squared value is 0.5, so the extrapolation is correct 50% of the time. If we look at his history, this seems more understandable. Gatlin won the 2004 Athens Olympics 100m sprint in 9.85 seconds. However, he was banned in 2006 for drug use. Then he made a comeback in 2010. That year, his best time was 10.09, so many thought that his career was over. But they were wrong. Gatlin ran 9.95 the next year and won the bronze medal at the 2012 London Olympics with a time of 9.79s. He then ran 9.85 in 2013 and broke his personal best with a time of 9.77s at the 2014 Diamond League Final. Other factors to consider about Gatlin's unpredictability are his age (he is 33, quite old for a sprinter) and his previous history of performance-enhancing drug (PED) use.

Here is the graph showing the extrapolations for sprinters' best times up to 2016:


Note that the graph is truncated and only the data after 2011 is included.

The extrapolation suggests the following ranking for fastest sprinters of 2015:

1. Kemar Bailey-Cole (JAM)
2. Nickel Ashmeade (JAM)
3. Justin Gatlin (USA)

The problem with this prediction is that Bailey-Cole's best time is 9.93s and he would have to run .13 seconds faster (that's a lot in sprinting) in order to run his projected time of 9.80s. It's also unlikely that Gatlin will only run in 9.90s when one looks at his previous successes in recent years. Bolt is out of the picture and so are many other top-tier runners.

This projection will improve as sprinters begin to run again in competitions once the sprinting season is in full swing: that will probably be on May 15 during the first IAAF Diamond League event in Doha, Qatar.


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