Even in this golden age of football analytics, the prevailing wisdom in much of the draft community is still to trust one’s own eyes over combine numbers. Many believe in “game speed,” the idea that a player’s movement ability on the field is separate from and does not necessarily translate to his performance in drills.
Just for fun, let’s pretend this is true, and that the only way to measure game speed is to watch players on the field. We now need to examine the way we perceive speed visually.
I’ve realized that although experienced evaluators have a strong ability to judge instinct and technique in prospects, they often struggle to isolate and appreciate physical traits, such as speed and lower body explosiveness, where their eyes can be misled by certain illusions. Straight-line speed seems like it would be the easiest trait to evaluate visually, but I find it is where many of us reveal our limitations.
We Really Aren’t Good At This
Every year players expected to ace the combine post mediocre or even slow times while others far exceed expectations. This disparity doesn’t matter if you believe in game speed, and drills such as the 40-yard dash certainly have a good amount of variance from trial to trial. Lingering injuries or even something as small as a head cold can throw off a time, and this in a drill where two tenths of a second is the difference between an elite performance and a disappointment. Still, we can be somewhat confident in 40 times because the participants have been coached on how to run the drill and are given multiple attempts.
So, in most cases the combine does not lie to us. This means we need to be held accountable for our bad takes.
@DonJamesSports Kaelin Clay
— Paulo Figari (@Paulo_FigariNFL) February 18, 2015
Kaelin Clay & Sammie Coates are about to run back-to-back. They could set the 40YD track aflame.
— Shane Alexander (@Alexander1Great) February 21, 2015
@JuMosq Wed night is my expectation. I got $25 on Kaelin Clay for best 40.
— Jeff Risdon (@JeffRisdon) February 14, 2015
— Jordan Plocher (@PFF_Jordan) February 14, 2015
He ran a 4.51. Improved to a 4.46 at his pro day.
I could go on with this. Braxton Miller said he was going to run a 4.28 this year and a lot of y’all believed him. I have the tweets.
Maybe we should just admit that #watchthetape isn’t as simple as it sounds. Our task is to judge the speed of different athletes of different sizes in different situations from different angles without timers and with limited points of reference. We call it “grinding.”
Process The… Procedure
Say we’re watching a receiver run a 9 route to get a feel for his speed. A 9 route is the closest thing in football to a straight-line sprint, except that our sprinter will likely need to run through or around defenders and look back for the ball at some point. We can use the hashmarks to measure how far our receiver is traveling, which should make the subconscious math our brain performs when we track an object through space a little bit easier. Remember that our strongest possible takeaway here is “this guy looks pretty fast.”
If we are using game footage to watch the 9 route we are already at a disadvantage because camera movement heavily distorts the speed of players on the field (this can be mitigated with All-22, but that is not always an option). And even if we could view the full route from a stationary position in the stadium we would still need to have an idea of what elite speed actually looks like in order to recognize it. This is difficult because turnover rate, stride length, and posture will all differ among different athletes even when the athletes are moving at the same speed. We need to be conscious of this.
The Components of Speed
In my experience, many evaluators tend to overvalue turnover rate (a.k.a. stride frequency, or how quickly you complete your running cycle) when estimating speed. Players with shorter legs take shorter steps, so their feet move back and forth more quickly, creating the illusion that they are moving at a much faster speed than those around them. The legs of the 5’6 Darren Sproles actually appear to blur on camera because his turnover rate is so insane, but the 6’5 Calvin Johnson eats up more yardage with a stride length that spans continents.
No single time at the combine can perfectly capture every component of speed. Athletes with elite acceleration and only middling top speed, as well as vice versa, can post good times in the 40. 10 and 20 yard splits can help us determine acceleration, but this doesn’t change the fact that the 40 provides only a glimpse of top speed.
Various efforts have been made by analytics sites to attach more meaning to the 40-yard dash. The “speed score” developed by Bill Barnwell adjusted the 40 for player weight and successfully identified famous bargain picks Arian Foster and Brandon Jacobs. But knowing how impressive speed is at a certain weight still doesn’t tell us much about how that speed is generated.
The Different Kinds of Speed
For this we can turn to metrics such as the Foot Speed score developed by David Marver (@ChangeThePadres), which reasons that the combine’s broad jump is the closest we can get to measuring stride length, and therefore by comparing the rarity of a player’s 40 time to the rarity of his broad jump we can estimate his foot speed. As far as I can tell, this is about as close as anyone in the football community has come to measuring *types* of speed.
It is an important innovation because we generally want players at different positions to be fast in different ways. One sought-after trait in receivers is the ability to separate from the defender downfield, which requires an “extra gear.” A receiver whose 40 time is mostly a result of his ability to accelerate due to his foot speed is less likely to possess this elite top speed than a player with a similar 40 time but a longer stride.
Conversely, acceleration is often valued over top speed in the evaluation of running backs, as the first objective of every run play is to get past the first level of the defense. Foot speed is important for this because it implies an ability to adjust for backfield disruption and accelerate into initial contact. This is what makes Derrick Henry such a fascinating prospect. He is an excellent speed athlete for his weight, but both his height and broad jump imply a greater stride length and lower foot speed than almost any other back in recent history. He is a very important case study.
Analytics shouldn’t diminish the importance of what we see, it should help us see more. There is a lot of evidence suggesting that combine stats, when used selectively to answer a specific question, can be strong predictors of NFL success. But even if there is such a distinct thing as game speed, we need to be aware that processing it visually is not such a simple thing. Whether we choose to employ analytics or to better train our eyes, our goal is to diminish the gap between what we see and what is true.