Diving into Statcast Sprint Speed
In April, Statcast quietly introduced a new speed metric dubbed Sprint Speed. It wasn’t until late June that Baseball Savant made the leaderboards publicly available and we now have data going back to 2015. I have been meaning to dive into the data to find any incremental value, and finally the day has come. From the leaderboard page, the metric is described as thus:
Sprint Speed is Statcast’s foot speed metric, defined as “feet per second in a player’s fastest one-second window.” The Major League average on a “max effort” play is 27 ft/sec, and the max effort range is roughly from 23 ft/sec (poor) to 30 ft/sec (elite). A player must have at least 10 max effort runs to qualify for this leaderboard.
You might recall that we already have a speed related metric on our player pages. It’s the Spd, or Speed Score, metric which was originally developed by Bill James and its components include stolen base percentage, frequency of stolen base attempts, percentage of triples, and runs scored percentage. So my initial curiosity stemmed from whether Statcast’s Sprint Speed correlated better with BABIP than Spd. My most recent xBABIP equation accounted for a hitter’s speed using Spd, but would Sprint Speed be an even better metric to use?
My assumption was that yes, of course it would be, as Sprint Speed is straight speed and ignores a hitter’s supporting cast (Spd is slightly team dependent given the “runs scored percentage” component, and also managerial philosophy dependent given its reliance on stolen base attempts). But rather than just run the correlation between Sprint Speed, Spd, and BABIP, I decided to compare the correlations between those speed metrics and a host of speed related stats. I only ran correlations for 2015 and 2016, ignoring 2017. So let’s get to it…
| Spd | Sprint Speed (ft / sec) | |
|---|---|---|
| Spd | 1.000 | 0.772 |
| Sprint Speed (ft / sec) | 0.772 | 1.000 |
| 3B/BIP | 0.719 | 0.537 |
| SB | 0.771 | 0.598 |
| SBA | 0.768 | 0.619 |
| SBA/PA | 0.800 | 0.659 |
| BABIP | 0.312 | 0.325 |
| IFH% | 0.429 | 0.533 |
I highlighted which speed metric correlated better with each speed-related stat. I was rather surprised to find that Spd “won” significantly in four of the six stats, while one of the two Sprint Speed wins was by a minor amount. Furthermore, I also expected Spd and Sprint Speed to correlate more strongly with each other. But it just goes to show you how context affects Spd.
At first, I wondered how Spd, which includes four components, could possibly correlate more strongly with triples per ball in play than Sprint Speed. Triples are essentially doubles for speedsters, so the faster you are, you figure will lead to more triples. But then I realized that triple percentage is a component of Spd, so of course it’s going to correlate highly with the metric. The same is true of the stolen base related stats I tested the correlations on.
BABIP, though, was not a component of Spd, so comparing the correlation here is a fair fight. Unfortunately, Sprint Speed barely wins, which is disappointing. I was so sure that Sprint Speed would prove to be far more correlated, which would help me improve my xBABIP equation, but that hasn’t proven to be the case. However, just because it doesn’t correlate much better with BABIP doesn’t necessarily mean it’s not the better metric to use. When the 2017 season ends and I have three years of data, I will run my xBABIP equation with the Sprint Speed metric instead of Spd and see if it makes much of a difference. Fingers crossed.
Interestingly, Sprint Speed won IFH% by a significant margin. Infield hit percentage is not a Spd component, so again it’s a fair fight. This might be telling that Sprint Speed is indeed a better metric to look at because the stats where Spd won were included in the calculation of the metric itself.
We still don’t have enough data to perform any heavy analysis. But what I would like to see is if we could use Sprint Speed as a stolen base breakout indicator. If a player hasn’t attempted many steals in the Majors, which likely resulted in a mediocre Spd score, but Sprint Speed confirms the player has excellent speed, does he beat his stolen base attempt projections the following year?
Mike Podhorzer is the founder of ProjectingX IQ, an advanced fantasy baseball analytics platform that transforms projection data and in-season performance signals into actionable intelligence. He is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year and three-time Tout Wars champion. He is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. Follow Mike on X@MikePodhorzer and contact him via email.
Thanks for doing some preliminary digging into this one, Mike. I am curious, what percentage of these measured “max effort” events are measured during multi-base events? Without any statistical basis whatsoever, I intuitively believe that acceleration is likely to play a bigger role in the stolen base stats than this sprint speed metric. Do players even reach max speed on a home to first or a first to second (etc) run?
Exit velocity seems like a huge part of BABIP. Foot speed is a factor, for sure, but Billy Hamilton has the one of the lowest Avg. EV’s in baseball. Despite that, he has an above avg BABIP (.320).
I like that you’re including batted ball types in xBABIP, but I think you could go further with EV.
The Statcast metric “xBA-BA” seems to correlate really well with foot speed. I’d be interested to see how well it does with correlating to Spring Speed or Speed Score.
I think I would be more interested to see how Sprint Speed in 2015 correlates to statistics in 2016 compared to the correlations of 2015 Spd to 2016 stats. Would Sprint Speed be better in identifying “speed breakouts”?
I am not surprised that peak speed doesn’t tell us much. Acceleration is more important than covering a few more feet per second over the course of a second. Taking an optimal route around the bases is also more important than peak speed. Those are the easy components to understand. The most difficult one is the mental aspect – anyone who has been around the game knows that some people are really good on the bases and some others are an out waiting to happen. As for your last point, speed is only one piece of stealing bases – I can’t imagine that sprint speed is a predictive tool at all for SB breakouts. If anything, it may be a predictor for CS as it is only one part of the equation. Without SB aptitude peak speed doesn’t do much.
You are definitely correct that speed is only one piece of stealing bases. But that other factor would show up more in success percentage. The fastest guys generally attempt the most steals, but smarter basestealers might be successful a higher percentage of the time. So I think raw speed is still a strong indicator of how often a player is going to be willing to run.
Speed certainly plays some part. The biggest factor is simply how much a guy wants to do it. Regardless of speed, most people are going to stop running if they get caught a few times. On that note, SB% is probably more predictive of increased SBs in a future year. Then there is the case where the league accepts that a player is not going to run, so the player takes advantage of that for a year. There are also a lot of guys that stop running when they hit enough. Stealing bases is hard and most guys just don’t want to try. There is no worse feeling than giving the other team an out.
As far as finding breakouts – the players and their teams know who is fast and who is not. It is not like they are going to unearth their speed through Statcast and alter their game. Speed is easy to see and measure – always has been.
As a dude that has spent a life around the game, the jump is the most important factor by a mile. It is impossible to measure though… acceleration is one thing, but getting a lean or an extra step before the ball is out of the pitcher’s hand is what makes SBs happen.
Actually, Statcast does measure lead distance but they haven’t released the data yet. Goldschmidt is one of the best according to statcast in lead distance.
I am not talking about lead distance at all. I actually don’t think that is very important. I mean the lean – like how much momentum do you have going to the next base before the ball is released?
Acceleration/quickness is interesting. Sprint Speed tries to measure a player’s top speed, which I think is different from “raw speed.”
Cody Bellinger has a really high Sprint Speed (28.6ft/s), just a step behind Trea Turner (29.2 ft/s). I’d guess that it takes Bellinger a few more steps to get up to top speed than it takes Turner. Those few steps are often what really matters.