Is speed really that important?
August 3, 2007 6 Comments
90 feet. Go.
Baseball is a game of hitting and running (and pitching, but that’s something else). In order to score, a player must actually run the 360 feet around the basepaths (in 90 foot increments) to end up back at home plate, and the faster a runner he is, the more able he will be to accomplish this. Right? Speed is one of those things in baseball that everyone seems to think is important, but they’re not entirely sure why that is. After all, it’s not entirely raw speed that influences whether or not someone is good on the bases. For example, in stolen bases, some amount of ability in reading the pitcher must be involved, and for what it’s worth, the pitcher’s abilities in holding the runner and the catcher’s arm must be taken into account. But then again, speed can influence categories commonly thought of as being hitting-related. Beating out an infield hit still raises a player’s OBP and AVG.
But how much does speed really matter on the basepaths? Runner on third, one out and the batter hits a high fly ball to left field. You’re the third base coach. Do you send the runner? How will you make that decision? Well, in previous work, I found that you’re not thinking about how fast the runner is. You’re looking at how far away the ball is. Even more, it doesn’t really seem to matter how fast the runner is as to whether or not he makes it. Not only do 97% of all runners who attempt to score on a fly ball to the outfield make it home safely, but speed doesn’t seem to be much of a determining factor as to whether or not the runner will make it home safely. In fact, most runners who attempt to take an extra base generally make it.
Time to break out one of my favorite techniques: binary logistic regression. This is a type of analysis that answers the question “What are the odds?” and allows us to see how different factors influence those odds. How do I know that speed isn’t much of a determining factor in telling us whether the runner will make it home safely on the potential sac fly? Well, binary logit tells us whether or not something significantly influences the odds, and if so, by how much (for you stat geeks, I look at Nagelkerke R-squared as my measure of variance explained).
One quick question to answer: How to measure speed? I’m using the good old Bill James speed scores method. In an article to be published in the upcoming edition of By The Numbers, I actually developed my own speed measure from the ground up using some fairly high-level methodology (which took forever to calculate). James’ method and mine correlated at .81. Mine was a slightly stronger measure in terms of scale properties, but his is much easier to calculate (and the scale properties are still pretty good). After going through all the analyses that I did, it turns out the James method works pretty well. I stuck with it.
So, when would speed come in handy? It sure would come in handy trying to go from first to home on a double. I coded for all times from 2003-2006 in which a runner was standing on first, his teammate at bat doubled, and the runner did not stop at third. Either the runner in question was slapping hands with the on-deck guy after scoring (success!) or he went back to the dugout having been thrown out (failure). I only looked at those runners who made the attempt and ignored all the guys who just stopped at third and called it a day. I entered his speed score in as a predictor into the logistic regression. Sure enough, speed significantly predicted the odds that he would be safe in the expected direction (faster runners were more likely to be safe), but the Nagelkerke R-squared was…. 1%. That’s it. One percent of the “recipe” for the odds of whether or not a runner will make it is how fast he runs. I tried restricting the sample to situations with less than two out (still 1%) and situations with two out (a little south of 1%.) I looked at fly balls with less than two outs figuring that the runner might hesitate to see if the ball would be caught (all the way up to 1.5%). I made sure that the ball went through the infield (1.1%).
Second to home on a single? R-squared was 1.2%.
First to third on a single? R-squared was 0.2%.
What about the most obviously visible time when speed comes into play: the stolen base. I isolated all SB attempts of second base. The R-squared for speed did make an impact here: 4.2%. Not anything to sneeze at, but probably less than you expected. Previously, I’ve found that something as simple as whether the pitcher throws over is good for explaining even more of the variance (7.6%).
But there is one extra thing that speed helps with. I looked at situations in which there was a runner on first and the batter hit a ground ball to one of the infielders (i.e. a double-play ball). Did the batter’s speed help him to stay out of the double play? Yes, and it explained 5.5% of the variance.
Why are these number so low? Even on something like a stolen base, only 10% of the variance in success rates has to do with speed? Well, the other determining factors of whether the runner will make it are how big a lead he gets, how good the pitcher is at holding him on (those two will be correlated), how well the catcher throws, what sort of pitch the pitcher throws, and a few other factors. With some of the extra base advances on hits, there’s the issue of where the runner is when the ball is picked up and how far away that is from the base he’s trying to reach. Plus, you try throwing a ball 350 feet and hit a target to within a foot or so. The point is that while a speedy runner will have an easier time about things than a slower runner, the contribution of speed is not all that big. I’d guess that a lot more has to do with how well the fielders react.
So what does this mean for teams? Some teams keep a guy around whose only real purpose is to pinch run (and have a few at-bats in garbage time). Sure, there are some situations where every little bit helps, but the contribution of speed in most situations is much less important than I believe is generally thought. Even the strategy of pinch-running for a big-hitting (but slow running) player with a banjo-hitting but faster guy late in the game seems to have its drawbacks. Why lift your best hitter for a pinch runner, especially in a tie game, when the hitter might need to come up in the extra innings? All things being equal, a faster runner is a better player, but remember: you can walk home on a home run.