- Jared Cross, ESPN Insider
Johnny Cueto's left knee buckles. To the runner on first, it appears, if only for an instant, that Cueto is about to lift his front leg and deliver a pitch. Instead, it's Cueto's back foot that moves first, two lightning-fast steps rotate his body nearly 90 degrees, and he throws a bullet to first base across his body. This Cueto two-step is the single best defense against baserunning in baseball, more effective than Yadier Molina's fantastic arm and quick release, and capable of making stolen base attempts untenable for even the fastest runners in the game.
The rate of pickoffs, perhaps unsurprisingly, is closely tied to the intent to steal, and when calculating success rates, it makes sense to include them in our calculations. Since the beginning of 2011, Cueto has nabbed eight runners with his move to first base -- note that all pickoff numbers in this article do not include pickoff-caught stealing -- while another 13 have been caught stealing second. Only two runners have stolen second base successfully on him. In other words, runners have been successful in less than 9 percent of their attempted steals of second base on him.
John Lackey highlights the other end of the spectrum. Lackey hasn't picked off a runner from first base since 2003. Over the past three-plus years, 65 runners have stolen second base on him, while only nine have been caught, a success rate of 88 percent.
So how much of this difference between these two pitchers can be explained by their battery mates, the runners they've faced, the game situations they've pitched in and just plain ol' luck? Well, independent studies by Thomas M. Loughin and Jason L. Bargen, John Dewan and Max Weinstein agree that pitchers have considerably more control over the running game than catchers do. John Dewan estimated that pitchers have 65 percent of the control, with the other 35 percent going to the catchers. In fact, pitchers have more control over the runner's chance of success than the runner himself.
To identify the most effective pitchers over the past three-plus seasons and to see just how successful they've been, I followed in Loughin and Bargen's footsteps and built two mixed-effects logistic regression models. The first model predicts the probability of a stolen base attempt based on the pitcher, the catcher, the runner, the inning and the score as well as the lineup position of the batter. The second model predicts the chance of that stolen base succeeding based on the players involved. These models provide estimates of how much each runner, pitcher and catcher affects both the probability of a stolen base attempt and the chance of success.
More on the Cueto-Lackey divide
While Cueto has enjoyed having above-average catchers, according to our model, he is easily the dominant factor in his own success.
Stolen bases are decided by the pitcher, not the catcher, and Jared Cross looks at the easiest (and hardest) pitchers to steal on.