Context Adjustments: Catchers and Stolen Bases (Part 1)
In FanDuel, a stolen base is worth 2 points. While the average starting hitter scores roughly 3 points per day in FanDuel, a player who gets on base via single, walk, or HBP and steals second will score 3 points right off the bat. As such, speedy players can have a lot of value in FanDuel but often seem to go overlooked in favor of power hitters who are playing in a favorable home run park. While I’m not here to determine which strategy is optimal, they both seem to have their merits, subjectively speaking.
Over the next couple weeks, I wanted to provide some insight for those who choose to go the speed route when selecting their FanDuel teams and examine one of the most important contextual factors when deciding whether or not a particular speedster is a good play on a particular day: the catcher.
The catcher is an integral part of the stolen base equation since he is the guy who will be attempting to throw your speedster out. As such, it’s important to identify which catchers are the best (and worst) at doing this.
While we could simply look at this year’s leaderboards and see which catchers have been the best thus far at throwing out runners, if you’ve been reading me long enough, you know that I’m not content to stop there. Because we’re dealing with finite samples when we work with baseball data, there will always be some amount of random variation in any stat we look at. For some stats, like strikeout rate or groundball rate, there’s very little. For others, like BABIP and HR/FB (for pitchers), there’s tons. How much random variation is in a catcher’s caught stealing rate, though? It’s a topic that’s never really been thoroughly examined, as far as I know, so I thought it’d be a good idea to do so today.
To study the amount of random variation in a catcher’s caught stealing rate, I’m going to use the same methodology as I did earlier in the year at Baseball Prospectus when I examined when hitting stats stabilize and when pitching stats stabilize. You can click over there if you’d like to read the full methodology, but the essentials are that I’ll be running a split-half correlation analysis, which means that I’ve taken half of a catcher’s stolen base attempts and put them in one group and put the other half in another group (the attempts that go into each group are randomized). I then look at the correlation between the groups at different intervals (i.e. after 10 attempts, after 20 attempts, after 30 attempts, etc.). I find the spot where the correlation (R) equals 0.50. It’s at this point that we can predict 50 percent of the future variation in a stat. Put another way, if a stat stabilizes at 100 AB and we have 100 AB of data for a player, we’d use a 50/50 split of the player’s actual data and the league to estimate his true talent for that stat. The more data we observe for a player, the less league average we use.
Running this analysis on a catcher’s caught stealing rate—defined as CS/(CS+SB)—we find that it takes 74 stolen base attempts (CS+SB) for the stat to reach an R of 0.50. A starting catcher will, on average, have 79 players attempt steals on him over a full season, so while every catcher is different, it takes roughly 94 percent of a season for the percentage of runners a catcher throws out to “stabilize.” To give you some points of reference, it takes a hitter’s strikeout rate roughly 16 percent of a season to stabilize, his home run rate 30 percent, his HBP rate 78 percent, and his singles rate 2.1 seasons.
The Best and Worst Throwing Catchers
Now that we know how long it takes for our stat to stabilize, we can use this point to create a regression to the mean equation that will tell us a catcher’s “true talent” level for throwing out runners. If I ignore seasonal weighting and aging issues for the time being and use all data from 2008-2010, we get these as our best catchers for throwing out runners (league average is roughly 27 percent):
No surprise, Yadier Molina is the best, and brother Jose Molina comes in second. You’ll likely want to avoid speedsters on days when they’re up against the Indians, Mariners, Astros, Reds, and Mets as well, since their starting catchers are all pretty good at gunning down runners. Of course, make sure you check lineups since even the best catchers only start behind the plate 70 percent of the time.
These are our worst:
Old timers Varitek and Posada are among the worst, and Posada doesn’t get many games behind the plate anymore. When Varitek starts over Jarrod Saltalamacchia for Boston, though, it appears to be a prime opportunity to let your speedsters loose. Actually, Salty appears himself a short way down the list, so pretty much anytime a speedster is up against the Red Sox, it’s a pretty good matchup. It also appears to be a good idea to pick a speedster when the primary catcher is starting for the White Sox, Tigers, Marlins, or Rockies.
Sorry for not posting last week. Hurricane Irene caused some trouble, but everything’s fine and I’ll be around for the rest of the season to help you out in selecting your FanDuel teams. While I looked this week at the catchers who are the best at throwing runners out, next week I’ll be looking at which catchers are the best at scaring runners into not running in the first place. The following week, I’ll take a look at how these two skills correlate and some other considerations when deciding which speedsters make for good plays.
Derek Carty’s work can also be found at Baseball Prospectus, CardRunners Fantasy Baseball, and DerekCarty.com. He has previously had his work published by The Hardball Times, NBC’s Rotoworld, Sports Illustrated, FOX Sports, and USA Today. He is the youngest champion in the history of LABR, the longest-running experts league in existence, and is a graduate of the MLB Scouting Bureau’s Scout Development Program (aka Scout School). He welcomes questions via e-mail, Facebook, or Twitter.
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