Today's Sabersphere includes the value of pitchouts, predicting pitcher injuries, and Michael Bourn's affect on Jonathan Papelbon's pace.
Russell Carleton looks at pitchouts: Pitchouts and My Underage Gambling Problem
Last week, my colleague Sam Miller ran a few numbers on the pointless, yet poignant play that is the pitchout (a billion points to whomever catches that reference) and concluded that pitchouts are actually a net loser: they cost the defense/pitching team more in runs than they gain. Sure, individual pitchouts sometimes nab a would-be base stealer (and that's a good thing), but overall, managers guessed wrong so often that the expected payoff wasn't high enough to justify the strategy. Rule number one of strategic thinking is that just because you got lucky on a stupid bet, it doesn't negate the fact that it was a stupid bet.
This study is a start at looking at injury projections. It is far from perfect, but I hope to get the ball rolling to help to get some initial numbers for people to mull over. I am just looking at the chances of a starting pitcher going on the DL and will look at projected time lost later.
FanGraphs keeps track of pitcher Pace, which you already knew. Here’s a definition of what pitcher Pace is, in case you need to brush up. The data comes from PITCHf/x timestamps, and while Pace doesn’t have any meaningful correlation with wins and losses — that is, it doesn’t make you better to speed up or slow down — it does have a meaningful correlation with what we might call "watchability". While we’re all ultimately in it for the baseball, it’s a lot more fun to watch a game with a fast tempo than a game with a slower tempo. A game with a fast tempo makes the baseball more concentrated.
few days ago, Bill Petti and Jeff Zimmerman did a two-part series introducing Edge% at Fangraphs. In it, they explained how pitchers that work to the edges of the strike zone see batters make less contact and get more swings on pitches out of the strike zone. They also found a positive correlation between Edge% and a pitcher's percentage of runners stranded on base (LOB%) of 0.13. They found that pitchers in the top ten percent of Edge% had an average LOB% 1.4 percentage points higher than the pitchers in the bottom 25 percent of the data pool.
If you would like to submit an article for Sabersphere, please email me at SpencerSchneier22@gmail.com.
Today's BtB Retro is R.J. Anderson asking the community for the best AL team blogs in terms of sabermetrics. So I ask you: Which are your favorite?
like reading about baseball, especially from bloggers who really know their own team. But as a guy who's into the sabermetric point of view, it can be frustrating to wade through a lot of team-specific blogs to find the one I want to read. So, I need your help.