Part 1: The New Revolution – Breaking Down Pitching Sabermetrics
UncleCharlie@fantasybaseballgeeks.com
Bill James defined saber metrics as “the search for objective knowledge about baseball.” Meaning saber metrics makes an attempt to solve the analytic questions about baseball, such as “Which Mets pitcher has the greatest value to his team?” or “How does Livan Hernandez have a better ERA than Dan Haren?” Sabermetrics in the fantasy baseball community have become overly popular in recent years, but this season I have seen a substantial spike in usage by main stream sites, such as CBS and ESPN. I had always gone to Fangraphs.com to get my fix, but I always relied on CBS and ESPN to give me the basic spin on things in an eccentric manner. To be honest, the overload of articles geared around sabermetrics from ESPN and CBS is kind of annoying me, and I have come to the point where I avoid those annoying graphs CBS puts out every week. When you have a graph that takes 30 seconds to load, includes 400 dots resembling your players and regression lines that take five minutes alone to comprehend it losses its effectiveness – that’s my opinion some might find it helpful (here is an example).
If I took a poll in each of my fantasy leagues, which generally consist of college friends, old baseball colleagues, and a few fantasy enthusiasts like myself, I would get a stirred reaction if I asked them to define the following terms: BsR, dERA, FIP, FIPx, ISO, WAR, WARP, BABIP, ERC, CERA, WPA. (Off the top of my head I could probably breakdown 5 of the 10 to someone, and I consider myself pretty up to speed on the sabermetrics of fantasy baseball.)
Therefore, in Part 1 of this series I plan on shedding some light on the most common terms for sabermetrics as they relate to pitchers and create a glossary for the beloved faithful of FantasyBaseballGeeks.com.
BABIP (Batting average on balls in play): It’s the success in which a batter reaches base safely on any ball in play. For pitchers, this is especially useful as it’s a good measure of luck. On average, if the ball is hit, and not hit out of the ballpark, you’re going to give up a hit around 30 percent of the time. So pitchers with high or low BABIPs are good bets to see their performances adjust over the course of the season.
Examples:
Leagues Luckiest Pitcher: Livan Hernandez currently boasts a ridiculous .188 BAIBP in 2010. Considering his career average is .309 he will start getting tagged pretty often and hard in the coming months meaning you should stay far away.
Leagues Unluckiest Pitcher: Justin Masterson currently boasts a bloated .411 BAIBP in 2010. ZiPS projected a BAIBP of .310 for Masterson this season meaning those balls that are sneaking through right now should start finding their way into gloves pretty soon. Masterson could be an excellent guy to pickup and enjoy the ride when his luck turns for the better.
FIP (Fielder Independent Pitching on an ERA scale): FIP helps you understand how well a pitcher pitched, even if he has a bunch of little leaguers taking the infield. You have to look at the three categories pitchers have control over and take the defense out of the equation, those are: Strikeouts, Walks, and Home Runs allowed.
Examples: Mike Pelfrey and Jonothan Niese
Mark Simon of ESPNNewYork.com did a great job breaking down the FIP of Mike Pelfrey and Jonathan Niese in this article. He indicated “Niese currently has a 3.73 FIP meaning he has given up 37 fly balls so far, but only three home runs (two coming against the Reds on Wednesday). FIP basically operates on the premise that he can maintain that kind of performance.”
“In Pelfrey’s case last season, he had an ERA of 5.03, a FIP of 4.39 and an xFIP of 4.52. Basically what that meant was that Pelfrey didn’t deserve the ERA with which he finished. FIP is believed to be a good predictor of future success, meaning that Pelfrey should expect an overall ERA drop for this year.” Which he has seen so far in early 2010, while I don’t believe he will maintain that low of an ERA it is not entirely shocking to see Pelfrey get out to the start he has in 2010.
xFIP (Expected Fielding Independent Pitching): Goes a step further and looks at how often your fly balls are home runs. Research has shown that home runs allowed are pretty much a function of fly balls allowed and home park, so xFIP is based on the average number of home runs allowed per outfield fly (Hardball Times).














