[learn_more caption="All Star Repost" state="open"] This post was originally written last year and is unedited. With many fantasy players beginning their research into the pitchers of 2014, we felt it was helpful to share it one more time. [/learn_more]
When it comes to sabermetrics many seem to say,”Bah! You kids and your new-fangles numbers!” Others talk about them as if to say, ”I’m smarter than you and I’ll prove it with my formula prowess!”
So before we go any further let’s define sabermetrics. To do that we’ll simply go to Wikipedia: “Sabermetrics is the specialized analysis of baseball through objective evidence, especially baseball statistics that measure in-game activity. The term is derived from the acronym SABR, which stands for the Society for American Baseball Research. It was coined by Bill James, who is one of its pioneers and is often considered its most prominent advocate and public face.” Click to read more or just go watch Moneyball.
There have been a couple primary areas that have contributed to the slow (according to some) adoption of sabermetrics:
- While sabermetrics deals with objective evidence, it is true that subjective evidence is important as well. A subjective phrase like “Who is your favorite baseball player?” is just as good a question as an objective one such as “Which Minnesota Twins pitcher had the most strikeouts per 9 innings?” (Answer: None of them.) Some have unfairly made this subjective versus objective analysis into and either/or argument, when it should have always been both/and conversation.
- Sabermetrics can seem overly complicated because it dives into sophisticated mathematical analysis, therefore seeming irrelevant, or “nerdy.” The sabermetric community often unintentionally perpetuated this by not talking about sabermetrics in understandable terms. For this reason, some will quickly write it off, rather than try to understand it.
This is the beginning of a series of posts called “Simple Sabermetrics” and the purpose is to talk about sabermetrics in simple, understandable terms. The truth is that sabermetrics absolutely can you make a better fantasy baseball player. Likewise, it can (no kidding) increase your love of the game when you’re at the ballpark.
For this first crack at simple sabremetrics we’ll start with FIP.
FIP stands for Fielding Independent Pitching. It also stands for Feline Infectious Peritoniti, a viral disease of cats. Do not get these two confused. FIP is, simply, the outcomes that the pitcher can directly control. A pitcher is responsible if he walks a batter. He’s credited if he strikes out a batter. It’s the pitcher’s fault if he gives up a home run. It’s not his fault if a fielder makes an error or if a ball falls for a hit 2 feet in front of Delmon Young or dribbles through the infield because Derek Jeter has a poor range at shortstop.
FIP was created by Tom Tango, but based upon research by Voros McCracken called DIPs Theory (Defense Independent Pitching Theory). The idea is to dig a little deeper than surface outcomes and evaluate pitchers based upon what they have direct control over.
Here’s how it’s calculated:
FIP = (13 * HR + 3 * BB – 2 * K) / IP + 3.20
You’ll notice the formula contains home runs, walks, and strikeouts, the three things a pitcher is in control of. The 3.20 is merely a constant to convert FIP to an ERA scale. But there is no need to calculate it yourself because you can find it on sites such as Fangraphs.
But while FIP is on an ERA scale, it is certainly not ERA. ERA is descriptive, whereas FIP tells you how well the pitcher should have done, not how well he actually did.
FIP can actually be an extremely useful stat for fantasy baseball because FIP is an excellent predictor. It’s also surprisingly simple to use.
Example #1: You are two months into the season and you have a pitcher that has an excellent ERA. Should you sell high? Well, you check his FIP and it’s actually higher than his ERA. You dig a little more and realize that he’s walking a ton of batters, but getting a little lucky in being able to strand them on base. You decide to trade him while his value is high, and his ERA goes on to blow up because all those walks finally caught up with him.
Example #2: Again, you are two months into the season and a pitcher you felt would be lights-out for you has an ERA of 4.50. You check his FIP and it’s 3.00. You realize that’s he’s striking out tons of guys, not walking very many batters and it’s suffering from the long ball. You wisely decide to hold on to him and his second half turns out to be CY Young caliber.
Above is a rough scale to help you understand what to look for with FIP. Use FIP each time you are questioning how well a pitcher will perform for the remainder of a season as it’s a simple, but excellent sabermetric tool to help you be a better fantasy baseball player.