Contributed by: Ben Diamond

We’re now in the age of accessibility where anybody can get hold of anything. That’s a relatively general statement, but it’s applicable to fantasy baseball. Any data a fantasy player could want is available, and it’s up to you to use that data appropriately. The easiest way to gain an edge in fantasy baseball is to use this data, often termed sabermetrics, to your advantage. While BABIP and FIP are useful, these days all experienced fantasy baseball players understand them. But there are many other sabermetric type measurements which are lesser known, though arguably more important.

 

 

BABIP
 

BABIP, or batting average on balls in play, is a frequently used measure. It’s easy to understand and incredibly versatile. Each player will establish their own BABIP baseline. The average is different with all players, as a fast and hard-hitting player will have a higher average on balls on play than a slow and light hitting player (in general). Once a baseline is established, any deviation from the average can indicate either good or bad luck. For example, Chris Davis had a .242 BABIP in 2014, despite a career mark of .320. His BABIP rose to .319 in 2015 leading to a significantly better season overall.

 

Notables: Odubel Herrera: .297/.344/.418, .387 BABIP… batting average is likely to decrease

                Albert Pujols: .244/.307/.480, .217 BABIP… batting average is likely to increase

BABIP works for pitchers very similarly to the way it does for hitters, as mentioned above. If a pitcher’s BABIP is significantly higher or lower than their career average, then it is not a sustainable performance. The only difference is that pitchers want a lower BABIP, unlike hitters who will excel with a high BABIP.

Notables: Marco Estrada: 3.13 ERA, .216 BABIP… ERA is likely to increase

                Nathan Eovaldi: 4.20 ERA, .337 BABIP… ERA is likely to decrease     

 

Soft%, Med%, and Hard%


Soft, medium, and hard contact percentages go hand in hand with BABIP. There’s so much luck built into baseball that you can hit the ball hard four times in a game and go 0-for-4, or hit four bloopers and have a 4-for-4 game. That said, it’s important to recognize when hitters are making quality contact and getting unlucky, and vice-versa. These measures can point to breakouts, as well as artificial hot and cold streaks. Fangraphs.com lists the averages for Soft%, Med%, and Hard% are 20 percent, 50 percent, and 30 percent, respectively. If a player is well above average in a category, then it may be worth looking into. For example, Luis Valbuena came out of nowhere with 25 home runs in just 132 games in 2015. Or was it out of nowhere? Upon closer inspection, his hard percentage was 36.2 percent in 2014, pointing toward a power breakout.

 

Notables: Brandon Belt: .280/.356/.478, 18 HR, 39.5 hard%… power production is likely to increase

               Josh Reddick: .272/.333/.449, 20 HR, 25.2 hard%… power production is likely to decrease

 

ISOLATED POWER


The baseball cliché “those doubles will start to turn into home runs soon” can be measured by ISO. Isolated power is a measure of a player’s raw power, with anything above .200 being elite, and below .120 being weak. ISO can be an indicator of an eventual power breakout and can help to uncover powerful bats who have yet to start hitting home runs. If a player has a high ISO, but not many home runs, he could see a serious bump in power production soon.

 

Notables: David Peralta: .312/.371/.522, 17 HR, .210 ISO… power production is likely to increase

                 Brandon Phillips: .294/.328/.395, 12 HR, .100 ISO… power production is likely to decrease

 

wRC+


There are predictive stats (like BABIP) and then there are evaluative stats. These give an accurate representation of how a player is performing right now, the most useful of which on offense is wRC+. WAR is great in real life, but in fantasy, defense doesn’t matter. So, wRC+ is a worthy replacement. wRC+ takes everything on offense into account, as well as park factors (dimensions of a stadium) and league factors (average offensive performance around the league). wRC+ considers a league average offensive performance 100, with anything lower being below average, and higher being above average. wRC+ is great for comparing players overall offensively. The highest wRC+ in 2015, or best offensive performer, was Bryce Harper at 197. The worst was Chris Owings, with a 52 wRC+.

 

FIP/xFIP/SIERA


The most widely known way to evaluate pitchers, and the second well known sabermetric, is FIP. Fielding independent pitching recognizes the luck involved in pitching—such as defense and random changes in BABIP—and throws away the factors that are out of the pitcher’s control. Doing so gives an earned ERA, one that can look at a pitcher’s true ability without luck involved. FIP is predictive of what a pitcher’s ERA should be, and often if a pitcher’s FIP is lower than their ERA, they should be expected to improve. If it’s higher, regression is likely. xFIP is a more accurate version of FIP, using a league average HR/FB instead of an individual’s HR/FB (as this stat can fluctuate randomly over a season). SIERA reads relatively the same as FIP/xFIP. Although it’s not as widely known, SIERA probably should be. That’s because it is consistently more accurate than FIP and xFIP. SIERA is, to put it simply, FIP on steroids. It takes into account a wide variety of factors, not just home runs, walks, strikeouts, and hit batsmen. For a quick comparison, Clayton Kershaw led the MLB in SIERA at 2.24, while also leading the majors in FIP and xFIP at 2.09 and 1.99. All of these values are relatively close, but if we’re nitpicking, the best fantasy players should be using SIERA (for more on these measures see Beyond ERA: DIPS, FIP, FIP & SIERA).

 

Notables: Carlos Carrasco: 3.63 ERA, 2.84 FIP, 2.66 xFIP, 2.74 SIERA… ERA is likely to decrease

                 Hector Santiago: 3.59 ERA, 4.77 FIP, 5.00 xFIP, 4.50 SIERA… ERA is likely to increase

 

ERA- / FIP- / xFIP-


While wRC+ is the best way to compare offensive performances from hitter to hitter, ERA-, FIP-, and xFIP- are the ideal ways to evaluate pitchers against each other. ERA- is essentially an improved version of ERA, as it is adjusted for league and park factors. FIP- and xFIP- work the same way. They read similarly to wRC+, as the league average is 100. The difference is that below 100 is above average, and vice-versa.