An Introduction to Sabermetrics

The majority of baseball fans do not understand baseball statistics.  Yes, they enjoy home runs and love the idea of their favorite pitcher throwing a no hitter. What would their response be if you asked any regular fan what on base percentage is? Or better yet do they know how to calculate it? I would give a 50/50 shot of them knowing that simple statistic. My goal is to broaden your horizons when it comes to in depth baseball statistics aka “Sabermetrics”.  Also, if you actually do not know what on base percentage is then I would start with simple statistics then come back and read my article.

The word “Sabermetrics” is a term that was created by the “godfather” himself, Bill James.  Bill James was the pioneer of the sabermetric revolution and even though the idea of analyzing statistical data has been around for centuries the real “boom” didn’t occur until James started writing his annual Baseball Abstracts.  These books consisted of pages and pages of in depth statistics. Today, James is the Senior Advisor on Baseball Operations for the Boston Red Sox.  He also has continued his abstracts but in the form of Bill James Handbook with the help of Baseball Info Solutions.

Now that you have a little background information about where sabermetrics came from, let’s dive into some of examples:

Batting Average on Balls in Play (BABIP) – This statistic is unlike many due to the fact that it can be used for both pitchers and hitters.  This stat is very similar to batting average (or batting average against for pitchers).  The difference is that is excludes all plays that are not in play (Home runs and strikeouts). A pitchers BABIP is regularly insufficient and functions mostly on their fielding defense and a lot of luck.  BABIP for hitters is detrimental to proving how well a hitter can place a ball. Speed also affects this metric, due to the fact that speed helps get on base but does not help with home runs so speed gets a boost in BABIP.  The best “pure” hitters will be tops in BABIP.

Top 5 BABIP for 2015

1. Odubel Herrera     PHI      .387

2. Miguel Cabrera     DET     .384

3. Dee Gordon            MIA     .383

4. Paul GoldschmidtARI      .382

5. Kris Bryant             CHC     .378

Outside of Herrera, who is not a household name, you got some of the best hitters in baseball right at the top of the BABIP rankings. Herrera is the outlier that proves how important speed is when it comes to BABIP.

How to calculate BABIP:

BABIP = (Hits – Home Runs) / (At Bats – Strikeouts – Home Runs + Sacrifices)

Walk Percentage and Strike out Percentage (BB% and K%) – These two statistics are as simple as stats can be. So for example BB% is the percentage at which a batter has walked relative to the amount of plate appearances they had. Joey Votto led the league with 143 walks in 695 plate appearances.  That calculates to a ridiculous 20.6 BB%. Votto walked on over 20% of his plate appearances. Walks lead to getting on base, getting on base leads to runs, and runs lead to more wins. Now on the other side of the totem pole there is K%.  The metric works the same as BB% as it is simply the percentage a hitter strike outs relative to the amount of plate appearances they had.  Chris Davis led the MLB with a sickening 208 strikeouts in 670 plate appearances.  This led to an astounding 31 K%, so Davis struck out on 31 percent of his plate appearances. Strikeouts are essentially “free” outs considering no good comes from them.  Unless there is a rare case of a drop third strike.  No runners will move and your team will be one out closer to ending the inning. Chris Davis and other big power hitters will always have high K% due to their free-swinging ways. Though in the new MLB where home runs are at a premium, sluggers such as Davis, Mark Reynolds, Chris Carter, among others will always have a place even though they give outs up like candy. 

How to calculate BB% and K%:

BB% = Walks / Plate appearances

K% = Strikeouts / Plate Appearances

Wins Above Replacement (WAR) -

WAR may be the most important stat that has come out of the sabermetrics revolution. This is an attempt to combine all facets of the game to truly compare players worth to the team.  Calculating WAR is unrealistic to calculate without a computer program due to the longevity of the equation. There is a simple equation that you can use to calculate WAR but by no means is it “simple”.

WAR = (Batting Runs + Base Running Runs +Fielding Runs + Positional Adjustment + League Adjustment +Replacement Runs) / (Runs Per Win)

(Good Luck)

This metric can be used for Hitters and Pitchers.  It is a statistic that simply proves each players importance to their respective teams. If you are interested in looking up your favorite players WAR you can go to FanGraphs or Baseball-reference both use similar frame works but use different models.  I did a little research into how different each form is and I didn’t find a big difference of WAR between their numbers.  A difference of 1 is the very most and is not a huge difference at hindsight. For example, a difference between 5 and 6 is still a top tier player in the league and will be all-star worthy with a consideration of MVP.


0-1 WAR

Role Player

1-2 WAR

Solid Starter

2-3 WAR

Good Player

3-4 WAR


4-5 WAR


5-6 WAR


6+ WAR

*This chart is from the FanGraphs website. (

 To get a better idea of what you are dealing with when looking into WAR, above is a chart to understand what each number means.  Players who had the tops in WAR were Bryce Harper (9.5), Mike Trout (9), and Josh Donaldson (8.7).  Harper and Donaldson ended up winning their leagues MVP’s. For pitchers, Kershaw (8.6), Arrieta (7.3), David Price and Max Sherzer (6.4), led the way in pitchers WAR. Arrieta and Houston starter Dallas Kuechel subsequently won their respective leagues Cy Young awards. Even though Kuechel was not in the top 3 in WAR but was no slouch with a 6.1 WAR and a league leading 20 wins. Just with these small sample sizes you can see how well WAR differentiates MVP type caliber players from the average or below average players.  It is a very well put together stat that will only be used more and more in the future, get used to seeing it now before its too late!

Fielding Independent Pitching (FIP) –

This statistic estimates how a well a pitchers performance over a complete season without their performance of their defense or any other outcomes that do not involve the pitcher himself. This statistic is a better understand of a pitchers ERA because ERA can be lucky and includes outcomes that a pitcher has nothing to do with. For example, when calculating WAR for a pitcher analysts use FIP and not ERA.  Figuring out FIP is impossible without using a computer program. The equation is long and thorough.

FIP = ((13*HR)+(3*(BB+HBP))-(2*K))/IP + constant

Figuring out the constant for FIP is the most difficult to figure out but is the same for every pitcher. Kershaw lead all pitchers with a 1.99 FIP, second was Jake Arrieta with a 2.35 FIP, and third was Garrett Cole with a 2.66.

Baseball is not like any other and that is how I fell in love with it.  There is so much incredible detail that is involved and an incredible amount of analysis that is needed to completely understand the game.  These sabermetrics have been injected into every clubhouse and every true fan should have an idea of the ones that are being used more than others.  My goal is not for you to figure out these metrics but to better understand where the numbers come from and what they mean relative to other players in the league. Any questions or comments just find me on twitter @tLLoyD199 or @TheHerdReport.