facebooktwittergoogle_plusreddittumblrmail

Image Baseball is a game that lends itself to statistical collection and analysis more than any other sports.  Each pitch creates a new potential outcome to be studied.  There are lefty-righty splits, lefty-lefty splits, righty-righty splits, and even righty-lefty splits to dissect.  Inroads are being made to study defense and baserunning to determine how a player should have performed.  And with the most games played per season of the four major sports, the stats accrue and eliminate variance over the course of a season.

In recent years, sabermetricians (i.e. Moneyball) have parsed the statistics down to the finest grains of sand.  In my opinion they have done so too much in some cases.  However, there are three advanced stats that I would like to introduce you to in this article:

WAR (Wins Above Replacement) — This stat is entering mainstream discussion with each passing year.  WAR is a not an end-all-be-all stat; it is meant to be a conversation starter and not the definitive statement of a player. WAR attempts to encompass a player’s offensive and defensive contributions.  For pitchers it is innings based and FIP-based (more on FIP next).  WAR accounts for a player’s position, as it gives more baseline to shortstops and catchers over corner outfielders and first basemen.

The theory is “What if Player X was replaced by a run-of-the-mill Triple A player?  What is the difference in performance?”  An average major league player produces 2.0 WAR/year.  Obviously for bench players and relievers the standard is lower and typically 1.0 WAR is considered good for those guys.  A WAR of 5.0 or greater is considered an all-star with a WAR of 8.0 or greater considered an MVP candidate.

FIP (Fielding Independent Pitching) — FIP is what I call a “ground truthing” stat.  I like to use it to see if a pitcher is due for a regression to the mean or if he can be considered to improve on his presently poor stats.  FIP accounts for things that only the pitcher can control, without having to rely on his defense — home runs allowed, strikeouts, and walks.  It is scaled to resemble Earned Run Average by the following formula:

FIP = (13*HR allowed) + (3* Walks allowed) – (2* Strikeouts) all divided by the Innings Pitched. This figure is then added (or subtracted) from a constant of 3.20

Let’s say a pitcher has a 2.50 ERA.  Fantastic year!  But wait….this pitcher has a high walk total and may be getting bailed out by his good defense behind him, as he has a FIP of 3.90.  This would tell me that our hypothetical pitcher may be due for a regression to the mean.  The corollary is true, too.  Perhaps a pitcher has a defense with poor range behind him and his ERA is 3.90, but his FIP is 2.50.  This would tell me that as long as the pitcher keeps his K’s high and BB’s low, his season may turn around.

BABIP (Batting Average Balls in Play) — BABIP is the hitters’ version of a “ground truthing” stat.  BABIP accounts for how a player is hitting based on balls in the play of field, so home runs and strikeouts are removed.  The formula is:

BABIP = (H – HR) / (AB – K – HR + SF), where SF are sacrifice flies.

BABIP is scaled to look like a batting average.  A typical BABIP range for hitters is .290 to .310.  So if a hitter is only batting .245 with a BABIP of .260, you can expect his performance to rise over time as his BABIP stabilizes.  The corollary to this is looking at a player with a batting average of .345, but his BABIP is an unsustainable .410, you can expect his performance to drop off.

However, you can’t just look at BABIP and say if it is not around .300 then the player will rise/drop.  You also have to look at the BABIP’s in the player’s history.  A player may have submitted BABIP’s of .330 as his baseline, indicating that he beats out infield hits and makes hard contact, so he may be able to sustain higher BABIP’s than a typical player.  A good example of this is Starling Marte.  Marte consistently posted BABIP’s of .340 to .380 in the minors, so it’s not outrageous to think that he could sustain a .330 to .340 BABIP in the majors due to his speed and hard contact ability.

There are plenty of other stats out there, some are good and some still need some work or seem too convenient, but these three are ones that you may see me reference throughout the 2013 season.

 

Kevin Creagh

Steel City Buzz Pirate Blogger

facebooktwittergoogle_plusreddittumblrmail