Sabermetrics

            When I write my blogs I tend to use a lot of stats that many people aren’t accustomed to seeing.  BABIP, FIP, xFIP, K/9, OPS+, UZR and WAR are examples of stats called sabermetrics or advanced stats.  The idea of sabermetrics is to take what a player is doing statistically and gain insight on the player’s tendencies.  These can range form seeing what a player likes to swing at and where he likes to swing the most using a Swing % in and out of the zone or seeing if a pitcher is getting a little lucky do to having a stronger defense than another pitcher using FIP and xFIP.  Or simply looking at an existing stat like OBP (On Base Percentage) and giving it more importance by using wOBA or weighted On Base Average to see how a player does on getting on base among other things.  In this blog I want to go over some of the saber stats I use when looking at players and also to help people who are lost when reading the blog and I mention a stat.

            The way I’ve decided to work this is by showing how to calculate the stat and then give a description on how it’s relevant.  I’ll also separate them into pitching and hitting stats that way it will be easier to know which stat pertains to which aspect of the game.  Yes it is true that many of the stats actually work for both (as an example BABIP has a hitting and pitching calculation) but unless I say it twice it will only apply to the aspect I mention it under.  So here we go, lets start at the hitting stats first.

Hitting:

1)   BABIP or Batting Average on Balls in Play- Hits-Homeruns/At Bats-Strike outs-Walks-Homeruns.

Basically this is a stat that tries to gauge the “luck” factor for hitters and literally translates out into “What is the players batting average when he puts the ball in play.”  As an example lets use Albert Pujols and Mike Trout; lets say both hit a hard grounder into the gap between 3^rd base and Shortstop.  Trout runs hard and beats a tough throw and his BABIP goes up but on that same play Pujols is thrown out meaning his BABIP will go down.  A lot of variables can be in play and that’s what BABIP tries to show us.

2)   OPS or On Base Plus Slugging- OBP+SLG.  This is a conflicting stat and also a misleading one.  It combines two important stats that have very good information but they aren’t equal stats.  Most consider OBP to be more important than SLG and many good OBP don’t have a high SLG so it makes the results iffy.  There are better stats to use but this is a good starting point.  Another version of this stat that is starting to become a little more popular is OPS+, pretty much it shows the percentage above or below the average OPS a player is.  Example if a player is a 90 OPS+ he his 10% below average, 100 being the baseline.

3)   HR/FB rate or Homerun to Fly Ball rate- HR/FB.  Pretty simple to explain, basically its how often a player hits the ball in the air does it go for a Homerun.  It’s not a luck stat but it is a stat that can act like one, if a player is hitting say a Homerun every 5 fly balls he’s hitting about a Homerun about 20% of the time which isn’t sustainable and he will eventually average out.

4)   wOBA or weighted On-Base Average- (0.691xuBB+.722xHBP+.884x1B+1.257x2B+1.593x3B+2.058xHR)/(AB+BB–IBB+SF+HBP).  That’s a very large equation that pretty much says not all players are equal.  This is the catch-all offensive stat that says the value of a hitter and takes all the 3 stats we call counting stats (AVG, OBP, SLG) and combines them into one stat to show the value of the hitter.  When I say that every player isn’t equal it is more or less talking about how the 3 counting stats work which all assume that the hitters are equal or the things they do are equal; a 2B is not worth double a 1B.  wOBA doesn’t just take the 3 stats into account but every aspect of the hitter and calculates for accuracy and scope more than numbers.  The numbers used to calculate the stat changed on a yearly basis.

5)   ISO or Isolated Power- ((2B) + (2x3B) + (3xHR))/AB.  Pretty much means Extra Base Hits / At Bats; like I said in OPS there was a better stat to gauge a hitters power numbers and here it is.  It only looks at when a hitter gets past a single.  One thing about this stat is it needs lots of data to make a good calculation, as in almost half a season before you can start looking into it otherwise the sample size is just not small.

6)   Swing% or Swing Rate.  A stat that is good on its own merits but more powerful when combined with BB% K% and others to get a good idea at what the hitter is doing when he swings.  As the name suggests it shows how often a batter is swinging, there are also stats to show how often a hitter is swinging in the strike zone (Z-Swing%) and outside the strike zone (O-Swing%).  Using all 3 shows the tendencies of hitters and how often the pitcher can get them to swing at pitches.  A useful tool for scouts and pitching coaches.

These are the main hitting stats that I look when I look at a team or player (ISO is better for players then teams).  So lets take a look at some of the pitching saber stats.

1)   ERA or Earned Runs Average- (ER/Innings Pitched)*9.  The best way to look at this stat is pretty much what it looks like, how many runs a player would give up in a 9-inning game.  Or just the average of runs he would be giving up in 9 innings overall.  Not a good stat to look for future success but it’s a nice way to just look at a player and say, “oh ok that’s how he’s pitching so far.”  For reference an average ERA is about 4.00.

2)   WHIP or Walks and Hits per Inning Pitched- BB+H/Innings Pitched.  Much like ERA this stat is exactly as it stats and shows how often a pitcher is letting a runner on base per inning pitched, and much like ERA it’s not the best evaluation tool.  Pitchers have very little control over their BABIP (yes pitchers have one too) so the WHIP could be misleading for good or ill.  A average WHIP is about 1.32.

3)   Quality Starts- No formula for this one just a simple counting stat and just an ok one at that IMO.  To get a Quality Start the pitcher must go at least 6 innings and give up no more than 3 runs.  The reason I don’t like this stat simply comes down to that baseline, if a pitcher gives up 3 runs in 6 innings he has an ERA of 4.50.  Yes technically he’s keeping the team in the game but that’s still unimpressive.  Also I should mention that this stat was created by Scott Boras to help sell his players…not I’m not kidding this stat was invented to get pitchers more money by making them sound better.  Not a terrible stat but not my favorite to look at.

4)   FIP or Fielding Independent Pitching- ((13*HR)+(3*(BB+HBP))-(2*K))/IP + constant).  This stat is what a pitchers ERA should look like if the balls in play and timing are league average.  To put it simply, it’s a stat that makes the defense league average and see how much the defense he currently has aids him and his ERA.  I like this stat since it shows a more accurate look at the pitcher at see if he’s getting lucky or not.  Example: if a pitchers ERA is 2.30 and his FIP is 4.60 this means he’s getting very lucky and that’s going to average out at some point, this works vise versa were a pitchers ERA is 4.60 and his FIP is 2.30 meaning he’s unlucky and his defense is hurting him a lot.  An average FIP should be around 4.00.  There is another stat called xFIP that calculates almost identically to this one but uses HR/FB rate which I don’t like.  It tends to change too much since HR/FB rates can drop and rise to inconsistently.

Well that’s most of the stats I look at but not nearly all of them, but this is getting on in length so maybe another day I’ll look into more of them and explain them as well.  Also there are many stats that I personally haven’t gotten the hang of yet so I want to learn them before I explain them.