Welcome to the first article of Staturday where we breakdown the different statistics in baseball.
This article will just serve as a primer to make sure we are all familiar with the different statistics in the game before we dive into the heavier statistics like wRC+, xFIP, or WAR. So let's start with some basic offense statistics.
Hitting:
If you were to go to Fan Graphs and search for this year's batting leaders, you would see a heading like this:
Hopefully some of these categories in the first block are self explanatory like PA (plate appearances) and RBI (runs batted in). In the second block we have BB%, K%, ISO, and BABIP. We will break these down in just a bit, but first let's look at AVG, OBP, and SLG.
AVG:
AVG stands for Average and it is just a simple calculation taking a player's total number of hits and dividinng them by the number of at-bats (AB) he had (H/AB). There is a difference between AB and PA. A plate appearance is anytime a player steps up to the plate. This includes anytime he gets a hit, an out, a walk, etc. At bats only includes the time a player gets a hit or records an out that is not sacrificial (bunting/fly out).
Example: Tim Anderson led baseball last year in batting average. He had 167 hits in 498 ABs (518 PA - (15 walks (BB) + 3 hit by pitches (HBP) + 2 sacrifice flys (SF)) = 498 AB).
OBP:
On Base Percentage calculates how often a player is on base. It is similarly calculated like AVG. OBP's equation is (H+BB+HBP)/(AB+BB+HBP+SF) . Mike Trout led baseball last year with an OBP of 0.438. This means that we would get on base 43.8% of the time he stepped into the batter's box.
SLG:
Slugging tells us how many bases a player averages per AB. In baseball, a single is worth 1 base, a double is 2, a triple is 3, and a home run is 4 bases. We use the same calculation as average but instead of just adding up all of the hits, we now break it down by total number of bases.
Using Mike Trout as an example again, he had 63 singles, 27 doubles, 2 triples, and 45 home runs. So (63*1 + 27*2 + 2*3 + 45*4)/470 = 0.645 bases per at bat.
Mike Trout and Tim Anderson had similar number of AB (470 to 498). While Anderson had a great batting average, Mike Trout averaged almost 0.150 bases per AB more than Anderson (0.645 to 0.508). This is why statistics and the more advanced statistics can be so useful when evaluating players and comparing them to one another.
Let's move back to that second group of statistics.
BB% and K%:
Walk Percentage and Strikeout Percentage are calculated just like AVG. You take the total number of walks or strikeouts and divide them by the number of plate appearances (not AB).
ISO:
Isolated Power tells us a batter's raw power. There are many different ways of calculating it but the most basic and commonly used way is simple taking SLG - AVG. Therefore if a player only ever hit singles, they would have an ISO of 0.
BABIP:
Batting Average on Balls in Play tells us how often a batter gets a hit when he puts a ball in play. BABIP is calculated as (H-HR)/(AB-K-HR+SF). This stat can fluctuate greatly from season to season and can let you know if a player has been considered lucky or unlucky. Comparing a player's BABIP from year to year can help you tell. A high BABIP could infer the player was lucky, but if we consistently has a high BABIP (e.x. around 0.370) then it may tell you that he is fast and beats out a lot of infield hits.
BABIP is a good example of how just looking at one stat will not tell you the entire story. It is good to look at a number of stats to see how a player truly performed that season. This is true for any stat whether you are focused on offense, defense, or pitching.
The remaining stats that we have not talked about will get their own individual posts later in the offseason.
Pitching:
Taking a look at Fan Graphs pitching leader board we see this:
Much like the hitting section, we will skip the first block of stats but this time we will start with the second block.
K/9, BB/9, and HR/9:
Strikeouts, walks and home runs per 9-innings is much like BB% or K% except they tell us how many "units" will average in a 9-inning sample. Let's look at strikeouts per 9-innings. To calculate it, you take the total number of strikeouts a pitcher got and divide it by the number of innings pitched. Then multiply that value by 9.
Example: In 2019, Gerrit Cole threw 212.1 innings while striking out 326 batters, walking 48 batters, and giving up 29 home runs. K/9 = (326/212.1)*9 = 13.83, BB/9 = (48/212.1)*9 = 2.03, HR/9 = (29/212.1)*9 = 1.23
BABIP:
BABIP for pitchers is calculated the exact same way as it is for hitters and can fluctuate just the same as a hitter's BABIP from year-to-year.
LOB%:
Left On Base percentage is a percentage of a pitcher’s runners that they leave on base (do not score) over the season.
GB%:
Ground Ball Percentage records what percentage of batted balls a pitcher gives up on the ground. A high GB% means that a pitcher induces more ground balls than a pitcher with a lower percentage. Ground balls are better than line drives or fly balls because they generally do less damage (fly balls can be home runs while ground balls are usually singles).
HR/FB:
Home Run to Fly Ball Rate is exactly what it sounds like; how many fly balls turn into home runs. A lower rate means a pitcher does a good job of keeping the ball in the park.
ERA:
Earned Run Average is one of the oldest stats in baseball. It calculates how many runs a pitcher is expected to give up over 9-innings pitched and is calculated just the #/9 group of stats.
Example: Gerrit Cole gave up 59 earned runs in 2019. (59/212.1)*9 = 2.50 ERA
We will explore FIP, xFIP, WAR and other pitching stats later in the offseason.
Defense:
Taking a look at Fan Graphs fielding leader board we see this:
There is a lot to unpack here but fortunately for now, most of it will be a later topic.
PO:
Put Outs are how many outs a player makes. If an outfielder catches a fly ball that is considered a Put Out. The same goes as a first basemen receiving a throw to record an out at first base. Catcher, first basemen, and outfielders usually record the most PO as they are the last ones to touch the ball.
A:
Assists are made by the player who helped assist with the out. An example being the shortstop who throws to first.
It should be noted that PO and A numbers for pitchers are only on fielding opportunities. A pitcher does not record an assist for striking a hitter out.
E:
Errors are plays that a player should make but fails to. These are determined by the score keeper and therefore are frowned upon in the advanced statistic community since there is no standard for what is or is not an error.
FP:
Fielding Percentage is the rate at which a fielder makes the play. It is calculated by adding up a players total number of opportunities, subtracting the errors from that total, and then dividing by the number of opportunities. (PO + A - E)/(PO+A) = FP
Example: Anthony Rizzo made 1140 PO and 123 A in 2019. He also made 5 errors. Using these values (1140+123-5)/(1140+123) = .996 FP
So this will be our launching point for the rest of the offseason. Every Saturday we will look at a new statistic and break it down. By Opening Day 2020, you will be equipped to break down a player's season and see just how well they compare to the rest of the baseball world.