Stats Glossary

As you know, we use some non-traditional statistics on this site from time to time.  I wouldn't call this a stat-oriented blog, so I'm not going to make this more complicated than it needs to be.  However, we do find new metrics useful from time to time, especially when trying to project performance for the future.  Traditional stats like average, ERA, RBI, etc. all tell us something about the game, but they are more results-oriented and don't have the same predictive value.

We'll start with stats that can be used for both pitchers and position players.

WAR: Stands for Wins Above Replacement.  It's an all-encompassing number for statistics that a player can control.  For position players that includes hitting, defense, and baserunning.  It attempts to measure how much wins that player provides over some every day joe AAA guy.  That player is considered to be "replacement level".  As an example, Blake DeWitt qualified as a replacement level player last year and not surprisingly has been replaced by an average AAA player (Adrian Cardenas) on the roster.  To give you an example of how WAR numbers break down, here's a quick reference chart...

Below 0: This is Koyie Hill level. It's a substandard MLB player who should be replaced.  He costs your team runs, and ultimately wins.

0: A replacement level player. As noted above, Blake DeWitt is an example. Neither hurts nor helps your team.

1: A solid reserve level player.  Reed Johnson is a good example.  For pitchers, it's a good bullpen arm.  For reference, both Kerry Wood and Jeff Samardzija were between 0 and 1, which is where most relievers are.

2: The minimum of what you want out of your starter. Marlon Byrd and Darwin Barney were around this level, largely on the strength of their defense. Most of the Cubs starters fell into the 2-3 range in 2011.  Others include Carlos Pena and Geovanny Soto.  Remember that position is important.  Pena was much more productive than Barney, but the league average production level at 1B is a lot higher than it is at 2B.

3: A good starter.  Castro was at 3.4 last season which makes him a pretty good player, but not a star.  With better defense, he would have easily been a 4 level player.   When we're talking about a starting pitcher, Ryan Dempster fits.  He's been between 2.8 and 3.7 the last 3 years. It would also be the WAR of a top-notch reliever. Sean Marshall was at 2.8 last year and Carlos Marmol as at 3.0 in 2010.

4: A very good starter: Cubs didn't have a player at this level.  Aramis Ramirez at 3.6 was the closest and that was due purely to his offensive production.  Had he been even an average defensive player, he would have been at 4 or above

5: A great player.  The Cubs didn't have a position player at this level.  The Cubs only player in this category was SP Matt Garza.

6-7: A star player.  The Cubs, obviously, had nobody at this level.

7+: MVP quality player. Matt Kemp was at 8.7

BABIP: Stands for Batting Average of Balls In Play.  To some degree, this stat measures "luck" on batted balls.  If your BABIP is high, it means a lot of batted balls fell for hits.  In other words, more seeing eye groundballs and bloop hits and less line drives right at ‘em.  In Yogi Berra’s words, more “hitting them where they ain’t”.  A higher number can mean less luck for a pitcher (and more luck for a hitter).  The league average for this statistic is about .300.  Note that it isn't allluck and BABIP varies from player to player.  Faster players tend to have higher BABIPs because they'll beat out a few extra ground balls.  Some players make hard contact more consistently and that can certainly have an effect on how many balls get past the defense.

Hitters Only:

First off, one thing you'll often see me use when describing a player is a "slash" line.  It looks something like this: .305/.367/.489.

The first number is batting average, the second number is OBP, and the third number is slugging percentage.

Now, we'll look at 3 different newer metrics using the same 6 players we used in the previous examples

ISO:  This is a percentage that tries to isolate the pure power component from a players slugging percentage.  It is simply slugging percentage minus batting average.  Here's how it breaks down using 2011 Cubs players to give you an idea.

Carlos Pena .237

Aramis Ramirez .204

Geovanny Soto .183

Starlin Castro .125

Marlon Byrd .119

Darwin Barney .078

Note: It doesn't mean Pena has more power than Ramirez, but more of his slugging percentage is derived from extra base hits rather than batting average.  Anything lower than .100 is basically a singles hitter.

wOBA:  wOBA is a nice little stat that combines both slugging ability and OBP and weighs the two more evenly than OPS (OBP + Slugging).  It's calculated so that it reads like OBP numbers.  So .330- .340 is about your average offensive player, while .400 would be superstar quality on offense (i.e. Matt Kemp was at .419).  If you're below .300,  you're probably a liability on offense.  Some 2011 Cubs for reference...

Aramis Ramirez .371

Carlos Pena .354

Starlin Castro .338

Geovanny Soto/Marlon Byrd  .315 (ish)

Darwin Barney: .296

RC+:  Stands for Runs Created and is like wOBA but measures total offensive value on a different scale: .100 is average, 125 is a very good offensive player, 150 is excellent, and 75 is a liability on offense.  Alfonso Soriano was the closest to an overall average player on the Cubs with 99, but considering he plays an offense-heavy position, that's not good enough.

Aramis Ramirez 133

Carlos Pena 119

Starlin Castro 109

Marlon Byrd/Geovanny Soto 93

Darwin Barney 79

Pitchers Only:  Again, we'll compare 6 2011 Cubs.  In this case, we'll compare the 6 most likely starters

FIP: Stands for Fielding Independent Pitching.  This number will look like an ERA but only factors in what a pitcher can control such as strikeouts, walks, and HR rate.  The attempt is to measure how a pitcher would fair without the influence of the defense behind him.  Pitchers with lower FIPs as compared to their ERAs tend to improve with better defense.

Matt Garza 2.95

Ryan Dempster 3.91

Paul Maholm 3.78

Chris Volstad 4.32

Travis Wood 4.06

Randy Wells 5.11

xFIP: The same as FIP except that it normalizes HR rate to the league average since sometimes HR rate can involve both good and bad luck.  Both FIP and xFIP are better predictors for future success than ERA.

Matt Garza 3.19

Ryan Dempster 3.70

Paul Maholm 4.03

Chris Volstad 3.64

Travis Wood 4.61

Randy Wells 4.45

HR/FB%: This measures the ratio of home runs to fly balls.  The assumption is that you can control the amount of flyballs you give up, but not necessarily the amount that leave the ballpark.  Generally anything over 10% is considered unlucky.  Volstad, for example, was at 15.5%, while Travis Wood had much better luck at 6.7%.

GB/FB ratio:  Ideally, you'd like a guy who throws more ground balls than flyballs, especially on days when the wind is blowing out.  You also need a good defensive infield if you want to field a staff of ground ball pitchers.  If your infield defense is bad and the wind is blowing in, high fly ball rates aren't necessarily a bad thing.  Anything over 1.5 is a pretty good groundball pitcher, anything over 2 is very good, and less than 1 is basically a flyball pitcher.  If you're 3 or over than you are in the Derek Lowe category of sinkerballers.  Cubs don't have that kind of groundball pitcher, but they've picked up a couple of pretty good GB pitchers this offseason.

Chris Volstad (1.89)

Paul Maholm (1.77)

Matt Garza (1.42)

Ryan Dempster (1.25)

Randy Wells (1.12)

Travis Wood (o.71)


You won't find me using fielding percentage which doesn't emphasize range or arm.  If I do talk about defense, we'll go with UZR/150, which isn't perfect but it does take more factors into account (i.e. errors, range, arm strength).  The "150" extrapolates the number out to 150 games.

Think of it this way:  Who's more valuable to your team? A guy who can make 100 more plays because of his range and arm, but commits 10 more errors or the guy who can make less plays but makes no errors?  Basically, the first guy helps you create 90 more outs on defense and, theoretically saves you runs over the course of a season.  The number in UZR attempts to mesure the runs a defender saves, so if his UZR/150 is 0, then he is an average defender.  The player neither saved you nor cost you runs with his defense. Here are the UZR's for 5 of the 6 Cubs we talked about in the hitting section (no current UZR rating for catcher)

Carlos Pena:  (+0.9)

Aramis Ramirez . (-10.9)

Starlin Castro  (-8.8)

Marlon Byrd  (+3.0)

Darwin Barney (+5.8)

Keep in mind that with UZR, there are large fluctuations and the larger the sample size the better, so it usually works best if you can go back 2-3 years.


So this is mostly what I'll use and I'll consider this a permanent work in progress.  I'll add more if I use them or subtract some if I don't find them useful anymore or something better comes along.  We'll also be changing the examples from year to year.