The Cubs lost both ends of a doubleheader yesterday to the lowly Pittsburgh Pirates.  My first reaction was to get upset, but does it really matter?  The Cubs have been eliminated from playoff contention, so the games really don’t matter.  Plus, it’s an opportunity to play some people who haven’t played much and try some different lineups.  The rest of the year is almost like a pre-Spring Training.

Instead of talking about yesterday’s games, I’d like to talk about baseball statistics.  Some people love them, some people hate them, and yet others simply don’t understand them. 

There was a time not too very long ago when everyone looked at the same statistics and agreed on what was good and what was bad.  Batting average was a key indicator of a player’s hitting ability, and homeruns and RBI were also important.  Today, baseball statistics have almost as many acronyms as the Federal government.  Talk to a connoisseur of baseball statistics and you’ll likely hear him say things like WARP, VORP, BABIP, UZR/150, etc.  But the big kahuna of baseball statistics today is OBP; on-base percentage.

On-base percentage is preferred over batting average because batting average does not take into consideration how often a batter draws a walk .  Proponents of OBP point out that the ability to get on base via a walk is incredibly important and should be included in the sport’s “key” statistic.

As an example for the uninitiated, it has long been accepted that a batter who gets a hit three times out of every ten times at bat is a good hitter.  This is still the case, but it is now recognized that someone who hits .275 (for example) may be more valuable to their team if they draw enough walks.  The .300 hitter may never take a walk, meaning that their OBP would also be .300, but the .275 hitter, assuming he draws a lot of walks, may have an OBP of .350 or higher.  In other words, the .275 hitter with the .350 OBP is more valuable to his team than the .300 hitter with the .300 OBP.

Even though OBP is the preferred statistic of the stathead class, it is not perfect.  Its downfall is that it counts all of the various ways a batter can reach base equally.  In other words, a walk is as valuable as a homerun.  Obviously, in the actual game, this is not true.  So other statistics come into play.  For instance, slugging percentage (SLG) measures a hitters total bases divided by their at-bats.  But unlike OBP, SLG does not measure a players propensity to reach base via a walk.  So OPS was created. 

OPS is on-base plus slugging and is a combination of OBP and SLG.  The two statistics are simply added to come up with a player’s OPS.  Personally, I’ve never liked the idea of taking two averages and adding them together to come up with another average.  I mean, think about it.  OBP measues something different than OPS using different variables.  How can you add up two averages that measure two different things by using two two different sets of variables and come up with something meaningful?  It just doesn’t seem right.  Regardless, no one asked me, so OPS stands  as an important “go to” stat.

The statistic elite were unsatisfied with OPS, so they came up with OPS+.  OPS+ is exactly the same as OPS, except it is adjusted for the ballpark and league in which the stats were achieved.  So a player that hit 30 homeruns, all in Arlington Stadium in Texas, would have a lower OPS+ than a hitter who hit 30 homeruns, all in Petco Park in San Diego.  Each player hit the same number of homeruns, but the player who hit his in a ballpark where it is much more difficult to hit homeruns (like Petco) would be rewarded for his more difficult feat.

The few statistics I’ve covered here just barely scratch the surface.  Wouldn’t it be nice (especially for those of us who are math-challenged) if there was one statistic that covered it all?  A statistic that everyone could understand and agree on?  My new favorite sports writer, Joe Posnanski, feels the same way.

I love this idea of a stat we would call “Production.” And I think it should be a stat that simply totals up a players’ production — not a percentage, not an average, not a fraction at all. Just total up everything.

Sounds good, but how would it work?  As it turns out, there’s a guy named Tom Tango who studies baseball statistics and has determined the weighted value of walks, hits, etc.  It assumes that the most important thing in baseball is scoring runs, so each type of hit (single, double, triple, homerun) and walk (intentional, unintentional) was examined in light of how likely it was to lead to a run. 

Tango determined that a single is worth 1 point, a double 1.6 points, a triple 2.2 points, and a homerun is worth 3 points.  A hit-by-pitch and a walk are both worth .7 points while an intentional walk is worth .4 points.  A stolen base is worth .4 points, but a caught stealing is worth -.4 points.  Posnanski gave the “Production” statistic (which he originally called “hitting average”) a test run and found that it correlated more closely to scoring runs than any other stat, including OBP, SLG, OPS, OPS+, and much better than batting average.

I like this idea a lot.  I’d like to be able to look at one statistic and know how that player’s effort contributes to his team scoring runs (the point of the game).  The “Production” stat does that, and it does it better than the other mainstream stats that are so popular.

Posnanski goes into much more detail and even includes the negative side of the equation.  Rather than cover that here, I’d rather just keep it simple.  The “Production” stat does what I want it to do.

In part 2, I’m going to look at who the best and worst players in baseball are using the “Production” statistic, and I’m going to apply the formula to several of the Cubs.