In 2003, a book by Michael Lewis changed the face of professional baseball. Previous to the book's publication, the average baseball fan had little appreciation for statistics beyond batting average, home runs, RBIs, and ERA. As controversial as the man it covered, Moneyball has clearly created a rift in baseball, both for fans and in front offices. There are two camps: those who believe that statistics are the way to figure out a player's value and those who believe that there are other, more intangible ways a player can benefit a team. Many teams have switched to a more statistically based approach, with GMs using WAR and VORP to create rosters or at the very least having a statistician on the team to help in personnel decisions.
Moneyball was extremely important because it introduced the average baseball fan to guys like Bill James and more importantly, the concept of sabermetrics. Quite simply, sabermetrics is the analysis of baseball using objective means. It breaks down how and why teams win ball games. Their simplified conclusion is this: runs obviously win games. There is really only one way to easily score runs and that is to have runners on base. Therefore, one of the most important ways to predict whether or not a team is going to score a lot of runs during a season is to look at a team's On Base Percentage.
However, this goes against the traditional wisdom belief that a team needs to put runners in scoring position any way possible, by hitting and running and sacrificing. The problem with this is that outs decrease the odds of scoring runs. The more people you have on base and the less outs you have give you the optimal ability to score runs. This is why people who believe in sabermetrics get on "RBI guys" like Jeff Francoeur because by "putting the ball in play" and only advancing a runner at the cost of an out actually over the course of a full season costs a team runs and therefore also costs the team wins (less runs = less wins).
The reason why things like batting average aren't looked at are because they are not an accurate way to predict scoring runs. It's broken down like this in Moneyball: a team with a 1.000 OBP will score an infinite amount of runs because there will always be someone on base and there is no way to create an out. A team with a 1.000 batting average may not score as many runs due to the fact that outs could still be created. A player might try to stretch a hypothetical single into a double or a guy could get thrown out at home. Batting average is a flawed metric for this very reason: it can be influenced by outside circumstances. More on that later.
Another important concept of sabermetrics is the idea of the "replacement player." This is not a player who is an average producer. A replacement level player is the expected level of production if a team needs to replace a starter with another player at minimal cost. A replacement level player hits below the average of the other players at his position but costs the team no runs defensively or on the basepaths. This is why you hear people say that David Wright is worth "five wins" above a replacement level player: with his production in the lineup, he will create and score enough runs to give the team five more wins compared to this nebulous replacement level player.
If you have a headache and need to take a break, you can do it at any time. It's okay. I'll still be here when you return.
Welcome back! Where was I? Oh right. Sabermetricians pride themselves on being able to objectively evaluate and predict certain objective truths about the game of baseball. For instance, sabermetrics can tell you who the best offensive player on the 2006 Mets was (it was Carlos Beltran) and through careful analysis can give someone a pretty good picture of whether or not a player can repeat that performance again. Just by looking at some numbers, a reader can pretty accurately predict what a player is capable of doing offensively.
For pitchers, it's even easier. When the average person measures the talent of a pitcher, they usually point to wins and losses or ERA. This is inaccurate because each of these can be influenced by outside circumstances, like batting average mentioned earlier. This is even more obvious for a pitcher as he can be affected by bad defense (players with poor range cannot make it to certain balls and could make a good pitcher look bad. On the flip side, a bad pitcher with a great defense could make him look good because they're making outs that probably shouldn't get made). A pitcher's win/loss is inaccurate because a pitcher could give up one run and still lose the game because the offense did nothing. Many people claim that pitchers "get the run support they deserve" which is literally impossible and is a buzzword by cranky old men who think that DIPS go on chips.
If you all ready understand sabermetrics you're probably nodding your head and agreeing with everything I'm saying. If you don't follow, I know what you're thinking right now. It probably is something to the effect of: "This nerd is trying to preach to us about them goshdang statistics! They're ruining baseball I tells ya! Maybe you should leave your parents' basement once in a while and get some sun!" Sabermetrics are not in conflict with traditional wisdom. It just helps compliment and back up "gut feelings." It's essentially the scientific method for baseball and I hear very little complains about that.
Next article I'll talk about other concepts that sabermetrics talk about, why it further doesn't conflict with traditional wisdom, teams that employ sabermetrics and their successes and failures. Then I'll look into the 2010 Mets and explain what their strengths and weaknesses are going to be.