Thanks, Oxtung and others for some explanation of the stats. Hoping others will add a little more to the understanding.

I'm not sure if you're asking for this but if you want explanations of the stats that are tossed around on this site frequently they are available, for the most part, on

Fangraphs website. At the top of that page there are tabs for Offensive stats, defensive stats, pitching stats, WAR, etc....

If you're just looking for a quick overview of the statistics presented in the article or in this thread so far I can give you my understanding of them (feel free to skip this post if you feel you already understand these statistics).

**ERA** is obviously the most basic and well known of the statistics available for pitchers.

**ERA+ **and

**ERA- **are essentially just ERA that has been changed into an easier to read/use format. So an average ERA is always going to be 100 no matter what year you're looking at. ERA+ comes from baseball-reference.com and better pitchers are given values >100. ERA- comes from fangraphs.com and for this statistic better pitchers are given values <100. Otherwise they are very similar statistics with some small nuances.

However ERA is very dependent on factors outside of a pitchers control. The ballpark he pitches in, his defense behind him or just random luck, does a ball fall in for a hit when it shouldn't? Which is called

**babip** or batting average on balls in play. Essentially when contact is made what percentage of the time does it fall for a hit.

To eliminate those factors people started to creat DIPS theory, or defense independent pitching statistics. The most popular of these currently are FIP and xFIP. The theory at the time these statistics were created was that pitchers could only control how many batters they struck out, walked and how many home runs they allowed.

Accordingly the

**FIP** formula only takes those 3 things into account to determine how well a pitcher actually pitched. Then there is some fancy math done to make the result look like a traditional ERA number. So if a players FIP (let's say a 5.18) is bad on an ERA scale (an ERA of 5.18 is obviously awful) then it is also a bad FIP number.

**xFIP** is the same thing as FIP except that it includes how many home runs a pitchers

*should *have given up based on league average home run rates instead of how many home runs a pitcher

*actually* gave up. This makes strikeouts, walks and flyball rate the only factors that matter. For a several years this was the go to stat. It was the best at determining how well a pitcher actually pitched as well as the best at predicting the next seasons ERA.

Some types of pitchers didn't seem to play nicely with FIP and xFIP, however. Knuckleballers and players like Tim Hudson consistently seemed to have lower ERA's than their FIP or xFIP suggest they should have. It has since been acknowledged that pitchers can control how many groundballs they produce versus how many flyballs and line drives. Fly balls are turned into outs the most frequently but they can also go for home runs and extra base hits. Line drives are clearly bad all around. Ground balls, while going for hits slightly more frequently than fly balls, rarely turn into extra base hits and never into home runs. So after quite a bit of research and debate it was determined that ground ball pitchers allow fewer runs than fly ball pitchers, all else being equal, and that it is a controllable skill.

That bred the most recent statistics like

**tERA** (the "t" stands for true) and the latest, and currently best (at least that I am aware of), statistic called

**SIERA**. These use a pitcher's strike out, walk and home run rates, just like FIP and xFIP, but it also adds in how a pitcher pitches. Is he a ground ball pitcher or fly ball? What's his line drive percentage? It also takes into account what stadium a player pitches in. A home run at Yankee Stadium might not be a home run at Target Field.

FIP, xFIP, tERA and SIERA are all known as ERA estimators as they are attempting to determine what a pitchers true skill level was. As such these can be used, cautiously, to determine what a pitchers following season will look like as well.

There is another line of thought however. Some people don't care about ERA because it is too vague of a statistic. A home run is a home run; the previous statistics don't differentiate between a home run allowed when your team is winning 7-0 or when your team is tied in the bottom of the 9th inning. Clearly the home run when you're up 7-0 means much less than a home run in the bottom of the ninth of a tie ball game.

There are two basic premises of

**Win Probability Added (WPA)** and similar stats. First, a pitcher (or batter or fielder as these stats work equally well for offensive players) is more valuable, in either a positive or negative way, in close or late game situations than he is early on during the game or in blow outs. This is referred to as the

**Leverage Index**. The later in the game and the closer the score the higher the Leverage Index.

Second, because we have an extensive history of the play by play of baseball we can determine the average outcome for any given situation. We can then compare how much better or worse Mike Pelfrey did than the average pitcher. Another way to say that is we can determine how much Mike Pelfreys actions affect the Twins probability of winning a game, for better or worse, when compared to an average pitcher. Imagine Pelfrey faces a bases loaded situation. We can look back and determine what an average pitcher actually did in that situation, let's say the generic pitcher gave up a hit and 2 runs. If Pelfrey strikes a batter out we know that he actually increased the Twins odds of winning the ball game when compared to the generic pitcher that allowed 2 runs. If Pelfrey's next pitch is hit for a home run he has now decreased the probability of the Twins winning compared to the generic pitcher. When you add up all of the changes in probability throughout a game, or season, and then factor in the Leverage Index you get the stat

**Win Probability Added**. For WPA a 0 is average and for every whole number above zero one win has been added to the team's win total. Similarly every number below zero is a game lost that an average pitcher wouldn't have.

Well I didn't mean to write a novel, but for the second time today it seems I have. I didn't touch on all the statistics but those are several. If you have questions about any others or feel I misrepresented a statistic above feel free to ask or correct me. Again, sorry for the novel.