We’ve covered pitcher selection multiple times in the past. There’s a good reason. The arm you choose to man the hill will play a huge role in whether you cash in fantasy MLB.

To be sure, a lot of your points will come from your hitters. But take a look at the scoring systems used at FanDuel and DraftKings. Notice how pitchers earn points. Keep in mind, a strong starter will spend the majority of the game on the mound. During that time, he can accrue a massive number of points, clearing the way for you to finish near the top and earn a cash payout.

The trick, of course, is knowing how to choose an ace who delivers. There’s a ton of criteria to consider. In the past, we’ve looked at things like ballpark selection, days rested, variations in scoring systems and MLB odds. Each one is important, but together they barely scratch the surface. You should also learn how to calculate and analyze select fantasy baseball pitching statistics.

Therein lies a huge opportunity. Most fantasy MLB players stop at batter vs. pitcher (BvP). Some of your competition won’t even make it that far. Put in the work and you’ll have valuable, insightful data from which to base your pitcher selections.

With that in mind, let’s roll up our sleeves and dig into advanced pitching stats for daily fantasy baseball.

## Batter Vs. Pitcher (BvP)

If you were to rank the statistics used by fantasy MLB players in the order of their popularity, batter vs. pitcher would surely be near the top. Ironically, BvP is one of the least reliable numbers when it comes to pitcher selection.

First, let’s define it.

BvP is a measure of how well a particular hitter performs against a particular pitcher. That might seem like useful data. After all, what is baseball if not a match-up between a pitcher and hitter?

But there’s a big problem with BvP. In order for any metric to be useful, there must be a sufficient amount of data behind it. That’s sorely lacking with this statistic.

For example, Detroit’s starting pitcher David Price is scheduled to face Minnesota tonight. The Twins’ Kennys Vargas is also expected to play. In 2014, Vargas faced Price a total of 5 times. This season, he’s faced him 3 times.

That’s nowhere near enough data to form reliable conclusions.

I realize there’s irony in including BvP in a guide about pitching stats and then dismissing it as not being worth your time. But so many fantasy baseball players use this statistic as a yardstick for evaluating pitchers that it’s important to point out its limitations.

Let’s move on to more reliable numbers.

## Defense-Independent Pitching Statistics (DIPS)

These stats provide a pure, unadulterated measure of a pitcher’s success. Aside from the catcher, they ignore players in fielding positions. Known as DIPS, they take into account the number of strikeouts, walks, home runs and batters hit by pitches. Those numbers attempt to filter out the effect of fielders on a pitcher’s performance.

Not everyone is a fan of DIPS. There are plenty of critics who question their usefulness. But it’s worth noting that a lot of successful fantasy players who swear by sabermetrics refer to these numbers when selecting pitchers.

The two most important defense-independent pitching statistics to take into account during the draft are FIP and xFIP.

## Fielding Independent Pitching: FIP & xFIP

FIP measures a pitcher’s earned run average according to how it would appear if that pitcher experienced the league average number of balls in play. It came about when folks realized that pitchers have less control over balls in play than originally assumed.

FIP attempts to strip out that variance. The fantasy player can thus drill down to the things that pitchers have more control over, such as strikeouts and walks.

**The formula is as follows:**

**FIP = (((13*HR)+(3*(BB))-(2*K))/IP) + constant**

**HR = home runs allowed
BB = walks
K = strikeouts
IP = innings pitched**

The constant is used to bring the league FIP into alignment with the league ERA. You can use any number you want for the constant, but most MLB stats enthusiasts use 3.2.

xFIP takes FIP a step backward. It replaces the pitcher’s home run total with the number of home runs he’s EXPECTED to allow. The idea is that a pitcher has limited control over whether a fly ball becomes a home run. That explains why his performance can vary significantly from season to season. A percentage, typically 10.5% or 10.6%, is applied to the pitcher’s HR number to account for that variance.

**The formula for xFIP is as follows:**

**xFIP = (((13*(xHR)+(3*(BB))-(2*K))/IP) + constant**

**If you’re cringing at the math, don’t worry. A simple spreadsheet will do the math for you.**

## Earned Run Average: ERA Vs. SIERA

As you know, a pitcher’s ERA reflects the number of earned runs he has given up per nine innings. It’s one of the simplest pitching statistics used by fantasy MLB players. No one wants to draft a pitcher who carries a high ERA. Conversely, pitchers who maintain a low ERA are in high demand.

The problem is, like BvP, ERA doesn’t tell the whole story. It leaves out a major chunk, and thus makes it difficult to infer a pitcher’s effectiveness.

SIERA, or skill-interactive ERA, seeks to fix that problem. It takes into account the same basic data that goes into calculating an ERA. But it goes a step further. SIERA includes a pitcher’s ground ball rate and fly ball rate. The idea is that ground balls turn into hits and outs more often than fly balls.

**The formula for SIERA is long and complicated. In fact, it’s probably one of the most complicated formulas you’ll come across in fantasy baseball. Here it is, just for fun:**

**SIERA = 6.145 – 16.986*(SO/PA) + 11.434*(BB/PA) – 1.858*((GB-FB-PU)/PA) + 7.653*((SO/PA)^2) +/- 6.664*(((GB-FB-PU)/PA)^2) + 10.130*(SO/PA)*((GB-FB-PU)/PA) – 5.195*(BB/PA)*((GB-FB-PU)/PA)**

If you’re already calculating xFIB, you can get by without calculating SIERA. SIERA is a better gauge of talent, but xFIB will take you most of the way with a lot less work.

If you’re interested in learning more about SIERA, here’s a reasonably good tutorial.

## Strikeouts Per Nine Innings: K/9

This statistic is self-explanatory.

A pitcher’s effectiveness is largely measured by how good he is at striking out batters. That being the case, K/9 should definitely be among the tools you use to draft starters.

This stat is calculated by multiplying a pitcher’s strikeouts by 9, and then dividing the result by the number of innings pitched. For example, Clayton Kershaw has, at this point in the 2015 season, logged 35 strikeouts over 24.1 innings pitched. His K/9 would be as follows:

K/9 = (35*9) / 24.1 = 13.07

The good news is that you’ll find this statistic posted at ESPN. You don’t have to crunch any numbers.

## Bases On Balls Per 9 Innings: BB/9

Like K/9, this stat is easy to understand and apply. It measures the number of walks given up per 9 innings pitched.

The formula to calculate BB/9 is similar to the one used to calculate K/9. Just replace the number of strikeouts with the number of walks allowed.

Let’s use Kershaw as an example. Thus far, he’s only given up 7 walks. His BB/9 would be as follows:

BB/9 = (7*9) / 24.1 = 2.61

All other variables remaining equal, you want to roster pitchers with a comparatively low BB/9. If your starter can’t control his walks, it’s probably going to be a very long and depressing game.

## Batting Average On Balls In Play: BABIP

Any discussion of pitching statistics would be incomplete without mentioning BABIP. BABIP measures the number of balls in play that turn into hits.

It’s not as straightforward as you might imagine. Recall from earlier that once a ball is in play, the pitcher has very little control over the outcome. It could turn into a hit or a home run depending on the type of ball (ground versus fly) and the fielder’s response.

That might seem to lessen the value of BABIP as a useful statistic for pitcher selection. After all, luck plays a big role. A line drive to third might get picked up and rocketed to first for an out. Or it might get missed, resulting in a hit. The pitcher has no control over the outcome after the batter connects.

But consider: if your pitcher is supported by a fantastic defense, he is more likely to have a low BABIP than would be the case if his fielders are mediocre. That means he’s more likely to turn in a better performance from a fantasy points standpoint.

While a pitcher has limited control over balls in play, BABIP still has considerable value when gauging talent. The key is to note the talent of his defense.

You can find this statistic posted under the sabermetrics tab at ESPN.

## Batted Ball Stats: Ground Balls, Fly Balls And Line Drives

These pitching statistics – GB%, FB% and LD% – are among the easiest you’ll work with. They reflect the percentage of ground balls, fly balls and line drives allowed by a pitcher. (Note that fly balls include home runs.)

Pitchers with high fly ball and line drive percentages are risky draft picks since the balls in play can easily turn into runs. By contrast, pitchers with high ground ball percentages tend to be a much safer option.

Ground balls and fly balls can be found at ESPN. You’ll also find a ratio of ground balls to fly balls (see the “G/F” column). Unfortunately, ESPN doesn’t post line drive percentages.

We’ve covered a lot of advanced statistics above. The level of analysis may seem daunting if you’re the type of fantasy MLB player who just wants to blow off steam by entering a few contests. But if you’re in it to win, crunching the above numbers can give you a distinct advantage when it comes to drafting ace starters. That alone could mean the difference between earning a cash payout and chalking up another loss.

You now have the tools you need to construct winning fantasy baseball lineups. Head over to FanDuel and DraftKings to put them to use!

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