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Find Success in Your League Using Advanced Stats (Fantasy Baseball)

by Michael Waterloo | @MichaelWaterloo | Featured Writer
Jan 29, 2019

Joey Gallo is an advanced stat darling

It’s two words that every fantasy baseball player – and baseball fan, in general – has heard.

Advanced stat.

There was a time where advanced stats, sabermetrics, or analytics were looked at as being a part of the game for the “nerds.” The game has been played the same way for years, the naysayers would say. Who needs these metrics to hit and throw a ball? Well, every team in the league, for one. Each MLB team has a dedicated analytics department finding new ways to increase their respective team’s odds to get a leg up on the competition.

To write about every advanced stat in the book, we’d need about 100,000 words. Luckily for you, avid fantasy player, we are going to boil it down to around 1,000 instead as we highlight the main advanced stats that you need to know and understand to find success in your fantasy league.

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BABIP, or Batting Average on Balls In Play, is quite literally the player’s batting average or batting average allowed balls that were hit in the field of play. BABIP excludes home runs and strikeouts. It’s useful for fantasy because it can help determine if a player has been lucky or unlucky based on their BABIP. While a BABIP of around .300 is considered average, don’t use that as a tried and true number. BABIP can fluctuate player by player, and players who have good speed tend to have a higher BABIP.


wOBA, or Weighted On-Base Average, looks not only at if a player reached base, but how a player reached base. A double is better than a single, so why not treat it as such?

It’s easier to go to a place like FanGraphs to see a player’s wOBA, but if you want to calculate it yourself, here is the formula, thanks to FanGraphs.

wOBA = .69xuBB + .72xHBP + .89x1B + 1.27x2B + 1.62x3B +2.10xHR


                                         AB + BB – IBB + SF + HBP

Makes sense, right?

It’s useful for fantasy because you get to see the overall contribution that a player is making offensively when it comes to getting on base. You want your fantasy player to have a high wOBA.


Wait, we just saw this one, didn’t we? Well, kind of. We had wOBA, but this is wOBA with an x in front of it. It stands for Expected Weighted On-Base Average.

Baseball Savant stepped its game up a few years ago with the xwOBA measuring tool. Even with wOBA looking at how a player is getting on base and the value behind each of those instances, there are still some unknowns. xwOBA factors in exit velocity (the rate of speed at which the ball leaves the player’s bat) and launch angle (the vertical angle that the ball leaves a player’s bat), while moving defense from the equation. xwOBA looks overall at the skill of a player instead of the results of their xwOBA.

xwOBA can be used to highlight players who may have been unlucky so far, similar to BABIP in that respect. Using the chart on Baseball Savant, you can see a player’s wOBA, xwOBA, and the difference between the two. You can see players who outperformed their wOBA, such as Scooter Gennett, who had a wOBA of .362 but an xwOBA of .309 for a league-leading difference of .058. You can also use it the other way to identify players who have been unlucky and should have a higher wOBA. Last year, that was Kole Calhoun, who had a wOBA of .283 and an xwOBA of .334 for a difference of -.051.


A Barrel is a ball that has an exit velocity of at least 98 mph and a launch angle between 26-30. It’s important to note, as mentions, that for every mph over 98, the range of launch angles expands.

What it’s measuring, in a sense, is how often a player is hitting the ball the near-perfect way.

Barrels are great way for fantasy owners to look a player’s power output and see how sustainable it is. Last year, Joey Gallo led the league in Brls/PA% (percentage of Barrels per plate appearance) with 11.4 and Brls/BBE% (percentage of Barrels per batted ball event) with 22.5. It’s a newer metric that can help you find a diamond in the rough with home runs.


Fielding Independent Pitching, or FIP, puts the control in the pitchers’ hand. Using ERA as a measure of success is like using wins as a measure of success. There are so many things that can happen any time a ball is struck that a pitcher can’t help. FIP is used to remove everything that happens when a ball is hit, and it measures instead walks, home runs, strikeouts, and hit-by-pitch results.

Using FIP to evaluate a pitcher will give you an idea of the pitcher’s true performance level. Use Zack Godley for instance. He had a down season in 2018 after his breakout 2017 season, as both his K% and GB% declined. His ERA went down, too, from 3.37 to 4.74. However, if you look at his FIP in 2018, it was 3.82, which indicates that he had an unlucky 2018. While he wasn’t the same pitcher he was in 2017, he also wasn’t who he seemed to be in 2018. FIP gives you a look at the true performance of a pitcher and can be used to target those who have been unlucky in trades, or sell those who have overperformed. There are other metrics like xFIP and SIERA, but get familiar with FIP before branching off into those.


For a while now, K/9 (Strikeouts per 9 innings) was the metric of choice in the fantasy community to evaluate pitchers and their strikeout performance. The shift is happening, thankfully, to K% as the go-to metric to use.

K/9 doesn’t give the true performance of a pitcher, as the pitcher can have a high K/9 but still allow a few walks or hits. Those aren’t part of the equation for K/9. For K%, though, is more of a measure of batters faced instead of at-bats. The higher the K%, the better you’re performing as a pitcher overall.


The most important stat that a pitcher can provide to you is a strikeout. When you strike a guy out, you aren’t leaving the result up to chance. SwStr%, or Swinging Strike Rate, looks at the percentage of pitches thrown by a pitcher that result in the batter swinging and missing. In a sense, it’s a stat that measures a pitcher’s stuff and pitch quality. We can, however, get into the trap of using SwStr% too often and too loosely instead of allowing a sample size to build up. Alex Chamberlain does a great job breaking it down in his piece on FanGraphs.

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Michael Waterloo is a featured writer at FantasyPros. For more from Michael, check out his archive and follow him @MichaelWaterloo.

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