IT’S ALMOST HERE! The Major League Baseball season is quickly arriving. We are talking about my favorite sport not only from a DFS perspective, but also as a fan. It’s one of my first loves, and from a sports perspective, it is my first love. How much do I love baseball? Let’s just say that when my wife and I were discussing when we wanted to start trying to have a baby, I made a requirement that the due date needed to be before, or after, opening day.

MLB DFS is a great game. It pays to be different, and it also pays to understand the game more than any other sport. With baseball, you actually have the ability to not only cash, but WIN tournaments without hitting the nuts at every position.

As Opening Day approaches, the first thing we have to know is the rules and scoring for the DFS Site we’re playing on. Both FanDuel and DraftKings have made changes to their scoring this year and even though they are smaller changes, they definitely can impact how we look at things to find value. These changes are also over time, going to affect pricing as well.

Below are FanDuel’s MLB Scoring. Everything has been increased by 3 over last year. The other notable changes are that we no longer are going to receive negative points for hitter outs or caught stealing.

The notable changes for DraftKings are that you can no longer stack hitters from a team. That number is now five. Also, one of their OF spots is now a UT spot. Which in my mind make no sense at all, but allows you to have more flexibility with your roster. You also, no longer have to roster hitters from three different teams. They have taken away the caught stealing in their scoring as well.

One of the first questions new players ask when coming into DFS is what is the difference was between a “cash game” lineup and a “GPP” lineup. As I thought about the best way to describe to him the difference, I remembered back when I first started in DFS and wondering the same thing. The “generic” version is that a cash game lineup is “safer” and has players in it that are more consistent. A GPP lineup has more risk and has the boom or bust type of players that you are looking for in order to push your way up the leader boards and hopefully take down a top 5% place.

The funny thing about it is this is indeed a “generic” definition. It in no way gives me an idea of what I should be looking for in order to determine what type of player Mark Teixeria is. As a DFS Rook, the first thing that you look at is the name, because that’s what stands out. We all know of players like Giancarlo Stanton, Alex Rodriguez, Mike Trout, and Bryce Harper, but what type of player are they in order for us to make sure that we are taking advantage of the type of player they are in real life, so we know what type of contest to play them in for DFS purposes?

There are four stats for hitters that I look at religiously. They are wOBA, ISO, BABIP, and wRC+. Each of them are important in their own way, and each of them, if used and applied correctly, can help you narrow down your player pool based on the pitcher they are facing that day.

For example, 98.9% of the DFS community didn’t play Bryce Harper when he was facing off against Madison Bumgarner early last year. Why would you? Bumgarner has been one of the best pitchers in baseball over the last 2 seasons, and Harper is a left handed batter. As you begin to break down the numbers you begin to see that Harper had a .318 avg against left handers last year.

Below is a breakdown of each statistic I utilize and how I apply it to DFS purposes.

***All Stats are broken down by handedness of pitcher facing***

wOBA: weighted On Base Average

Simply put, wOBA is very similar to your traditional triple slash line of Avg./OBP/SLG that produces and OPS stat. While this is also very useful for DFS purposes, it does not however take into account how well a player will contribute to his teams run scoring. As we know, not all hits are created equal. A double is worth more points in DFS than a single. Batting average and on base percentage assume that they are. wOBA combines all the aspects of hitting into one stat, weighting them proportionately to their run value. An walk is calculated the lowest all the way up to a home run which is weighted the heaviest. I look at a players wOBA vs RHP and LHP. For pitchers you can also find the wOBA they have allowed vs. RHB and LHB. The only thing that wOBA doesn’t account for is the ballpark adjustment. Which is ok, because my value of park adjustment changes based on the situation (Pitcher facing and weather). Below are 2 charts that illustrate what is considered a good wOBA and the league average last year by position.



Image Source: Fangraphs.com

Now, what does this mean for DFS? If you take wOBA vs a pitcher’s handedness for a batter, and compare it to the wOBA that a pitcher allows against that handed batter, then we have a starting point for players that we want to target against that pitcher. Say a pitcher allows a .284 wOBA to RHB for the year, and we have a hitter that has a .387 wOBA vs that handed pitcher, we can take the average of the two and have an idea of the medium that we are looking at.

Example: (P wOBA allowed) .284 + .387 (Hitters wOBA vs Handedness of Pitcher) = .671/2 = .335 (wOBA medium)

The reason I look at the wOBA medium is because you can never expect the hitter or pitcher to fully dominate the matchup in most scenarios. Obviously you have the games where Kershaw is going against the Rockies (who struggle vs. LHP) and you favor the pitcher more. Due to the variance in baseball, there is no sure fire way to project what a hitter or pitcher is going to do.

Once you find which pitchers allow a high wOBA to the handedness of hitter, you have a pitcher you can target and the start to a pool of players to look at for cash games.

ISO: Isolated Power

ISO is a very simple stat. It’s the sexy statistic. If chicks dig the long ball, the DFS digs ISO! ISO is the stat that measures a hitter’s raw power and tells you how often a player hits for extra bases. This is important in DFS because more bases means more points, and the whole purpose of the game is to score the most points. Although ISO wasn’t created for DFS, it certainly feels like it was. ISO is better than SLG because if Hunter Pence is 4 for 10 with 4 singles, he has a .400 avg and a .400 SLG%. While David Ortiz is 1 for 10 with a home run and zero singles, he has a .100 avg and a .400 SLG. There is no way to tell just from the SLG % which player you want to take in tournaments to get the power you will need in order to win. ISO eliminates that. Hunter Pence would have a .000 ISO where Ortiz would have a .300 ISO. In this instance, why wouldn’t we take Ortiz to get the power? It doesn’t replace wOBA, just helps you identify if the player you are looking at has power to go along with the wOBA. The perfect scenario is that a player has a good wOBA and ISO vs a pitcher that allows a poor wOBA and ISO. When you get this, it looks like Mike Trout vs. Kyle Kendrick.

Again, I work out the average for the hitters for that day based on their ISO vs pitcher handedness and the pitchers ISO allowed vs. Handedness.

To calculate a pitchers ISO allowed we take the difference of a pitchers slugging percentage allowed and batting average allowed.

EXAMPLE: Scott Kazmir allows .343 SLG % to LHB and .220 AVG to LHB

.343 – .220 = .123 ISO allowed to LHB

The league average for ISO changes from year to year. You can use this information to figure out whether or not you have a plus or negative match-up for the players you’re looking at.

BABIP: Batting average on balls in play

BABIP is the stat that, in my opinion, tells us how lucky a player has been when putting the ball in play. With today’s game, the shift is a part of the game that DFS players have come to hate when it’s against their hitters, but love when it’s for their pitchers. This stat is easy to understand. It takes out everything that isn’t a ball in the field of play. Walks, strikeouts, home runs are all excluded when calculating this statistic. Here is the equation.

BABIP = (H – HR) / (AB – K – HR + SF)

BABIP is a great statistic to see how “lucky” or “unlucky” the player you’re looking at is at getting a hit against the handedness of the pitcher facing is. Remember, the shift is a part of today’s game that is here to stay. One thing to take into account is whether or not the team you’re facing shifts a lot. If you’re deciding between two players that are both left handed at the same price, and are similar in other metrics in a cash game, then look to BABIP. This is also a great way to find value. The league average usually hovers right around the .305 mark. If you are trying to decide against a second baseman, then take the BABIP of the hitter vs. the pitcher’s handedness, plus the BABIP of the pitcher facing that handedness of hitter, and divide by 2 to receive your BABIP medium. Compare against the league average BABIP for that handedness of hitter facing that handedness of pitcher, and you can use these numbers to find decide between the two players and find value that you are looking for.

wRC+: Weighted runs created plus

The final statistic that is important to putting it all together is weighted runs created plus. This is an improved statistic of Bill James’ Runs Created statistic, which was an attempt to create a value on a player’s total offensive value. Great idea for DFS purposes!

I won’t bore you with the formula, but similar to the other three stats that we use, we need to split based on handedness of pitcher for the batter, find the average, and compare to the league average.

wRC+ is park and league adjusted, which is especially helpful when comparing players around the league to those that play for the Rockies, which play half of their games at Coors Field. The league average for position players is around 100, and every point above 100 is a percentage point above league average. For example, if Brett Gardner has a 134 wRC+ against RHP this year then he has created 34% more runs against RHP compared to league average. This can allow us to find out whether a player is a good value and more likely to produce fantasy points for our lineups that night given the matchup he has.

Obviously, there are still two weeks before the season starts, and one of the big advantages we have over new people coming in is that historical data is more likely to repeat itself in baseball than any other sport. The great thing about MLB DFS though, is that it also pays to be contrarian more than any other sport. Fading Mike Trout in a dream matchup because his ownership percentage is going to be through the roof is more advantageous in MLB because on any night, he could only go 2-4 with 2 singles and a run scored. Not bad, but not what we pay an elite price for.

I will be back sometime next week to discuss with you how to look at stats for pitchers. There are things we can use from this to go along with that, and as we gear up for opening day, I will show you my Advanced Stats chart and go over how to use all of this information to build winning DFS lineups.