MLB DFS Analysis: Luck’s got nothing to do with it
Actually, it does.
Luck has a lot to do with success as a Major League baseball player, especially considering the general outcome of a game is decided by just a few runs. Luck can mean a ball bouncing off a bag and turning a groundout into a double. Luck can mean an outfielder falls over looking for a routine out and is still able to stand up in time to catch it (see Kyle Schwarber a couple weeks ago). Luck can mean that extra one or two feet at the fence turns a home run into a warning track flyout.
In the same light, Luck has a lot to do with our success as DFS players (and soon to be sports bettors). The difference between taking down a GPP and making $10,000 and placing 541st and making $50 can be the result of the warning track flyout. The difference between sweeping cash games and losing 40% of your action can be that bag bounce double. We play on thin margins, so understanding where your luck is more likely to matter is important.
Of course we can't control luck. We can't predict these events. But what we can do is isolate players that have been unnaturally unlucky and try to buy low on them at a reduced opportunity cost.
Are ya feelin Lucky, punk?
What does it mean to be an unlucky hitter? Well to me, it means someone that should be accounting for more hits than they are. Those hits could be anything from a bunt to a home run, they all matter. When it comes to hits, there are a multitude of metrics that we could use to try to pinpoint success or the lack of it, but something that matters across the board is hitting the ball hard.
I pulled the Advanced and Batted Ball data from Fangraphs for all hitters in 2018 with at least 10 plate appearances. Generally 10 plate appearances is a short sample, but for the purpose of this exercise I'm not necessarily concerned with something like that, as all balls in play matter for me. I then took all the hitters on the slate for this afternoon and looked up their stats, and then pulled only the players from the sample with a Hard Contact rate (Hard%) over 35%, so that we are only working with players that are indeed hitting the ball hard this season (the average Hard Contact rate is around 36%).
Next, we needed to know who has been unlucky even with a good hard contact rate. We all know that BABIP is a good way to look into guys getting what they deserve (and is considered a luck based stat) so I sorted by lowest BABIP to highest. The Top 20 in those results are here:
From here, we have a base to work with of guys that are hitting the ball hard and have a below average BABIP. Next, we would need to look at things like flyball rate, Pull%, and AVG to see if we are working with someone that is putting the ball into advantageous areas (ie. The outfield).
In the Top 10 of this list, there are three players that stick out: Adam Duvall, Khris Davis, and Jason Kipnis. All three of those players have a tiny BABIP and an even lower batting average, which shows room for normalization even on a low amount of balls in play. They all have a flyball rate above 40% and a GB/FB ratio below one, meaning that they are lifting the ball and giving us valuable distance, which can lead to extra base hits. The lowest Hard Hit rate of the group is Kipnis at 36.5%, and Davis is destroying the ball at a 47% clip. These three should see some very nice normalization sometime soon and cost an average of $3800 on Draftkings as of now.
The Hammer or the Nail?
Another awesome tool when it comes to seeking out incoming normalization (and regression) are the premium tools at DailyRoto.com, especially the batted ball trends. These tools allow you to see who is hitting the ball every which way over the course of the season and comparatively over the last 15 days.
At this point in the season, there is a lot of certainty in this or that. There are a lot of people saying that players are going to continue to hit a home run every two games and that other players will be awful all year. It is at this point in the season when understanding regression and normalization is the most beneficial, because we can buy low and sell high on players that are deviating more than they should.
And with enough luck, it'll pay off big.
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