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DFS Strategy: Finding The Best MLB Team Stack

By Matt McGarvey

Jul 17, 2016; Washington, DC, USA; Pittsburgh Pirates starting pitcher Chad Kuhl (39) pitches against the Washington Nationals in the second inning at Nationals Park. Mandatory Credit: Geoff Burke-USA TODAY Sports
Jul 17, 2016; Washington, DC, USA; Pittsburgh Pirates starting pitcher Chad Kuhl (39) pitches against the Washington Nationals in the second inning at Nationals Park. Mandatory Credit: Geoff Burke-USA TODAY Sports /
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Aug 2, 2016; Seattle, WA, USA; Seattle Mariners starting pitcher Wade LeBlanc (35) throws against the Boston Red Sox during the first inning at Safeco Field. Mandatory Credit: Joe Nicholson-USA TODAY Sports
Aug 2, 2016; Seattle, WA, USA; Seattle Mariners starting pitcher Wade LeBlanc (35) throws against the Boston Red Sox during the first inning at Safeco Field. Mandatory Credit: Joe Nicholson-USA TODAY Sports /

DFS Strategy: Finding The Best Stack

What makes daily fantasy sports unique is that it’s a game that constantly requires the player to become adaptive to changes in the market. This is evident in common MLB team stacking.

In its infancy, stacking was uncommon and therefore a contrarian and profitable strategy. As more and more people began to recognize the upside of stacking, it became a widely accepted approach to tournament play.  Looking at it in a vacuum, this took away a significant edge from stacking (there may actually be evidence that stacking is becoming a negative expected value strategy due to ownership, but we’ll talk about that later).

Going back to my latest strategy article, we know that we make money from being different from the herd. So since I think it’s safe to say that stacking on its own, is no longer contrarian. The next logical step would be to improve the accuracy in which we choose stacks.

There are plenty of theories and strategies of which stacks to pick, but I’ve been exploring a few batted ball metrics that may lead to tournament success. I’m still in the very early stages of exploring this theory in combination with the data, so I wouldn’t heavily invest in it, but it may be worth considering on days where it’s difficult to find the right stack.

Next: Thoery on how to Stack

DFS Stratgey
Aug 6, 2016; St. Louis, MO, USA; St. Louis Cardinals starting pitcher Carlos Martinez (18) looks on after giving up a three run home run to Atlanta Braves third baseman Adonis Garcia (13) during the fifth inning at Busch Stadium. Mandatory Credit: Jeff Curry-USA TODAY Sports /

Theory: Targeting pitchers with low strikeout rates, high fly ball percentages, in hitter friendly ball parks, may lead to finding stacks with upside, where the team total is under projected and therefore contrarian.

Here is my listed thought process and how I came to this theory:

  • Pitchers who fail to strike out batters will generally allow more contact
  • If pitchers allow more contact, then the chances of home runs should increase.
  • If a pitcher has a relatively high FB/GB ratio, then more batted balls have a chance of being a home run (See data for home run rates for FB and GB pitchers).
  • If the game is being played in a hitter friendly park then home runs should increase.
  • Other factors to consider, but will considerably lower the sample of potential stacks: Wind speed and direction, weather (hot/cold/dome).

Next: Which Pitchers To Target Tonight

Mandatory Credit: Jake Roth-USA TODAY Sports
Mandatory Credit: Jake Roth-USA TODAY Sports /

Most of these concepts aren’t anything new, but it provides a way in which we can implement tangible metrics into strategy form. Now obviously some of these factors will already be accounted for. For example, any pitcher who has a low strikeout rate is most likely not favored as greatly in Vegas compared to a high strike out pitcher (all other things being equal).

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That being said, if a pitcher fits this description, but has the highest opposing team run total on the slate, it’s probably not a profitable strategy to target him in tournaments because Vegas has already factored in these pitcher qualities and the opposing team may be highly owned.

Tonight slate offers one pitcher who fits this theory fairly well, Chad Kuhl and another, Wade LeBlanc, that isn’t perfect, but worth a look.

Chad Kuhl (Facing the SD Padres):

  • Low K/9 rate of 6.126
  • He has a 50% FB rate over the last 12 months in the majors, which ranks the highest on the night
  • Game is being played in a hitter friendly park (PNC Park)
  • Game time temperature of mid 80’s is fairly high in comparison to other games on the slate.

His sample size is very small as he’s only pitched in 4 games in the big leagues this year, but strikeout and fly ball rates tend to prove significant even over small samples.

Wade LeBlanc (Facing the Detroit Tigers):

  • Low K/9 of 6.656
  • 47% FB rate this year and a 57% FB rate over the last 15 days
  • Not the greatest park for hitters; more pitcher friendly

As mentioned, I won’t be betting the farm on any of the teams opposing these guys face, but I’ll surely have some exposure to the Padres tonight.

Next: How to effectively fade in tournaments

Best of luck tonight gamers!