My approach to identifying lineups worthy of stacking evolved from fantasy football where I’d look at the opposing defenses fantasy points allowed to help identify positive matchups. For DFS baseball I look at a team’s DFS points per plate appearance (ppa) and compare to the opposing pitcher’s DFS ppa. A “bad” pitcher could lead to an increase in production from the hitters and conversely, a “good” pitcher could lead to a decrease in production.
How to Read the Charts
The Minnesota Twins are facing a RHP at home (Burch Smith KCR who has faced 236 batters). On FanDuel the Twins are currently putting up 2.30 points per plate appearance (PPA) vs. RHP at home and Burch Smith is currently allowing 121% more PPA than the MLB average (2.119 PPA). Their modified PPA is 2.79 (2.30 x 121%) and the difference is simply their modified PPA minus their situational PPA. Rinse & repeat for DraftKings.
It is important to note that due to the volatility of stolen bases, I do not include them when calculating ppa.
Lineup | Situation | Opposing Pitcher | Batters Faced | ![]() |
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FanDuel MLB Avg is 2.119 | DraftKings MLB Avg is 1.616 | ||||||||
PPA x % | Mod PPA | Dif | PPA x % | Mod PPA | Dif | ||||
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RHP at home | Burch Smith KCR | 236 | 2.30 x 121% | 2.79 | +0.49 | 1.74 x 119% | 2.06 | +0.33 |
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RHP at home | Felix Pena LAA | 148 | 2.56 x 107% | 2.73 | +0.17 | 1.92 x 106% | 2.04 | +0.12 |
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LHP at home | Matt Harvey CIN | 428 | 2.32 x 112% | 2.59 | +0.27 | 1.75 x 111% | 1.95 | +0.20 |
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RHP at home | Dylan Bundy BAL | 488 | 2.27 x 113% | 2.57 | +0.31 | 1.70 x 113% | 1.92 | +0.22 |
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RHP at home | Chance Adams NYY | – | 2.55 x 100% | 2.55 | +0.00 | 1.93 x 100% | 1.93 | +0.00 |
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LHP at home | Joey Lucchesi SDP | 325 | 2.54 x 99% | 2.50 | -0.04 | 1.91 x 99% | 1.88 | -0.02 |
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RHP at home | Marco Estrada TOR | 397 | 2.01 x 116% | 2.34 | +0.33 | 1.56 x 116% | 1.80 | +0.24 |
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RHP on road | Ivan Nova PIT | 487 | 2.12 x 110% | 2.33 | +0.22 | 1.61 x 112% | 1.80 | +0.19 |
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RHP at home | Lance McCullers Jr. HOU | 506 | 2.35 x 96% | 2.26 | -0.09 | 1.78 x 94% | 1.68 | -0.10 |
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RHP on road | Kenta Maeda LAD | 415 | 2.40 x 92% | 2.22 | -0.18 | 1.81 x 92% | 1.67 | -0.14 |
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LHP at home | Andrew Suarez SFG | 414 | 2.14 x 101% | 2.16 | +0.02 | 1.64 x 103% | 1.69 | +0.05 |
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RHP at home | Jordan Zimmermann DET | 297 | 2.00 x 109% | 2.18 | +0.18 | 1.52 x 110% | 1.67 | +0.15 |
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RHP at home | Jose Urena MIA | 491 | 2.24 x 98% | 2.20 | -0.04 | 1.69 x 98% | 1.66 | -0.03 |
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RHP on road | Nathan Eovaldi BOS | 248 | 2.20 x 94% | 2.06 | -0.14 | 1.67 x 95% | 1.58 | -0.08 |
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RHP on road | Zack Wheeler NYM | 508 | 2.23 x 91% | 2.04 | -0.20 | 1.70 x 92% | 1.55 | -0.14 |
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RHP on road | Jeremy Hellickson WSN | 297 | 2.10 x 95% | 1.99 | -0.11 | 1.60 x 96% | 1.54 | -0.06 |
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RHP at home | Kevin Gausman ATL | 534 | 1.79 x 108% | 1.93 | +0.14 | 1.37 x 110% | 1.51 | +0.13 |
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LHP at home | Tyler Anderson COL | 518 | 1.99 x 96% | 1.92 | -0.07 | 1.51 x 96% | 1.45 | -0.05 |
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RHP on road | Corey Kluber CLE | 561 | 2.23 x 84% | 1.87 | -0.36 | 1.70 x 86% | 1.46 | -0.24 |
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RHP on road | Zach Eflin PHI | 320 | 1.93 x 96% | 1.85 | -0.08 | 1.50 x 97% | 1.45 | -0.05 |
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LHP on road | James Paxton SEA | 505 | 2.13 x 88% | 1.87 | -0.26 | 1.61 x 88% | 1.42 | -0.19 |
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LHP at home | Austin Gomber STL | 90 | 2.03 x 93% | 1.89 | -0.14 | 1.55 x 90% | 1.40 | -0.15 |
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LHP on road | Mike Minor TEX | 460 | 1.63 x 112% | 1.83 | +0.20 | 1.28 x 112% | 1.43 | +0.15 |
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LHP at home | Carlos Rodon CHW | 238 | 2.14 x 85% | 1.82 | -0.31 | 1.63 x 84% | 1.37 | -0.25 |
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RHP on road | Kyle Hendricks CHC | 527 | 1.76 x 99% | 1.74 | -0.02 | 1.37 x 100% | 1.37 | +0.00 |
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RHP on road | Jose Berrios MIN | 563 | 1.96 x 88% | 1.72 | -0.24 | 1.51 x 88% | 1.33 | -0.18 |
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RHP on road | Freddy Peralta MIL | 192 | 2.04 x 86% | 1.75 | -0.29 | 1.55 x 82% | 1.27 | -0.28 |
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LHP on road | Blake Snell TBR | 474 | 2.00 x 77% | 1.54 | -0.46 | 1.54 x 77% | 1.20 | -0.35 |
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RHP on road | Clay Buchholz ARI | 206 | 1.87 x 81% | 1.52 | -0.36 | 1.46 x 83% | 1.21 | -0.25 |
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RHP on road | Edwin Jackson OAK | 166 | 1.72 x 89% | 1.53 | -0.18 | 1.33 x 89% | 1.18 | -0.15 |
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