NBA Playoff Best Bets of the Day (4/29)
Alex Christenson
The advantage to writing once a week is that I get to treat every article like an evergreen article. Every Monday, you’ll get a crash course on MLB DFS theory with a side of the day’s plays. This week, I want to talk about the most common mistake I see people make — trying to predict what will happen in that night’s games.
MLB DFS isn’t about predicting what will happen, it’s about accepting the fact that we can’t predict what will happen and using that to our advantage. It’s about understanding the full range of outcomes for each player and team and leveraging the field’s overconfidence in certain spots. It reminds me of a game I play with my mom, Words with Friends (like Scrabble). She’s an English professor and she’s brilliant, but I always beat her:
“You’re not supposed to beat me in word games, this is my domain!”
“No, Mom. This is a numbers game disguised as a word game.”
MLB DFS is the same way — it’s a game of probability, correlation and game theory… disguised as fantasy baseball.
MLB DFS Plays for Monday
Pitching
Tyler Glasnow, Los Angeles Dodgers
Tyler Glasnow is far and away the best pitcher on the slate, but that doesn’t necessarily make him the best play. However, let’s consider his full range of outcomes. His projected value is over two points better than the second-best projected value and he’s projected for almost 2.5 full strikeouts more than anyone else. This gives him a tremendous floor as well as a great ceiling. In other words, he’s worthy of both the heftiest price tag and highest ownership projection.
I’m not viewing him as a priority, but I’ll use him if we can find the savings and contrarian upside elsewhere. Speaking of…
Spencer Arrighetti, Houston Astros
Spencer Arrighetti might offer both. One reason our MLB is better and more powerful than any other in the industry is the fact that it requires very little sample to project young pitchers. It works by examining the velocity and spin rate combinations of each pitch someone throws. So the sample size for Arrighetti isn’t one start, three innings, or 19 batters faced, it’s 79 pitches. This also allows our model to be reactionary whenever a pitcher has either found something that makes them more effective or is suddenly struggling with arm fatigue or an injury not yet announced to the public.
Arrighetti got smacked around by the Royals and didn’t post particularly special numbers at any stop in the minors. This makes the argument against him rather straightforward, especially considering his matchup with Atlanta. On the other hand, it also means no one is going to play a guy with serious strikeout stuff at $5.5k.
If we were playing fantasy baseball, we’d be stacking Braves (we still might). Since we’re playing DFS, we can and should consider using Arrighetti. After all, he has the highest GPP Score.
I will only use Arrighetti if I’m using Glasnow. In the optimizer, you can create this rule like so:
By clicking the anchor next to Arrighetti’s name, you’re telling the optimizer “if Arrighetti is in a lineup, Glasnow should be too.” The 100% tells the optimizer to follow this rule in 100% of lineups. Notice, this rule, “If Arrighetti, Glasnow,” is still followed if a lineup doesn’t contain Arrighetti.
Ben Brown, Chicago Cubs
Luis Gil, New York Yankees
The theme continues with these two. Brown and Gil are also exciting youngsters. Both of them have already shown a small track record of success at the big-league level, so they may feel less risky. It appears as though the model actually likes Arrighetti’s stuff the most out of the three.
I will go to either of these guys, either with Glasnow or with each other, if I choose to stack Atlanta.
Hitting
Atlanta Braves
The Braves aren’t necessarily my favorite stack Monday, but I wanted to mention them first to drive home this concept that it’s often true that both a pitcher and the team he’s facing can be great plays. This makes sense conceptually — people are naturally afraid of uncertainty. There’s a ton of uncertainty around Arrighetti, which means people don’t want to play him, but they also may be hesitant to stack against him. We like uncertainty!
The GPP Scores tell us that’s exactly what’s happening tonight. Matt Olson, Austin Riley, Marcell Ozuna, Ronald Acuña and Jarred Kelenic all stand out at their respective positions.
New York Yankees
The Yankees have treated us quite well early on this season, and tonight is another chance to hop on the bandwagon. Gleyber Torres has the highest GPP Score by six points at the 2B position and both Aaron Judge and Giancarlo Stanton have GPP Scores over 10, thanks in large part to high HR probabilities.
Houston Astros
Yordan Alvarez leads the slate in HR odds and Kyle Tucker isn’t far behind. Yainer Diaz, Jose Altuve and Alex Bregman are also near the top of their respective positions in GPP Scores. You’re probably noticing a pattern by now — the high-powered expensive offense are all under-rostered because:
- People want to prioritize Tyler Glasnow (understandable)
- There are a ton of superstars in the outfield so it’s hard to combine these stacks in any meaningful way
- It seems the expensive offense of choice tonight is Los Angeles, so many people who don’t use Glasnow will use the savings on his team’s offense instead
Jon Singleton and Jake Meyers offer this stack a bit of affordability that the other two I mentioned do not.
OK, so at this point we’ve got three great offenses, but all use a minimum of two OF spots. It would be helpful to identify a cheaper offense that uses a max of one OF spot and some outfielders.
Seattle Mariners
If I’ve got the money for Julio Rodríguez, great, but it won’t be the end of the world if I don’t. Seattle catches my eye because of Cal Raleigh, Mitch Garver, Jorge Polanco and even J.P. Crawford (other than Bobby Witt and Mookie Betts, SS is a wasteland). They shine in GPP Score at the positions the main three stacks do not.
Final Thoughts
I will finalize all thoughts and player pool decisions in chat after the last rostership update, but hopefully this article provides a window into my lineup building process. I’m not trying to predict what will happen, that’s a fool’s errand. I’m instead trying to identify the largest rostership inefficiencies and then maximizing the lineup’s potential around it, all the while using the GPP Scores to do exactly that.
