Fantasy Baseball for Smart People: How to Profit Big During MLB Season
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Billy Beane and the Oakland A's flipped Major League Baseball on its head by questioning widely accepted narratives and approaching roster construction from a scientific, data-driven viewpoint. "Moneyball" revolutionized baseball, and now it's your turn to be the GM.
you stack… Historically, stacking three or four bats has been less volatile than not stacking at all! It’s only once we hit the five-player mark that stacking has been risky, and even then, the downside is minimal. From these numbers alone—dramatically increased upside with only slightly greater risk—I think we can conclude that stacking isn’t necessarily a bad idea in cash games. Do I always stack three/four bats in my head-to-head and 50/50 leagues? No, but I certainly don’t avoid it,
split. Right-handed bats are worse against right-handed pitching, but the effect isn’t nearly as great as lefty-on-lefty; actually, right-handed batters have been nearly equally likely to take a righty deep as they are to hit a home run against a left-handed pitcher. The difference on the right side of the chart is what I care about most, as it shows that left-handed hitters are far more pitcher-dependent for their production (or at least their power) than right-handed bats. Overall, there’s no
salary cap allocation data can help you understand if you’re on the right track. We’ve already seen that lineups that paid more for pitching performed better last season, in both cash games and GPPs. And though there are certainly times I’ll take a flier on a high-upside pitcher with lots of strikeout potential, I generally like to save some money on my bats, too. But what sort of batter salary cap allocation method has worked best in the past: a high/low strategy or a balanced one? For the
production of pitchers, broken down by salary and ownership. Here’s a different look at this data... The top third of pitchers in terms of ownership outproduce the top third in terms of salary, which I think speaks to the level of predictability at the position. That consistency is linked to pricing; you don’t need to pay for the top arms because they’re expensive, but rather because their predictability is the impetus for them being priced in the top tier. Basically, DraftKings is more
to have much higher utilization than RB2. We’ll say 40 percent versus 10 percent. If RB1 has a big game—let’s say 20 points—you’d gain an advantage over 60 percent of the field, but you’d still need to compete with 40 percent on even footing. Compare that to RB2; if he goes off, you’d need to compete with just 1-in-10 other users on an even playing field. That difference—a field that’s one-fourth the size—suggests RB2 is the superior play unless you believe that RB1 is more than four times as